The ancestral levels of transcription and the evolution of sexual phenotypes in filamentous fungi

Changes in gene expression have been hypothesized to play an important role in the evolution of divergent morphologies. To test this hypothesis in a model system, we examined differences in fruiting body morphology of five filamentous fungi in the Sordariomycetes, culturing them in a common garden environment and profiling genome-wide gene expression at five developmental stages. We reconstructed ancestral gene expression phenotypes, identifying genes with the largest evolved increases in gene expression across development. Conducting knockouts and performing phenotypic analysis in two divergent species typically demonstrated altered fruiting body development in the species that had evolved increased expression. Our evolutionary approach to finding relevant genes proved far more efficient than other gene deletion studies targeting whole genomes or gene families. Combining gene expression measurements with knockout phenotypes facilitated the refinement of Bayesian networks of the genes underlying fruiting body development, regulation of which is one of the least understood processes of multicellular development.

CDKN2A copy number loss in HPV- and HPV+ head and neck cancer to indicate poor prognosis: An integrated genomic and clinical TCGA analysis

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Background: HPV infection is associated with high p16 expression and relatively good prognosis in head and neck cancers. Analysis of CDKN2A, the gene that encodes the p16 tumor suppressor protein, may further elucidate the association between HPV status and prognosis in head and neck squamous cell carcinomas (HNSCCs). We aimed to identify whether CDKN2A copy number loss was associated with poor survival in HNSCCs stratified by HPV status. Methods: We analyzed The Cancer Genome Atlas (TCGA) head and neck cancer data, integrating genomic measurements with clinical metadata. Patients 85 years old or younger with a primary tumor in the oral cavity, oropharynx, hypopharynx, or larynx were included. Defining CDKN2A copy number loss as a relative log2 copy number ratio < −0.6, CDKN2A mRNA and p16 protein expression levels were compared to confirm significant differences in gene transcription and translation between the copy number loss and non-copy number loss patient groups. Overall survival (OS) and disease-free survival (DFS) were evaluated to characterize prognostic differences between genomic groups. Results: 397 patients negative for HPV (HPV−) and 91 patients positive for HPV (HPV+) HNSCC were identified. 139 HPV− patients and 9 HPV+ patients demonstrated CDKN2A copy number loss. The CDKN2A copy number loss group expressed significantly lower levels of CDKN2A mRNA and p16 protein than did the non-copy number loss group in both HPV+ and HPV− disease. Median OS for HPV− patients with and without CDKN2A copy number loss was 21.8 months and 46.0 months (P = 0.02). Median DFS was 12.0 and 19.4 months respectively (P < 0.05). Median OS for HPV+ patients with and without CDKN2A copy number loss was 12.7 months and 57.4 months (P = 0.004) and median DFS was 7.0 and 36.6 months respectively (P = 0.02). Conclusions: CDKN2A copy number loss was associated with low CDKN2A mRNA and p16 protein expression, with poor prognosis in terms of disease-free and overall survival.

Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up

Background

Lung adenocarcinomas (LUADs) lead to the majority of deaths attributable to lung cancer. We performed whole-exome sequencing (WES) and immune profiling analyses of a unique set of clinically annotated early-stage LUADs to better understand the pathogenesis of this disease and identify clinically relevant molecular markers.

Methods

We performed WES of 108 paired stage I-III LUADs and normal lung tissues using the Illumina HiSeq 2000 platform. Ten immune markers (PD-L1, PD-1, CD3, CD4, CD8, CD45ro, CD57, CD68, FOXP3 and Granzyme B) were profiled by imaging-based immunohistochemistry (IHC) in a subset of LUADs (n = 92). Associations among mutations, immune markers and clinicopathological variables were analyzed using ANOVA and Fisher's exact test. Cox proportional hazards regression models were used for multivariate analysis of clinical outcome.

