Geographic variation in phenotypic divergence between two hybridizing field cricket species

Patterns of morphological divergence across species' ranges can provide insight into local adaptation and speciation. In this study, we compared phenotypic divergence among 4,221 crickets from 337 populations of two closely related species of field cricket, Gryllus firmus and G. pennsylvanicus, and their hybrids. We found that these species differ across their geographic range in key morphological traits, such as body size and ovipositor length, and we directly compared phenotype with genotype for a subset of crickets to demonstrate nuclear genetic introgression, phenotypic intermediacy of hybrids, and essentially unidirectional mitochondrial introgression. We discuss how these morphological traits relate to life history differences between the two species. Our comparisons across geographic areas support prior research suggesting that cryptic variation within G. firmus may represent different species. Our study highlights how variable morphology can be across wide-ranging species and the importance of studying reproductive barriers in more than one or two transects of a hybrid zone

The Effects of Heterospecific Mating Frequency on the Strength of Cryptic Reproductive Barriers

Heterospecific mating frequency is critical to hybrid zone dynamics and can directly impact the strength of reproductive barriers and patterns of introgression. The effectiveness of post-mating prezygotic (PMPZ) reproductive barriers, which include reduced fecundity via heterospecific matings and conspecific sperm precedence, may depend on the number, identity and order of mates. Studies of PMPZ barriers suggest that they may be important in many systems, but whether these barriers are effective at realistic heterospecific mating frequencies has not been tested. Here, we evaluate the strength of cryptic reproductive isolation in two leaf beetles (Chrysochus auratus and C. cobaltinus) in the context of a range of heterospecific mating frequencies observed in natural populations. We found both species benefited from multiple matings, but the benefits were greater in C. cobaltinus and extended to heterospecific matings. We found that PMPZ barriers greatly limited hybrid production by C. auratus females with moderate heterospecific mating frequencies, but that their effectiveness diminished at higher heterospecific mating frequencies. In contrast, there was no evidence for PMPZ barriers in C. cobaltinus females at any heterospecific mating frequency. We show that integrating realistic estimates of cryptic isolation with information on relative abundance and heterospecific mating frequency in the field substantially improves our understanding of the strong directional bias in F1 production previously documented in the Chrysochus hybrid zone. Our results demonstrate that heterospecific mating frequency is critical to understanding the impact of cryptic post-copulatory barriers on hybrid zone structure and dynamics, and that future studies of such barriers should incorporate field-relevant heterospecific mating frequencies

The contribution of sex chromosome conflict to disrupted spermatogenesis in hybrid house mice

Incompatibilities on the sex chromosomes are important in the evolution of hybrid male sterility, but the evolutionary forces underlying this phenomenon are unclear. House mice (Mus musculus) lineages have provided powerful models for understanding the genetic basis of hybrid male sterility. X chromosome-autosome interactions cause strong incompatibilities in Mus musculus F1 hybrids, but variation in sterility phenotypes suggests a more complex genetic basis. Additionally, X-Y chromosome conflict has resulted in rapid expansions of ampliconic genes with dosage-dependent expression that is essential to spermatogenesis. Here we evaluated the contribution of X-Y lineage mismatch to male fertility and stage-specific gene expression in hybrid mice. We performed backcrosses between two house mouse subspecies to generate reciprocal Y-introgression strains and used these strains to test the effects of X-Y mismatch in hybrids. Our transcriptome analyses of sorted spermatid cells revealed widespread overexpression of the X chromosome in sterile F1 hybrids independent of Y chromosome subspecies origin. Thus, postmeiotic overexpression of the X chromosome in sterile F1 mouse hybrids is likely a downstream consequence of disrupted meiotic X-inactivation rather than X-Y gene copy number imbalance. Y-chromosome introgression did result in subfertility phenotypes and disrupted expression of several autosomal genes in mice with an otherwise non-hybrid genomic background, suggesting that Y-linked incompatibilities contribute to reproductive barriers, but likely not as a direct consequence of X-Y conflict. Collectively, these findings suggest that rapid sex chromosome gene family evolution driven by genomic conflict has not resulted in strong male reproductive barriers between these subspecies of house mice

Accounting for quality improvement during the conduct of embedded pragmatic clinical trials within healthcare systems: NIH Collaboratory case studies

Embedded pragmatic clinical trials (ePCTs) and quality improvement (QI) activities often occur simultaneously within healthcare systems (HCSs). Embedded PCTs within HCSs are conducted to test interventions and provide evidence that may impact public health, health system operations, and quality of care. They are larger and more broadly generalizable than QI initiatives, and may generate what is considered high-quality evidence for potential use in care and clinical practice guidelines. QI initiatives often co-occur with ePCTs and address the same high-impact health questions, and this co-occurrence may dilute or confound the ability to detect change as a result of the ePCT intervention. During the design, pilot, and conduct phases of the large-scale NIH Collaboratory Demonstration ePCTs, many QI initiatives occurred at the same time within the HCSs. Although the challenges varied across the projects, some common, generalizable strategies and solutions emerged, and we share these as case studies. KEY LESSONS: Study teams often need to monitor, adapt, and respond to QI during design and the course of the trial. Routine collaboration between ePCT researchers and health systems stakeholders throughout the trial can help ensure research and QI are optimally aligned to support high-quality patient-centered care

Homage to Felsenstein 1981, or why are there so few/many species?

If there are no constraints on the process of speciation, then the number of species might be expected to match the number of available niches and this number might be indefinitely large. One possible constraint is the opportunity for allopatric divergence. In 1981, Felsenstein used a simple and elegant model to ask if there might also be genetic constraints. He showed that progress towards speciation could be described by the build-up of linkage disequilibrium among divergently selected loci and between these loci and those contributing to other forms of reproductive isolation. Therefore, speciation is opposed by recombination, because it tends to break down linkage disequilibria. Felsenstein then introduced a crucial distinction between "two-allele" models, which are subject to this effect, and "one-allele" models, which are free from the recombination constraint. These fundamentally important insights have been the foundation for both empirical and theoretical studies of speciation ever since

Two Origins for the Gene Encoding α-Isopropylmalate Synthase in Fungi

BACKGROUND: The biosynthesis of leucine is a biochemical pathway common to prokaryotes, plants and fungi, but absent from humans and animals. The pathway is a proposed target for antimicrobial therapy. METHODOLOGY/PRINCIPAL FINDINGS: Here we identified the leuA gene encoding alpha-isopropylmalate synthase in the zygomycete fungus Phycomyces blakesleeanus using a genetic mapping approach with crosses between wild type and leucine auxotrophic strains. To confirm the function of the gene, Phycomyces leuA was used to complement the auxotrophic phenotype exhibited by mutation of the leu3+ gene of the ascomycete fungus Schizosaccharomyces pombe. Phylogenetic analysis revealed that the leuA gene in Phycomyces, other zygomycetes, and the chytrids is more closely related to homologs in plants and photosynthetic bacteria than ascomycetes or basidiomycetes, and suggests that the Dikarya have acquired the gene more recently. CONCLUSIONS/SIGNIFICANCE: The identification of leuA in Phycomyces adds to the growing body of evidence that some primary metabolic pathways or parts of them have arisen multiple times during the evolution of fungi, probably through horizontal gene transfer events

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

The North American tree-ring fire-scar network

Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders