Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease.

BACKGROUND: X-chromosome inactivation (XCI) is an epigenetic process that occurs during early development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies on the methylation status of the methylation-sensitive restriction enzyme (Hpall) binding site present in proximity of short tandem polymorphic repeats on the androgen receptor (AR) gene. This approach using one locus results in uninformative or inconclusive data for 10-20% of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Herein, we develop a method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 11 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. RESULTS: In comparison to the AR clinical test for identification of X inactivation, our method was concordant with the AR method in 9 samples, discordant in 1, and provided a measure of X inactivation in 1 sample with uninformative clinical results. We applied this method on an additional 81 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. CONCLUSIONS: This study presents the use of transcriptome and exome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in a cohort of female patients with different types of suspected rare genetic disease.

Non-random Codon Usage of Synonymous and Non-synonymous Mutations in the Human HLA-A Gene.

The structure and function of human leucocyte antigen (HLA-A) is well known and is an extremely variable protein. From the public HLA-A database, we chose 26 high frequency HLA-A alleles (45% of sequenced alleles). Using five arbitrary references from these alleles, we analyzed synonymous mutations at the third codon position (sSNP3) and non-synonymous mutations (NSM). Both mutation types showed non-random locations of 29 sSNP3 codons and 71 NSM codons in the five reference lists. Most sSNP3 codons show identical mutation types with many mutations resulting from cytosine deamination. We proposed 23 ancestral parents of sSNP3 in five reference sequences using conserved parents in five unidirectional codons and 18 majority parents in reciprocal codons. These 23 proposed ancestral parents show exclusive codon usage of G3 or C3 parents located on both DNA strands that mutate to A3 or T3 variants mostly (76%) by cytosine deamination The sSNP3 and NSM show clear separation of the two variant types with most sSNP3 located in conserved areas in exons 2, 3 and 4, compared to most NSM appearing in two Variable Areas with no sSNP3 in the latter parts of exons 2 (α1) and 3 (α2). The Variable Areas contain NSM (polymorphic) residues at the center of the groove that bind the foreign peptide. We find distinctly different mutation patterns in NSM codons from those of sSNP3. Namely, G-C to A-T mutation frequency was much smaller, suggesting that evolutional pressures of deamination and other mechanisms applied to the two areas are significantly different.

Principles and mechanisms of asymmetric cell division.

Asymmetric cell division (ACD) is an evolutionarily conserved mechanism used by prokaryotes and eukaryotes alike to control cell fate and generate cell diversity. A detailed mechanistic understanding of ACD is therefore necessary to understand cell fate decisions in health and disease. ACD can be manifested in the biased segregation of macromolecules, the differential partitioning of cell organelles, or differences in sibling cell size or shape. These events are usually preceded by and influenced by symmetry breaking events and cell polarization. In this Review, we focus predominantly on cell intrinsic mechanisms and their contribution to cell polarization, ACD and binary cell fate decisions. We discuss examples of polarized systems and detail how polarization is established and, whenever possible, how it contributes to ACD. Established and emerging model organisms will be considered alike, illuminating both well-documented and underexplored forms of polarization and ACD.

One versus two biological parents with mental disorders: Relationship to educational attainment in the next generation.

BACKGROUND: Both maternal and, separately, paternal mental illness are associated with diminished academic attainment among children. However, the differential impacts of diagnostic type and degree of parental burden (e.g. one v. both parents affected) on these functional outcomes are unknown. METHODS: Using the Swedish national patient (NPR) and multi-generation (MGR) registers, 2 226 451 children (1 290 157 parental pairs), born 1 January 1973-31 December 1997, were followed through 31 December 2013. Diagnostic status of all cohort members was defined for eleven psychiatric disorders, and families classed by exposure: (1) parents affected with any disorder, (2) parents affected with a disorder group (e.g. neuropsychiatric disorders), and (3) parents affected with a specific disorder (e.g. ADHD). Pairs were further defined as 'unaffected,' 'single-affected,', or 'dual-affected.' Among offspring, the study evaluated fulfillment of four academic milestones, from compulsory (primary) school through University (college). Sensitivity analyses considered the impact of child's own mental health, as well as parental education, on main effects. RESULTS: Marked reductions in the odds of achievement were observed, emerging at the earliest levels of schooling for both single-affected [adjusted odds ratio (aOR), 0.50; 95% CI 0.49-0.51] and dual-affected (aOR 0.29, 95% CI 0.28-0.30) pairs and persisting thereafter [aOR range (single), 0.52-0.65; aOR range (dual), 0.30-0.40]. This pattern was repeated for analyses within diagnosis/diagnostic group. Main results were robust to adjustment for offspring mental health and parent education level. CONCLUSIONS: Parental mental illness is associated with profound reductions in educational attainment in the subsequent generation, with children from dual-affected families at uniquely high risk.

Stable populations and Hardy-Weinberg equilibrium.

The conditions on the mating matrix associated with a stable equilibrium are specified for an autosomal locus with five alleles. This points the way to the maintenance of Hardy-Weinberg proportions with non-random mating. The myth of random mating is exposed.

Non-Random Island Nucleation in the Electrochemical Roughening on Pt(111).

Many chemical surface systems develop ordered nano-islands during repeated reaction and restoration. Platinum is used in electrochemical energy applications, like fuel cells and electrolysers, although it is scarce, expensive, and degrades. During oxidation-reduction cycles, simulating device operation, nucleation and growth of nano-islands occurs that eventually enhances the dissolution. Preventing nucleation would be the most effective solution. However, little is known about the atomic details of the nucleation; a process almost impossible to observe. Here, we analyze the nuclei-distance distribution mapping out the underlying atomic mechanism: a rarely observed, non-random nucleation takes place. Special, preferential nucleation sites that a priori do not exist, develop initially via a precursor and eventually form a semi-ordered Pt-oxide structure. This precursor mechanism seems to be general, possibly explaining also the nano-island formation on other surfaces/reactions.

Sampling bias exaggerates a textbook example of a trophic cascade.

Understanding trophic cascades in terrestrial wildlife communities is a major challenge because these systems are difficult to sample properly. We show how a tradition of non-random sampling has confounded this understanding in a textbook system (Yellowstone National Park) where carnivore [Canis lupus (wolf)] recovery is associated with a trophic cascade involving changes in herbivore [Cervus canadensis (elk)] behaviour and density that promote plant regeneration. Long-term data indicate a practice of sampling only the tallest young plants overestimated regeneration of overstory aspen (Populus tremuloides) by a factor of 4-7 compared to random sampling because it favoured plants taller than the preferred browsing height of elk and overlooked non-regenerating aspen stands. Random sampling described a trophic cascade, but it was weaker than the one that non-random sampling described. Our findings highlight the critical importance of basic sampling principles (e.g. randomisation) for achieving an accurate understanding of trophic cascades in terrestrial wildlife systems.

Reorganization of inter-chromosomal interactions in the 2q37-deletion syndrome.

Chromosomes occupy distinct interphase territories in the three-dimensional nucleus. However, how these chromosome territories are arranged relative to one another is poorly understood. Here, we investigated the inter-chromosomal interactions between chromosomes 2q, 12, and 17 in human mesenchymal stem cells (MSCs) and MSC-derived cell types by DNA-FISH We compared our findings in normal karyotypes with a three-generation family harboring a 2q37-deletion syndrome, featuring a heterozygous partial deletion of histone deacetylase 4 (HDAC4) on chr2q37. In normal karyotypes, we detected stable, recurring arrangements and interactions between the three chromosomal territories with a tissue-specific interaction bias at certain loci. These inter-chromosomal interactions were confirmed by Hi-C. Interestingly, the disease-related HDAC4 deletion resulted in displaced inter-chromosomal arrangements and altered interactions between the deletion-affected chromosome 2 and chromosome 12 and/or 17 in 2q37-deletion syndrome patients. Our findings provide evidence for a direct link between a structural chromosomal aberration and altered interphase architecture that results in a nuclear configuration, supporting a possible molecular pathogenesis.