Results

LUADs in this cohort exhibited an average of 243 coding mutations. We identified 28 genes with significant enrichment for mutation. SETD2-mutated LUADs exhibited relatively poor recurrence- free survival (RFS) and mutations in STK11 and ATM were associated with poor RFS among KRAS-mutant tumors. EGFR, KEAP1 and PIK3CA mutations were predictive of poor response to adjuvant therapy. Immune marker analysis revealed that LUADs in smokers and with relatively high mutation burdens exhibited increased levels of immune markers. Analysis of immunophenotypes revealed that LUADs with STK11 mutations exhibited relatively low levels of infiltrating CD4+/CD8+ T-cells indicative of a muted immune response. Tumoral PD-L1 was significantly elevated in TP53 mutant LUADs whereas PIK3CA mutant LUADs exhibited markedly down-regulated PD-L1 expression. LUADs with TP53 or KEAP1 mutations displayed relatively increased CD57 and Granzyme B levels indicative of augmented natural killer (NK) cell infiltration.

Conclusion(s)

Our study highlights molecular and immune phenotypes that warrant further analysis for their roles in clinical outcomes and personalized immune-based therapy of LUAD.

PhyloOncology: Understanding cancer through phylogenetic analysis

Despite decades of research and an enormity of resultant data, cancer remains a significant public health problem. New tools and fresh perspectives are needed to obtain fundamental insights, to develop better prognostic and predictive tools, and to identify improved therapeutic interventions. With increasingly common genome-scale data, one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics, a scientific discipline used in diverse fields. From grouping subsets of cancer samples to tracing subclonal evolution during cancer progression and metastasis, the use of phylogenetics is a powerful systems biology approach. Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

New insights on the sister lineage of percomorph fishes with an anchored hybrid enrichment dataset

Percomorph fishes represent over 17,100 species, including several model organisms and species of economic importance. Despite continuous advances in the resolution of the percomorph Tree of Life, resolution of the sister lineage to Percomorpha remains inconsistent but restricted to a small number of candidate lineages. Here we use an anchored hybrid enrichment (AHE) dataset of 132 loci with over 99,000 base pairs to identify the sister lineage of percomorph fishes. Initial analyses of this dataset failed to recover a strongly supported sister clade to Percomorpha, however, scrutiny of the AHE dataset revealed a bias towards high GC content at fast-evolving codon partitions (GC bias). By combining several existing approaches aimed at mitigating the impacts of convergence in GC bias, including RY coding and analyses of amino acids, we consistently recovered a strongly supported clade comprised of Holocentridae (squirrelfishes), Berycidae (Alfonsinos), Melamphaidae (bigscale fishes), Cetomimidae (flabby whalefishes), and Rondeletiidae (redmouth whalefishes) as the sister lineage to Percomorpha. Additionally, implementing phylogenetic informativeness (PI) based metrics as a filtration method yielded this same topology, suggesting PI based approaches will preferentially filter these fast-evolving regions and act in a manner consistent with other phylogenetic approaches aimed at mitigating GC bias. Our results provide a new perspective on a key issue for studies investigating the evolutionary history of more than one quarter of all living species of vertebrates.

Climatic and evolutionary drivers of phase shifts in the plague epidemics of colonial India

Immune heterogeneity in wild host populations indicates that disease-mediated selection is common in nature. However, the underlying dynamic feedbacks involving the ecology of disease transmission, evolutionary processes, and their interaction with environmental drivers have proven challenging to characterize. Plague presents an optimal system for interrogating such couplings: Yersinia pestis transmission exerts intense selective pressure driving the local persistence of disease resistance among its wildlife hosts in endemic areas. Investigations undertaken in colonial India after the introduction of plague in 1896 suggest that, only a decade after plague arrived, a heritable, plague-resistant phenotype had become prevalent among commensal rats of cities undergoing severe plague epidemics. To understand the possible evolutionary basis of these observations, we developed a mathematical model coupling environmentally forced plague dynamics with evolutionary selection of rats, capitalizing on extensive archival data from Indian Plague Commission investigations. Incorporating increased plague resistance among rats as a consequence of intense natural selection permits the model to reproduce observed changes in seasonal epidemic patterns in several cities and capture experimentally observed associations between climate and flea population dynamics in India. Our model results substantiate Victorian era claims of host evolution based on experimental observations of plague resistance and reveal the buffering effect of such evolution against environmental drivers of transmission. Our analysis shows that historical datasets can yield powerful insights into the transmission dynamics of reemerging disease agents with which we have limited contemporary experience to guide quantitative modeling and inference.

