The Field Museum of Natural History, 1400 S. Lake Shore Dr

a b s t r a c t The toucan genus Ramphastos (Piciformes: Ramphastidae) has been a model in the formulation of Neotropical paleobiogeographic hypotheses

Population Structure and Genetic Diversity among Isolates of Coccidioides posadasii in Venezuela and Surrounding Regions

Coccidioides posadasii is a pathogenic fungus that causes coccidioidomycosis in many arid regions of the Americas. One of these regions is bordered by the Caribbean Sea, and the surrounding landscape may play an important role in the dispersion of C. posadasii across South America through southeastern Mexico, Honduras, Guatemala, and Venezuela. Comparative phylogenomic analyses of C. posadasii reveal that clinical strains from Venezuela are genetically distinct from the North American populations found in (i) Arizona and (ii) Texas, Mexico, and the rest of South America (TX/MX/SA). We find evidence for admixture between the Venezuela and the North American populations of C. posadasii in Central America. Additionally, the proportion of Venezuelan alleles in the admixed population decreases as latitude (and distance from Venezuela) increases. Our results indicate that the population in Venezuela may have been subjected to a recent bottleneck and shows a strong population structure. This analysis provides insight into potential for Coccidioides spp. to invade new regions.IMPORTANCE Valley Fever is a fungal disease caused by two species of fungi: Coccidioides immitis and C. posadasii These fungi are found throughout the arid regions of North and South America; however, our understanding of genetic diversity and disease in South America is limited. In this report, we analyze 10 new genomes of Coccidioides posadasii from regions bordering the Caribbean Sea. We show that these populations are distinct and that isolates from Venezuela are likely a result of a recent bottleneck. These data point to patterns that might be observed when investigating recently established populations.NIH/NIAIDUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Allergy & Infectious Diseases (NIAID) [R21AI28536]; NIH/NIGMSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [R01GM121750]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Temporal and spatial diversification of Pteroglossus aracaris (Aves: Ramphastidae) in the Neotropics: constant rate of diversification does not support an increase in radiation during the Pleistocene. Molecular Phylogenetics and Evolution

a b s t r a c t We use the small-bodied toucan genus Pteroglossus to test hypotheses about diversification in the lowland Neotropics. We sequenced three mitochondrial genes and one nuclear intron from all Pteroglossus species and used these data to reconstruct phylogenetic trees based on maximum parsimony, maximum likelihood, and Bayesian analyses. These phylogenetic trees were used to make inferences regarding both the pattern and timing of diversification for the group. We used the uplift of the Talamanca highlands of Costa Rica and western Panama as a geologic calibration for estimating divergence times on the Pteroglossus tree and compared these results with a standard molecular clock calibration. Then, we used likelihood methods to model the rate of diversification. Based on our analyses, the onset of the Pteroglossus radiation predates the Pleistocene, which has been predicted to have played a pivotal role in diversification in the Amazon rainforest biota. We found a constant rate of diversification in Pteroglossus evolutionary history, and thus no support that events during the Pleistocene caused an increase in diversification. We compare our data to other avian phylogenies to better understand major biogeographic events in the Neotropics. These comparisons support recurring forest connections between the Amazonian and Atlantic forests, and the splitting of cis/trans Andean species after the final uplift of the Andes. At the subspecies level, there is evidence for reciprocal monophyly and groups are often separated by major rivers, demonstrating the important role of rivers in causing or maintaining divergence. Because some of the results presented here conflict with current taxonomy of Pteroglossus, new taxonomic arrangements are suggested

Worldwide phylogenetic distributions and population dynamics of the genus Histoplasma