The changes in plant and soil C pools and their C:N stoichiometry control grassland N retention under elevated N inputs.

Nitrogen (N) retention is a critical ecosystem function for maintaining soil fertility and mitigating pollution caused by anthropogenic N input. However, it has not yet been elucidated how responses of plant and soil regulate ecosystem N retention. Here, we combined a 14-year N addition experiment in a temperate steppe with a global meta-analysis in grasslands, to assess changes in carbon (C) pool size and stoichiometric C:N ratio of plant and soil components and evaluate the contribution of each component to grassland N retention under increasing N levels. We found that N addition increased N storage in the plant pool by stimulating biomass production and reducing tissue C:N at the community level. However, the non-random loss of forbs and legumes associated with a low C:N ratio partially offset the decline in community-level C:N ratio, thereby diminishing the positive net effect of N enrichment on plant N storage. The observed increase in soil N storage was predominantly determined by the decrease in C:N ratio of topsoil, while no changes were detected in the subsoil. On 14-year time scale, the upper limitation of N retention capacity in our study site was 167.02 g N/m2 . Global meta-analysis further indicated that a decade's N addition significantly increased the N storage in shoot, root and topsoil through enhancing the C pool and decreasing the C:N ratio, while did not affect those of subsoil. However, the positive correlation between the response of subsoil N storage and treatment duration further indicates that, though the accumulation of added N lagged behind that of topsoil, subsoil could play an important role in N retention on a longer time scale. Our study demonstrated that the enhanced plant productivity and altered physiological metabolism indicated by the decreased C:N ratio jointly determined grassland ecosystem N retention. The capacity of the grassland ecosystem to retain exogenous N input is limited, especially for a large amount of N input that occurs in a short period. However, in the context of chronically rising N deposition, the long-term N retention capacity of grasslands should largely depend on the response of subsoil, especially after topsoil N is saturated.

Evidence and risk indicators of non-random sampling in clinical trials in implant dentistry: A systematic appraisal.

AIM: Analysis of distribution of p-values of continuous differences between test and controls after randomization provides evidence of unintentional error, non-random sampling, or data fabrication in randomized controlled trials (RCTs). We assessed evidence of highly unusual distributions of baseline characteristics of subjects enrolled in clinical trials in implant dentistry. MATERIALS AND METHODS: RCTs published between 2005 and 2020 were systematically searched in Pubmed, Embase, and Cochrane databases. Baseline patient data were extracted from full text articles by two independent assessors. The hypothesis of non-random sampling was tested by comparing the expected and the observed distribution of the p-values of differences between test and controls after randomization. RESULTS: One-thousand five-hundred and thirty-eight unique RCTs were identified, of which 409 (26.6%) did not report baseline characteristics of the population, and 671 (43.6%) reported data in forms other than mean and standard deviation and could not be used to assess their random sampling. Four-hundred and fifty-eight trials with 1449 baseline variables in the form of mean and standard deviation were assessed. The study observed an over-representation of very small p-values [<.001, 1.38%, 95% confidence interval (CI) 0.85-2.12 compared to the expected 0.10%, 95% CI 0.00-0.26]. No evidence of over-representation of larger p-values was observed. Unusual distributions were present in 2.38% of RCTs and more frequent in non-registered trials, in studies supported by non-industry funding, and in multi-centre RCTs. CONCLUSIONS: The inability to assess random sampling due to insufficient reporting in 26.6% of trials requires attention. In trials reporting suitable baseline data, unusual distributions were uncommon, and no evidence of data fabrication was detected, but there was evidence of non-random sampling. Continued efforts are necessary to ensure high integrity and trust in the evidence base of the field.

mixIndependR: a R package for statistical independence testing of loci in database of multi-locus genotypes.

BACKGROUND: Multi-locus genotype data are widely used in population genetics and disease studies. In evaluating the utility of multi-locus data, the independence of markers is commonly considered in many genomic assessments. Generally, pairwise non-random associations are tested by linkage disequilibrium; however, the dependence of one panel might be triplet, quartet, or other. Therefore, a compatible and user-friendly software is necessary for testing and assessing the global linkage disequilibrium among mixed genetic data. RESULTS: This study describes a software package for testing the mutual independence of mixed genetic datasets. Mutual independence is defined as no non-random associations among all subsets of the tested panel. The new R package "mixIndependR" calculates basic genetic parameters like allele frequency, genotype frequency, heterozygosity, Hardy-Weinberg equilibrium, and linkage disequilibrium (LD) by mutual independence from population data, regardless of the type of markers, such as simple nucleotide polymorphisms, short tandem repeats, insertions and deletions, and any other genetic markers. A novel method of assessing the dependence of mixed genetic panels is developed in this study and functionally analyzed in the software package. By comparing the observed distribution of two common summary statistics (the number of heterozygous loci [K] and the number of share alleles [X]) with their expected distributions under the assumption of mutual independence, the overall independence is tested. CONCLUSION: The package "mixIndependR" is compatible to all categories of genetic markers and detects the overall non-random associations. Compared to pairwise disequilibrium, the approach described herein tends to have higher power, especially when number of markers is large. With this package, more multi-functional or stronger genetic panels can be developed, like mixed panels with different kinds of markers. In population genetics, the package "mixIndependR" makes it possible to discover more about admixture of populations, natural selection, genetic drift, and population demographics, as a more powerful method of detecting LD. Moreover, this new approach can optimize variants selection in disease studies and contribute to panel combination for treatments in multimorbidity. Application of this approach in real data is expected in the future, and this might bring a leap in the field of genetic technology. AVAILABILITY: The R package mixIndependR, is available on the Comprehensive R Archive Network (CRAN) at: https://cran.r-project.org/web/packages/mixIndependR/index.html .

A graphical model for skewed matrix-variate non-randomly missing data.

Epidemiological studies on periodontal disease (PD) collect relevant bio-markers, such as the clinical attachment level (CAL) and the probed pocket depth (PPD), at pre-specified tooth sites clustered within a subject's mouth, along with various other demographic and biological risk factors. Routine cross-sectional evaluation are conducted under a linear mixed model (LMM) framework with underlying normality assumptions on the random terms. However, a careful investigation reveals considerable non-normality manifested in those random terms, in the form of skewness and tail behavior. In addition, PD progression is hypothesized to be spatially-referenced, i.e. disease status at proximal tooth-sites may be different from distally located sites, and tooth missingness is non-random (or informative), given that the number and location of missing teeth informs about the periodontal health in that region. To mitigate these complexities, we consider a matrix-variate skew-$t$ formulation of the LMM with a Markov graphical embedding to handle the site-level spatial associations of the bivariate (PPD and CAL) responses. Within the same framework, the non-randomly missing responses are imputed via a latent probit regression of the missingness indicator over the responses. Our hierarchical Bayesian framework powered by relevant Markov chain Monte Carlo steps addresses the aforementioned complexities within an unified paradigm, and estimates model parameters with seamless sharing of information across various stages of the hierarchy. Using both synthetic and real clinical data assessing PD status, we demonstrate a significantly improved fit of our proposition over various other alternative models.

Molecular Mechanisms of Skewed X-Chromosome Inactivation in Female Hemophilia Patients-Lessons from Wide Genome Analyses.