Quantifying Transmission of Clostridium difficile within and outside Healthcare Settings

To quantify the effect of hospital and community-based transmission and control measures on Clostridium difficile infection (CDI), we constructed a transmission model within and between hospital, community, and long-term care-facility settings. By parameterizing the model from national databases and calibrating it to C. difficile prevalence and CDI incidence, we found that hospitalized patients with CDI transmit C. difficile at a rate 15 (95% CI 7.2-32) times that of asymptomatic patients. Long-term care facility residents transmit at a rate of 27% (95% CI 13%-51%) that of hospitalized patients, and persons in the community at a rate of 0.1% (95% CI 0.062%-0.2%) that of hospitalized patients. Despite lower transmission rates for asymptomatic carriers and community sources, these transmission routes have a substantial effect on hospital-onset CDI because of the larger reservoir of hospitalized carriers and persons in the community. Asymptomatic carriers and community sources should be accounted for when designing and evaluating control interventions.

PhyInformR: phylogenetic experimental design and phylogenomic data exploration in R

Background

Analyses of phylogenetic informativeness represent an important step in screening potential or existing datasets for their proclivity toward convergent or parallel evolution of molecular sites. However, while new theory has been developed from which to predict the utility of sequence data, adoption of these advances have been stymied by a lack of software enabling application of advances in theory, especially for large next-generation sequence data sets. Moreover, there are no theoretical barriers to application of the phylogenetic informativeness or the calculation of quartet internode resolution probabilities in a Bayesian setting that more robustly accounts for uncertainty, yet there is no software with which a computationally intensive Bayesian approach to experimental design could be implemented.

Results

We introduce PhyInformR, an open source software package that performs rapid calculation of phylogenetic information content using the latest advances in phylogenetic informativeness based theory. These advances include modifications that incorporate uneven branch lengths and any model of nucleotide substitution to provide assessments of the phylogenetic utility of any given dataset or dataset partition. PhyInformR provides new tools for data visualization and routines optimized for rapid statistical calculations, including approaches making use of Bayesian posterior distributions and parallel processing. By implementing the computation on user hardware, PhyInformR increases the potential power users can apply toward screening datasets for phylogenetic/genomic information content by orders of magnitude.

Conclusions

PhyInformR provides a means to implement diverse substitution models and specify uneven branch lengths for phylogenetic informativeness or calculations providing quartet based probabilities of resolution, produce novel visualizations, and facilitate analyses of next-generation sequence datasets while incorporating phylogenetic uncertainty through the use parallel processing. As an open source program, PhyInformR is fully customizable and expandable, thereby allowing for advanced methodologies to be readily integrated into local bioinformatics pipelines.

Software is available through CRAN and a package containing the software, a detailed manual, and additional sample data is also provided freely through github: https://github.com/carolinafishes/PhyInformR.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0837-3) contains supplementary material, which is available to authorized users.

PathScore: a web tool for identifying altered pathways in cancer data

PathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.

AVAILABILITY AND IMPLEMENTATION

Web application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at: github.com/sggaffney/pathscore with a GPLv3 license.

CONTACT

stephen.gaffney@yale.edu.