Submitted by Janaína Nascimento ([email protected]) on 2019-02-21T12:48:43Z No. of bitstreams: 1 ve_Teixeira_Marcus_etal_INI_2016.pdf: 1289612 bytes, checksum: 9bdff083b5ed242adea0746751b2b957 (MD5)Approved for entry into archive by Janaína Nascimento ([email protected]) on 2019-02-21T14:12:04Z (GMT) No. of bitstreams: 1 ve_Teixeira_Marcus_etal_INI_2016.pdf: 1289612 bytes, checksum: 9bdff083b5ed242adea0746751b2b957 (MD5)Made available in DSpace on 2019-02-21T14:12:04Z (GMT). No. of bitstreams: 1 ve_Teixeira_Marcus_etal_INI_2016.pdf: 1289612 bytes, checksum: 9bdff083b5ed242adea0746751b2b957 (MD5) Previous issue date: 2016Translational Genomics Research Institute-North. Division of Pathogen Genomics. Flagstaff, AZ, USA / University of Brasília. Department of Cell Biology. Brasilia, DF, Brazil.University of São Paulo. Department of Biochemistry. São Paulo, SP, Brazil.National Autonomous University of Mexico. Department of Microbiology and Parasitology. Mexico City, Mexico.Corporación para Investigaciones Biológicas. Medellín, Colombia.Federal University of Rio Grande do Norte. Institute of Tropical Medicine. Department of Cell Biology and Genetics. Natal, BrazilCBS-KNAW Fungal Biodiversity Centre. Utrecht, Netherlands.Translational Genomics Research Institute-North. Division of Pathogen Genomics. Flagstaff, AZ, USA.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Micologia. Rio de Janeiro, Brasil.University of Brasília. Department of Cell Biology. Brasilia, DF, Brazil.Translational Genomics Research Institute-North. Division of Pathogen Genomics. Flagstaff, AZ, USA.Background: Histoplasma capsulatum comprises a worldwide complex of saprobiotic fungi mainly found in nitrogen/phosphate (often bird guano) enriched soils. The microconidia of Histoplasma species may be inhaled by mammalian hosts, and is followed by a rapid conversion to yeast that can persist in host tissues causing histoplasmosis, a deep pulmonary/systemic mycosis. Histoplasma capsulatum sensu lato is a complex of at least eight clades geographically distributed as follows: Australia, Netherlands, Eurasia, North American classes 1 and 2 (NAm 1 and NAm 2), Latin American groups A and B (LAm A and LAm B) and Africa. With the exception of the Eurasian cluster, those clades are considered phylogenetic species. Methodology/Principal Findings: Increased Histoplasma sampling (n = 234) resulted in the revision of the phylogenetic distribution and population structure using 1,563 aligned nucleotides from four protein-coding regions. The LAm B clade appears to be divided into at least two highly supported clades, which are geographically restricted to either Colombia/Argentina or Brazil respectively. Moreover, a complex population genetic structure was identified within LAm A clade supporting multiple monophylogenetic species, which could be driven by rapid host or environmental adaptation (~0.5 MYA). We found two divergent clades, which include Latin American isolates (newly named as LAm A1 and LAm A2), harboring a cryptic cluster in association with bats. Conclusions/Significance: At least six new phylogenetic species are proposed in the Histoplasma species complex supported by different phylogenetic and population genetics methods, comprising LAm A1, LAm A2, LAm B1, LAm B2, RJ and BAC-1 phylogenetic species. The genetic isolation of Histoplasma could be a result of differential dispersion potential of naturally infected bats and other mammals. In addition, the present study guides isolate selection for future population genomics and genome wide association studies in this important pathogen complex

Population structure of <i>Histoplasma capsulatum</i> deduced by Bayesian Analysis of Population Structure (BAPS).

<p>A) Structure plots of 205 isolates revealing 6 different major populations (Clusters 1–6). Phylogenetic species were assigned to each of the six deduced populations as follows: Cluster 1 representing the phylogenetic species NAm 1, Cluster 2 representing the phylogenetic species RJ, Cluster 3 containing LAm B, Cluster 4 constituted by phylogenetic species NAm 2, Cluster 5 constituted by LAm A1, LAm A2, BR1-4, and the paraphyletic low supported clades Eurasia, Unknown 1 and Unknown 2 and Cluster 6 containing Netherlands, Panama, Africa, Australia and BAC1. B) Bayesian population tree based on substructures of the 6 initial clusters deduced by BAPS. Gene flow is represented by mixture isolates that are annotated with brackets along the tree.</p

Maximum Likelihood (ML) tree of <i>Histoplasma capsulatum</i> generated by IQ-TREE software for 232 taxa through 4 different loci (<i>arf</i>, <i>ole1</i>, <i>tub</i> and <i>anti-H</i> loci) reveals at least monophyletic braches as following: NAm 1, NAm 2, RJ, LAm B, NAm LAm A1, LAm A2, BR1-4, and Cluster 6 containing Netherlands, Panama, Africa, Australia and BAC1.

<p>Dual branch support, inferred by non-parametric bootstrap for ML analysis, combined with posterior probabilities obtained for the BI analysis, was added to the branches. Monophyletic branches that were supported by two methods (Bootstrap≥70/Posterior Probabilities≥0.95) were designated high confidence clades. We also identified possible in-group variation that may be associated with specific niches. Low supported clades such as Eurasia, Unknown 1 and Unknown 2 were detected but do not follow our monophyletic branches supporting criteria.</p

Extended Bayesian Skyline Plot (EBSP) of <i>Histoplasma capsulatum sensu lato</i>.