INTRODUCTION: Hemophilia A (HA) is an X-linked bleeding disorder caused by factor VIII (FVIII) deficiency or dysfunction due to F8 gene mutations. HA carriers are usually asymptomatic because their FVIII levels correspond to approximately half of the concentration found in healthy individuals. However, in rare cases, a carrier may exhibit symptoms of moderate to severe HA primarily due to skewed inactivation of her non-hemophilic X chromosome. AIM: The aim of the study was to investigate X-chromosome inactivation (XCI) patterns in HA carriers, with special emphasis on three karyotypically normal HA carriers presenting with moderate to severe HA phenotype due to skewed XCI, in an attempt to elucidate the molecular mechanism underlying skewed XCI in these symptomatic HA carriers. The study was based on the hypothesis that the presence of a pathogenic mutation on the non-hemophilic X chromosome is the cause of extreme inactivation of that X chromosome. METHODS: XCI patterns were studied by PCR analysis of the CAG repeat region in the HUMARA gene. HA carriers that demonstrated skewed XCI were further studied by whole-exome sequencing (WES) followed by X chromosome-targeted bioinformatic analysis. RESULTS: All three HA carriers presenting with the moderate to severe HA phenotype due to skewed XCI were found to carry pathogenic mutations on their non-hemophilic X chromosomes. Patient 1 was diagnosed with a frameshift mutation in the PGK1 gene that was associated with familial XCI skewing in three generations. Patient 2 was diagnosed with a missense mutation in the SYTL4 gene that was associated with familial XCI skewing in two generations. Patient 3 was diagnosed with a nonsense mutation in the NKAP gene that was associated with familial XCI skewing in two generations. CONCLUSION: Our results indicate that the main reason for skewed XCI in our female HA patients was negative selection against cells with a disadvantage caused by an additional deleterious mutation on the silenced X chromosome, thus complicating the phenotype of a monogenic X-linked disease. Based on our study, we are currently offering the X inactivation test to symptomatic hemophilia carriers and plan to expand this approach to symptomatic carriers of other X-linked diseases, which can be further used in pregnancy planning.

Influence of demographically-realistic mortality schedules on vaccination strategies in age-structured models.

Because demographic realism complicates analysis, mathematical modelers either ignore demography or make simplifying assumptions (e.g., births and deaths equal). But human populations differ demographically, perhaps most notably in their mortality schedules. We developed an age-stratified population model with births, deaths, aging and mixing between age groups. The model includes types I and II mortality as special cases. We used the gradient approach (Feng et al., 2015, 2017) to explore the impact of mortality patterns on optimal strategies for mitigating vaccine-preventable diseases such as measles and rubella, which the international community has targeted for eradication. Identification of optimal vaccine allocations to reduce the effective reproduction number Rv under various scenarios is presented. Numerical simulations of the model with various types of mortality are carried out to ascertain the long-term effects of vaccination on disease incidence. We conclude that both optimal vaccination strategies and long-term effects of vaccination may depend on demographic assumptions.

Dynamics of social interactions, in the flow of information and disease spreading in social insects colonies: Effects of environmental events and spatial heterogeneity.

The relationship between division of labor and individuals' spatial behavior in social insect colonies provides a useful context to study how social interactions influence the spreading of elements (which could be information, virus or food) across distributed agent systems. In social insect colonies, spatial heterogeneity associated with variations of individual task roles, affects social contacts, and thus the way in which agent moves through social contact networks. We used an Agent Based Model (ABM) to mimic three realistic scenarios of elements' transmission, such as information, food or pathogens, via physical contact in social insect colonies. Our model suggests that individuals within a specific task interact more with consequences that elements could potentially spread rapidly within that group, while elements spread slower between task groups. Our simulations show a strong linear relationship between the degree of spatial heterogeneity and social contact rates, and that the spreading dynamics of elements follow a modified nonlinear logistic growth model with varied transmission rates for different scenarios. Our work provides important insights on the dual-functionality of physical contacts. This dual-functionality is often driven via variations of individual spatial behavior, and can have both inhibiting and facilitating effects on elements' transmission rates depending on environment. The results from our proposed model not only provide important insights on mechanisms that generate spatial heterogeneity, but also deepen our understanding of how social insect colonies balance the benefit and cost of physical contacts on the elements' transmission under varied environmental conditions.

Suppression of Non-Random Fertilization by MHC Class I Antigens.

Hermaphroditic invertebrates and plants have a self-recognition system on the cell surface of sperm and eggs, which prevents their self-fusion and enhances non-self-fusion, thereby contributing to genetic variation. However, the system of sperm-egg recognition in mammals is under debate. To address this issue, we explored the role of major histocompatibility complex class I (MHC class I, also known as histocompatibility 2-Kb or H2-Kb and H2-Db in mice) antigens by analyzing H2-Kb-/-H2-Db-/-ß2-microglobulin (ß2M)-/- triple-knockout (T-KO) male mice with full fertility. T-KO sperm exhibited an increased sperm number in the perivitelline space of wild-type (WT) eggs in vitro. Moreover, T-KO sperm showed multiple fusion with zona pellucida (ZP)-free WT eggs, implying that the ability of polyspermy block for sperm from T-KO males was weakened in WT eggs. When T-KO male mice were intercrossed with WT female mice, the percentage of females in progeny increased. We speculate that WT eggs prefer fusion with T-KO sperm, more specifically X-chromosome-bearing sperm (X sperm), suggesting the presence of preferential (non-random) fertilization in mammals, including humans.

Estimating the cumulative rate of SARS-CoV-2 infection.

Accurate estimates of the cumulative incidence of SARS-CoV-2 infection remain elusive. Among the reasons for this are that tests for the virus are not randomly administered, and that the most commonly used tests can yield a substantial fraction of false negatives. In this article, we propose a simple and easy-to-use Bayesian model to estimate the infection rate, which is only partially identified. The model is based on the mapping from the fraction of positive test results to the cumulative infection rate, which depends on two unknown quantities: the probability of a false negative test result and a measure of testing bias towards the infected population. Accumulating evidence about SARS-CoV-2 can be incorporated into the model, which will lead to more precise inference about the infection rate.

Estimates of COVID-19 Cases across Four Canadian Provinces.

This article estimates population infection rates from coronavirus disease 2019 (COVID-19) across four Canadian provinces from late March to early May 2020. The analysis combines daily data on the number of conducted tests and diagnosed cases with a methodology that corrects for non-random testing. We estimate the relationship between daily changes in the number of conducted tests and the fraction of positive cases in the non-random sample (typically less than 1 percent of the population) and apply this gradient to extrapolate the predicted fraction of positive cases if testing were expanded to the entire population. Over the sample period, the estimated population infection rates were 1.7-2.6 percent in Quebec, 0.7-1.4 percent in Ontario, 0.5-1.2 percent in Alberta, and 0.2-0.4 percent in British Columbia. In each province, these estimates are substantially below the average positive case rate, consistent with non-random testing of higher-risk populations. The results also imply widespread undiagnosed COVID-19 infection. For each identified case by mid-April, we estimate there were roughly 12 population infections.