Cost-Effectiveness of Pertussis Vaccination During Pregnancy in the United States

Vaccination against pertussis has reduced the disease burden dramatically, but the most severe cases and almost all fatalities occur in infants too young to be vaccinated. Recent epidemiologic evidence suggests that targeted vaccination of mothers during pregnancy can reduce pertussis incidence in their infants. To evaluate the cost-effectiveness of antepartum maternal vaccination in the United States, we created an age-stratified transmission model, incorporating empirical data on US contact patterns and explicitly modeling parent-infant exposure. Antepartum maternal vaccination incurs costs of $114,000 (95% prediction interval: 82,000, 183,000) per quality-adjusted life-year, in comparison with the strategy of no adult vaccination, and is cost-effective in the United States according to World Health Organization criteria. By contrast, vaccinating a second parent is not cost-effective, and vaccination of either parent postpartum is strongly dominated by antepartum maternal vaccination. Nonetheless, postpartum vaccination of mothers who were not vaccinated antepartum improves upon the current recommendation of untargeted adult vaccination. Additionally, the temporary direct protection of the infant due to maternal antibody transfer has efficacy for infants comparable to that conferred to toddlers by the full primary vaccination series. Efficient protection against pertussis for infants begins before birth. We highly recommend antepartum vaccination for as many US mothers as possible.

Cost-effectiveness of next-generation vaccines: The case of pertussis

Despite steady vaccination coverage rates, pertussis incidence in the United States has continued to rise. This public health challenge has motivated calls for the development of a new vaccine with greater efficacy and duration of protection. Any next-generation vaccine would likely come at a higher cost, and must provide sufficient health benefits beyond those provided by the current vaccine in order to be deemed cost-effective. Using an age-structured transmission model of pertussis, we quantified the health and economic benefits of a next-generation vaccine that would enhance either the efficacy or duration of protection of the childhood series, the duration of the adult booster, or a combination. We developed a metric, the maximum cost-effective price increase (MCPI), to compare the potential value of such improvements. The MCPI estimates the per-dose price increase that would maintain the cost-effectiveness of pertussis vaccination. We evaluated the MCPI across a range of potential single and combined improvements to the pertussis vaccine. As an upper bound, we found that a next-generation vaccine which could achieve perfect efficacy for the childhood series would permit an MCPI of $18 per dose (95% CI: $12-$31). Pertussis vaccine improvements that extend the duration of protection to an average of 75 years would allow for an MCPI of $22 per dose for the childhood series (CI: $10-$33) or $12 for the adult booster (CI: $4-$18). Despite the short duration of the adult booster, improvements to the childhood series could be more valuable than improvements to the adult booster. Combining improvements in both efficacy and duration, a childhood series with perfect efficacy and average duration of 75 years would permit an MCPI of $39 per dose, the highest of any scenario evaluated. Our results highlight the utility of the MCPI metric in evaluating potential vaccines or other interventions when prices are unknown.

Determinants of Human African Trypanosomiasis Elimination via Paratransgenesis

Human African trypanosomiasis (HAT), transmitted by tsetse flies, has historically infected hundreds of thousands of individuals annually in sub-Saharan Africa. Over the last decade, concerted control efforts have reduced reported cases to below 10,000 annually, bringing complete elimination within reach. A potential technology to eliminate HAT involves rendering the flies resistant to trypanosome infection. This approach can be achieved through the introduction of transgenic Sodalis symbiotic bacteria that have been modified to produce a trypanocide, and propagated via Wolbachia symbionts, which confer a reproductive advantage to the paratransgenic tsetse. However, the population dynamics of these symbionts within tsetse flies have not yet been evaluated. Specifically, the key factors that determine the effectiveness of paratransgenesis have yet to be quantified. To identify the impact of these determinants on T.b. gambiense and T.b. rhodesiense transmission, we developed a mathematical model of trypanosome transmission that incorporates tsetse and symbiont population dynamics. We found that fecundity and mortality penalties associated with Wolbachia or recombinant Sodalis colonization, probabilities of vertical transmission, and tsetse migration rates are fundamental to the feasibility of HAT elimination. For example, we determined that HAT elimination could be sustained over 25 years when Wolbachia colonization minimally impacted fecundity or mortality, and when the probability of recombinant Sodalis vertical transmission exceeded 99.9%. We also found that for a narrow range of recombinant Sodalis vertical transmission probability (99.9–90.6% for T.b. gambiense and 99.9–85.8% for T.b. rhodesiense), cumulative HAT incidence was reduced between 30% and 1% for T.b. gambiense and between 21% and 3% for T.b. rhodesiense, although elimination was not predicted. Our findings indicate that fitness and mortality penalties associated with paratransgenic symbionts, as well as tsetse migration rates, are instrumental to HAT elimination, and should be a key focus in the development of paratransgenic symbionts.

