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

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences

BACKGROUND: Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). RESULTS: We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10 CONCLUSION: These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences

Background Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). Results We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 x 10(-8)), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 x 10(-8)), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 x 10(-21)) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. Conclusion These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.Peer reviewe

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

MRI characterization of 124 CT-indeterminate focal hepatic lesions: evaluation of clinical utility

Objective. To evaluate the diagnostic yield of MRI performed for characterization of focal hepatic lesions that are interpreted as indeterminate on CT. Patients and methods. In a retrospective investigation, 124 indeterminate focal hepatic lesions in 96 patients were identified on CT examinations over 5 years from 1997 to 2001. All patients had MRI performed for the liver within 6 weeks of their CT examination. CT and MR images were reviewed independently by two separate groups of two radiologists. The value of MRI in characterizing these lesions was assessed. Diagnoses were confirmed based on histology, characteristic imaging features, and clinical follow-up . Results. MRI definitely characterized 73 lesions (58%) that were indeterminate on CT. MRI was accurate in 72/73 of these lesions. MRI could not definitely characterize 51 lesions (42%). Ten lesions were not visualized on MRI, and follow-up imaging confirmed that no lesion was present in eight of these cases (pseudolesions). Conclusion. MRI is valuable for the characterization of indeterminate focal hepatic lesions detected on CT.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75168/1/13651820701216950.pd

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

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

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