Les auteurs estiment les taux d'infection par le coronavirus 2019 (COVID­19) de la population de quatre provinces canadiennes, de la fin de mars au début de mai 2020. Dans leur analyse, ils associent les données quotidiennes relatives au nombre de tests effectués et au nombre de cas diagnostiqués au moyen d'une méthodologie grâce à laquelle les données sont corrigées pour tenir compte du caractère non aléatoire des tests. Ils estiment la relation entre l'évolution quotidienne du nombre de tests effectués et de la proportion de cas positifs dans l'échantillon non aléatoire (généralement moins de 1 pour cent de la population) et utilisent ce gradient pour extrapoler une prédiction quant à la proportion de cas positifs qui seraient diagnostiqués si les tests étaient administrés à la population entière. Au cours de la période d'échantillonnage, les taux estimatifs d'infection de la population se situent dans les intervalles suivants : 1,7 à 2,6 pour cent au Québec, 0,7 à 1,4 pour cent en Ontario, 0,5 à 1,2 pour cent en Alberta et 0,2 à 0,4 pour cent en Colombie-Britannique. Dans chaque province, ces estimations se révèlent largement inférieures au taux moyen de cas positifs, ce qui s'explique par l'administration non aléatoire des tests aux populations qui présentent un risque plus élevé. Ces résultats indiquent également que les cas de COVID­19 non diagnostiqués sont largement répandus. Pour chaque cas diagnostiqué jusqu'à la mi-avril, les auteurs estiment à environ 12 le nombre de cas d'infection dans la population.

Dispersal syndromes can impact ecosystem functioning in spatially structured freshwater populations.

Dispersal can strongly influence ecological and evolutionary dynamics. Besides the direct contribution of dispersal to population dynamics, dispersers often differ in their phenotypic attributes from non-dispersers, which leads to dispersal syndromes. The consequences of such dispersal syndromes have been widely explored at the population and community level; however, to date, ecosystem-level effects remain unclear. Here, we examine whether dispersing and resident individuals of two different aquatic keystone invertebrate species have different contributions to detrital processing, a key function in freshwater ecosystems. Using experimental two-patch systems, we found no difference in leaf consumption rates with dispersal status of the common native species Gammarus fossarum. In Dikerogammarus villosus, however, a Ponto-Caspian species now expanding throughout Europe, dispersers consumed leaf litter at roughly three times the rate of non-dispersers. Furthermore, this put the contribution of dispersing D. villosus to leaf litter processing on par with native G. fossarum, after adjusting for differences in organismal size. Given that leaf litter decomposition is a key function in aquatic ecosystems, and the rapid species turnover in freshwater habitats with range expansions of non-native species, this finding suggests that dispersal syndromes may have important consequences for ecosystem functioning.

The causes of disproportionate non-random mortality among life-cycle stages.

The emergent properties of the collection of species in a natural community, such as diversity and the distribution of relative abundances, are influenced by both niche-based and neutral (stochastic) processes. This pluralistic view of the natural world reconciles theory with empirical observations better than does either a strictly niche- or neutrality-based perspective. Even so, rules (or rules of thumb) that govern the relative contributions that niche-based and stochastic processes make as communities assemble remain only vaguely formulated and incompletely tested. For example, the translation of non-random (non-neutral) ecological processes, which differentially sort among species within a community, into species-compositional patterns may occur more influentially within some demographic subsets of organisms than within others. In other words, the relative contributions of niche vs. neutral processes may vary among age-, size-, or stage-classes. For example, non-random patterns of mortality that occur among seedlings in a rain forest, or among newly settled juveniles in communities of sessile marine communities, could be more influential than non-random mortality during later stages in determining overall community diversity. We propose two alternative, mutually compatible, hypotheses to account for different levels of influence from mortality among life-cycle stages toward producing non-random patterns in organismal communities. The Turnover Model simply posits that those demographic classes characterized by faster rates of turnover contribute greater influence in the short-term as sufficient mortality gives rise to non-random changes to the community, as well as over the longer-term as multiple individuals of a given fast-turnover demographic class transition into later classes compared to each individual that ratchets from a slow-turnover starting class into a later class. The Turnover Model should apply to most communities of organisms. The Niche Model, which posits that niche-based processes are more influential in some demographic classes relative to others, may alternatively or additionally apply to communities. We also propose several alternative mechanisms, especially relevant to forest trees, that could cause dynamics consistent with the Niche Model. These mechanisms depend on differences among demographic classes in the extent of demographic variation that individual organisms experience through their trait values or neighborhood conditions.