Human African trypanosomiasis, also known as sleeping sickness, is a parasitic disease transmitted by tsetse flies in sub-Saharan Africa. The disease leads to death if not treated. Recent control efforts have reduced the burden of disease from hundreds of thousands of cases per year to fewer than 10,000 cases annually. A potential strategy to completely eliminate sleeping sickness involves genetically modifying the symbiotic bacteria, which are vertically transmitted from mother to offspring, in order to investigate which factors are most important for the successful elimination of human African trypanosomiasis. We found that sleeping sickness was eliminated only when the genetically modified symbionts were successfully transmitted from mother to offspring, and did not reduce fertility or increase mortality in tsetse. We additionally identified tsetse migration rate as an important factor for sleeping sickness elimination.

Genomic and Gene-Expression Comparisons among Phage-Resistant Type-IV Pilus Mutants of Pseudomonas syringae pathovar phaseolicola

Pseudomonas syringae pv. phaseolicola (Pph) is a significant bacterial pathogen of agricultural crops, and phage Φ6 and other members of the dsRNA virus family Cystoviridae undergo lytic (virulent) infection of Pph, using the type IV pilus as the initial site of cellular attachment. Despite the popularity of Pph/phage Φ6 as a model system in evolutionary biology, Pph resistance to phage Φ6 remains poorly characterized. To investigate differences between phage Φ6 resistant Pph strains, we examined genomic and gene expression variation among three bacterial genotypes that differ in the number of type IV pili expressed per cell: ordinary (wild-type), non-piliated, and super-piliated. Genome sequencing of non-piliated and super-piliated Pph identified few mutations that separate these genotypes from wild type Pph--and none present in genes known to be directly involved in type IV pilus expression. Expression analysis revealed that 81.1% of gene ontology (GO) terms up-regulated in the non-piliated strain were down-regulated in the super-piliated strain. This differential expression is particularly prevalent in genes associated with respiration--specifically genes in the tricarboxylic acid cycle (TCA) cycle, aerobic respiration, and acetyl-CoA metabolism. The expression patterns of the TCA pathway appear to be generally up and down-regulated, in non-piliated and super-piliated Pph respectively. As pilus retraction is mediated by an ATP motor, loss of retraction ability might lead to a lower energy draw on the bacterial cell, leading to a different energy balance than wild type. The lower metabolic rate of the super-piliated strain is potentially a result of its loss of ability to retract.

The Impact of Enhanced Screening and Treatment on Hepatitis C in the United States

BACKGROUND

The effectiveness of interferon-free direct-acting antivirals (DAA) in treating chronic hepatitis C virus (HCV) is limited by low screening and treatment rates, particularly among people who inject drugs (PWIDs).

METHODS

To evaluate the levels of screening and treatment with interferon-free DAAs that are required to control HCV incidence and HCV-associated morbidity and mortality, we developed a transmission model, stratified by age and by injection drug use, and calibrated it to epidemiological data in the United States from 1992 to 2014. We quantified the impact of administration of DAAs at current and at enhanced screening and treatment rates, focusing on outcomes of HCV incidence, prevalence, compensated and decompensated cirrhosis, hepatocellular carcinoma, liver transplants, and mortality from 2015 to 2040.

RESULTS

Increasing annual treatment of patients 4-fold-from the approximately 100 000 treated historically to 400 000-is predicted to prevent 526 084 (95% confidence interval, 466 615-593 347) cases of cirrhosis and 256 315 (201 589-316 114) HCV-associated deaths. By simultaneously increasing treatment capacity and increasing the number of HCV infections diagnosed, total HCV prevalence could fall to as low as 305 599 (222 955-422 110) infections by 2040. Complete elimination of HCV transmission in the United States through treatment with DAAs would require nearly universal screening of PWIDs, with an annual treatment rate of at least 30%.

CONCLUSIONS

Interferon-free DAAs are projected to achieve marked reductions in HCV-associated morbidity and mortality. Aggressive expansion in HCV screening and treatment, particularly among PWIDs, would be required to eliminate HCV in the United States.

Optimizing age of cytomegalovirus screening and vaccination to avert congenital disease in the US

Cytomegalovirus (CMV) infection is the leading cause of congenital cognitive deficit, visual impairment and hearing loss in the US. Clinical trials are underway to evaluate the efficacy of CMV vaccine candidates in seronegative females. The optimal age of such vaccination depends on the interplay among age-specific transmission dynamics, vaccine efficacy and vaccine waning. We developed an age-structured model of CMV transmission dynamics in the US and estimated age-specific transmission rates of CMV based on age-stratified CMV prevalence, congenital infections per birth, breastfeeding patterns and demographic data. We found that the optimal age of vaccination depended on the duration of vaccine protection. For most scenarios, the optimal age of vaccination was between 19 and 21 years of age. However, for a rapidly waning vaccine, the optimal age of vaccination can shift to infants under 1 year. This shift arises when the duration of vaccine efficacy is too brief to offer appreciable protection during the child-bearing years. In this case, it becomes more effective to achieve indirect protection by reducing transmission from infants, the transmissibility from whom was estimated to be an order of magnitude higher than other age classes. Knowledge of vaccine waning is paramount to optimizing CMV vaccination and is thus a key parameter for longitudinal clinical evaluation.

Inferring the Origin of Metastases from Cancer Phylogenies

Determining the evolutionary history of metastases is a key problem in cancer biology. Several recent studies have presented inferences regarding the origin of metastases based on phylogenies of cancer lineages. Many of these studies have concluded that the observed monophyly of metastatic subclones favored metastasis-to-metastasis spread ("a metastatic cascade" rather than parallel metastases from the primary tumor). In this article, we argue that identifying a monophyletic clade of metastatic subclones does not provide sufficient evidence to unequivocally establish a history of metastatic cascades. In the absence of a complete phylogeny of the subclones within the primary tumor, a scenario of parallel metastatic events from the primary tumor is an equally plausible interpretation. Future phylogenetic studies on the origin of metastases should obtain a complete phylogeny of subclones within the primary tumor. This complete phylogeny may be obtainable by ultra-deep sequencing and phasing of large sections or by targeted sequencing of many small, spatially heterogeneous sections, followed by phylogenetic reconstruction using well-established molecular evolutionary models. In addition to resolving the evolutionary history of metastases, a complete phylogeny of subclones within the primary tumor facilitates the identification of driver mutations by application of phylogeny-based tests of natural selection.

Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection

Divergence in gene regulation is hypothesized to underlie much of phenotypic evolution, but the role of natural selection in shaping the molecular phenotype of gene expression continues to be debated. To resolve the mode of gene expression, evolution requires accessible theoretical predictions for the effect of selection over long timescales. Evolutionary quantitative genetic models of phenotypic evolution can provide such predictions, yet those predictions depend on the underlying hypotheses about the distributions of mutational and selective effects that are notoriously difficult to disentangle. Here, we draw on diverse genomic data sets including expression profiles of natural genetic variation and mutation accumulation lines, empirical estimates of genomic mutation rates, and inferences of genetic architecture to differentiate contrasting hypotheses for the roles of stabilizing selection and mutation in shaping natural expression variation. Our analysis suggests that gene expression evolves in a domain of phenotype space well fit by the House-of-Cards (HC) model. Although the strength of selection inferred is sensitive to the number of loci controlling gene expression, the model is not. The consistency of these results across evolutionary time from budding yeast through fruit fly implies that this model is general and that mutational effects on gene expression are relatively large. Empirical estimates of the genetic architecture of gene expression traits imply that selection provides modest constraints on gene expression levels for most genes, but that the potential for regulatory evolution is high. Our prediction using data from laboratory environments should encourage the collection of additional data sets allowing for more nuanced parameterizations of HC models for gene expression.

Solving the ecological puzzle of mycorrhizal associations using data from annotated collections and environmental samples - an example of saddle fungi

The relation between ecological and genetic divergence of Helvella species (saddle fungi) has been perplexing. While a few species have been clearly demonstrated to be ectomycorrhizal fungi, ecological roles of many other species have been controversial, alternately considered as either saprotrophic or mycorrhizal. We applied SATé to build an inclusive deoxyribonucleic acid sequence alignment for the internal transcribed spacers (ITS) of annotated Helvella species and related environmental sequences. Phylogenetic informativeness of ITS and its regions were assessed using PhyDesign. Mycorrhizal lineages present a diversity of ecology, host type and geographic distribution. In two Helvella clades, no Helvella ITS sequences were recovered from root tips. Inclusion of environmental sequences in the ITS phylogeny from these sequences has the potential to link these data and reveal Helvella ecology. This study can serve as a model for revealing the diversity of relationships between unculturable fungi and their potential plant hosts. How non-mycorrhizal life styles within Helvella evolved will require expanded metagenomic investigation of soil and other environmental samples along with study of Helvella genomes.

The peopling of the African continent and the diaspora into the new world

Africa is the birthplace of anatomically modern humans, and is the geographic origin of human migration across the globe within the last 100,000 years. The history of African populations has consisted of a number of demographic events that have influenced patterns of genetic and phenotypic variation across the continent. With the increasing amount of genomic data and corresponding developments in computational methods, researchers are able to explore long-standing evolutionary questions, expanding our understanding of human history within and outside of Africa. This review will summarize some of the recent findings regarding African demographic history, including the African Diaspora, and will briefly explore their implications for disease susceptibility in populations of African descent.

Utility of characters evolving at diverse rates of evolution to resolve quartet trees with unequal branch lengths: analytical predictions of long-branch effects

BACKGROUND

The detection and avoidance of "long-branch effects" in phylogenetic inference represents a longstanding challenge for molecular phylogenetic investigations. A consequence of parallelism and convergence, long-branch effects arise in phylogenetic inference when there is unequal molecular divergence among lineages, and they can positively mislead inference based on parsimony especially, but also inference based on maximum likelihood and Bayesian approaches. Long-branch effects have been exhaustively examined by simulation studies that have compared the performance of different inference methods in specific model trees and branch length spaces.

RESULTS

In this paper, by generalizing the phylogenetic signal and noise analysis to quartets with uneven subtending branches, we quantify the utility of molecular characters for resolution of quartet phylogenies via parsimony. Our quantification incorporates contributions toward the correct tree from either signal or homoplasy (i.e. "the right result for either the right reason or the wrong reason"). We also characterize a highly conservative lower bound of utility that incorporates contributions to the correct tree only when they correspond to true, unobscured parsimony-informative sites (i.e. "the right result for the right reason"). We apply the generalized signal and noise analysis to classic quartet phylogenies in which long-branch effects can arise due to unequal rates of evolution or an asymmetrical topology. Application of the analysis leads to identification of branch length conditions in which inference will be inconsistent and reveals insights regarding how to improve sampling of molecular loci and taxa in order to correctly resolve phylogenies in which long-branch effects are hypothesized to exist.

CONCLUSIONS

The generalized signal and noise analysis provides analytical prediction of utility of characters evolving at diverse rates of evolution to resolve quartet phylogenies with unequal branch lengths. The analysis can be applied to identifying characters evolving at appropriate rates to resolve phylogenies in which long-branch effects are hypothesized to occur.

Integrating Community-Based Interventions to Reverse the Convergent TB/HIV Epidemics in Rural South Africa

The WHO recommends integrating interventions to address the devastating TB/HIV co-epidemics in South Africa, yet integration has been poorly implemented and TB/HIV control efforts need strengthening. Identifying infected individuals is particularly difficult in rural settings. We used mathematical modeling to predict the impact of community-based, integrated TB/HIV case finding and additional control strategies on South Africa’s TB/HIV epidemics. We developed a model incorporating TB and HIV transmission to evaluate the effectiveness of integrating TB and HIV interventions in rural South Africa over 10 years. We modeled the impact of a novel screening program that integrates case finding for TB and HIV in the community, comparing it to status quo and recommended TB/HIV control strategies, including GeneXpert, MDR-TB treatment decentralization, improved first-line TB treatment cure rate, isoniazid preventive therapy, and expanded ART. Combining recommended interventions averted 27% of expected TB cases (95% CI 18–40%) 18% HIV (95% CI 13–24%), 60% MDR-TB (95% CI 34–83%), 69% XDR-TB (95% CI 34–90%), and 16% TB/HIV deaths (95% CI 12–29). Supplementing these interventions with annual community-based TB/HIV case finding averted a further 17% of TB cases (44% total; 95% CI 31–56%), 5% HIV (23% total; 95% CI 17–29%), 8% MDR-TB (68% total; 95% CI 40–88%), 4% XDR-TB (73% total; 95% CI 38–91%), and 8% TB/HIV deaths (24% total; 95% CI 16–39%). In addition to increasing screening frequency, we found that improving TB symptom questionnaire sensitivity, second-line TB treatment delays, default before initiating TB treatment or ART, and second-line TB drug efficacy were significantly associated with even greater reductions in TB and HIV cases. TB/HIV epidemics in South Africa were most effectively curtailed by simultaneously implementing interventions that integrated community-based TB/HIV control strategies and targeted drug-resistant TB. Strengthening existing TB and HIV treatment programs is needed to further reduce disease incidence.

Harnessing case isolation and ring vaccination to control Ebola

As a devastating Ebola outbreak in West Africa continues, non-pharmaceutical control measures including contact tracing, quarantine, and case isolation are being implemented. In addition, public health agencies are scaling up efforts to test and deploy candidate vaccines. Given the experimental nature and limited initial supplies of vaccines, a mass vaccination campaign might not be feasible. However, ring vaccination of likely case contacts could provide an effective alternative in distributing the vaccine. To evaluate ring vaccination as a strategy for eliminating Ebola, we developed a pair approximation model of Ebola transmission, parameterized by confirmed incidence data from June 2014 to January 2015 in Liberia and Sierra Leone. Our results suggest that if a combined intervention of case isolation and ring vaccination had been initiated in the early fall of 2014, up to an additional 126 cases in Liberia and 560 cases in Sierra Leone could have been averted beyond case isolation alone. The marginal benefit of ring vaccination is predicted to be greatest in settings where there are more contacts per individual, greater clustering among individuals, when contact tracing has low efficacy or vaccination confers post-exposure protection. In such settings, ring vaccination can avert up to an additional 8% of Ebola cases. Accordingly, ring vaccination is predicted to offer a moderately beneficial supplement to ongoing non-pharmaceutical Ebola control efforts.

H-CLAP: hierarchical clustering within a linear array with an application in genetics

In most cases where clustering of data is desirable, the underlying data distribution to be clustered is unconstrained. However clustering of site types in a discretely structured linear array, as is often desired in studies of linear sequences such as DNA, RNA or proteins, represents a problem where data points are not necessarily exchangeable and are directionally constrained within the array. Each position in the linear array is fixed, and could be either "marked" (i.e., of interest such as polymorphic or substitute sites) or "non-marked." Here we describe a method for clustering of those marked sites. Since the cluster-generating process is constrained by discrete locality inside such an array, traditional clustering methods need adjustment to be appropriate. We develop a hierarchical Bayesian approach. We adopt a Markov clustering algorithm, revealing any natural partitioning in the pattern of marked sites. The resulting recursive partitioning and clustering algorithm is named hierarchical clustering in a linear array (H-CLAP). It employs domain-specific directional constraints directly in the likelihood construction. Our method, being fully Bayesian, is more flexible in cluster discovery compared to a standard agglomerative hierarchical clustering algorithm. It not only provides hierarchical clustering, but also cluster boundaries, which may have their own biological significance. We have tested the efficacy of our method on data sets, including two biological and several simulated ones.