<p>EBSPs represents population size changes over time and divergence dating was inferred using BEAST v1.8.2 based on conservative intervals of nucleotide substitutions rates and dates (0.00043–0.00656 subst/site/lineage/My; 0.0–15 Ma) that encompass values obtained by Kasuga et al. [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0004732#pntd.0004732.ref040" target="_blank">40</a>]. Y-axes are effective population size divided by generation time. X-axes are in millions of years. Confidence intervals of each dated phylogenetic species were added to the nodes.</p

Data from: Best practices for justifying fossil calibrations

Our ability to correlate biological evolution with climate change, geological evolution, and other historical patterns is essential to understanding the processes that shape biodiversity. Combining data from the fossil record with molecular phylogenetics represents an exciting synthetic approach to this challenge. The first molecular divergence dating analysis (Zuckerkandl and Pauling 1962) was based on a measure of the amino acid differences in the hemoglobin molecule; with replacement rates established (calibrated) using inaccurate paleontological age estimates from textbooks (e.g., Dodson 1955). Since that time, the amount of molecular sequence data has increased dramatically, affording ever-greater opportunities to apply molecular divergence approaches to fundamental problems in evolutionary biology. To capitalize on these opportunities, increasingly sophisticated divergence dating methods have been, and continue to be, developed. In contrast, comparatively little attention has been devoted to critically assessing the paleontological and associated geological data used in divergence dating analyses. The lack of rigorous protocols for assigning calibrations based on fossils raises serious questions about the credibility of divergence dating results (Shaul and Graur 2002; Brochu et al. 2004; Graur and Martin 2004; Hedges and Kumar 2004; Reisz and Muller 2004a,b; Theodor, 2004; van Tuinen and Hadly 2004a,b; van Tuinen et al. 2004; Benton and Donoghue 2007; Donoghue and Benton 2007; Parham and Irmis 2008; Ksepka 2009; Benton et al. 2009; Heads 2011). The assertion that incorrect calibrations will negatively influence divergence-dating studies is not controversial. Attempts to identify incorrect calibrations through the use of a posteriori methods are available (e.g., Near and Sanderson 2004; Near et al. 2005; Rutschman et al. 2007; Marshall 2008; Pyron 2010; Dornburg et al. 2011). These methods avoid the need for molecular systematists to interpret the unfamiliar and often obscure literature of paleontology, stratigraphy, and geochronology. Most a posteriori methods assess the consistency among calibrations on different nodes and reject inconsistent calibrations. However, consistency among fossil calibrations (or lack thereof) may be the consequence of temporal or geographical biases in the rock record. For example, all dates could be equally underestimated because of missing rock units or missing fossils in a particular time interval. In these instances, cross validation could lead to the rejection of calibrations that provide a better approximation of divergence times (Marshall 2008; Benton et al. 2009; Lee et al. 2009). We do not deny that a posteriori methods are a useful means of evaluating calibrations, but there can be no substitute for a priori assessment of the veracity of paleontological data

Data from: Best practices for justifying fossil calibrations

Our ability to correlate biological evolution with climate change, geological evolution, and other historical patterns is essential to understanding the processes that shape biodiversity. Combining data from the fossil record with molecular phylogenetics represents an exciting synthetic approach to this challenge. The first molecular divergence dating analysis (Zuckerkandl and Pauling 1962) was based on a measure of the amino acid differences in the hemoglobin molecule; with replacement rates established (calibrated) using inaccurate paleontological age estimates from textbooks (e.g., Dodson 1955). Since that time, the amount of molecular sequence data has increased dramatically, affording ever-greater opportunities to apply molecular divergence approaches to fundamental problems in evolutionary biology. To capitalize on these opportunities, increasingly sophisticated divergence dating methods have been, and continue to be, developed. In contrast, comparatively little attention has been devoted to critically assessing the paleontological and associated geological data used in divergence dating analyses. The lack of rigorous protocols for assigning calibrations based on fossils raises serious questions about the credibility of divergence dating results (Shaul and Graur 2002; Brochu et al. 2004; Graur and Martin 2004; Hedges and Kumar 2004; Reisz and Muller 2004a,b; Theodor, 2004; van Tuinen and Hadly 2004a,b; van Tuinen et al. 2004; Benton and Donoghue 2007; Donoghue and Benton 2007; Parham and Irmis 2008; Ksepka 2009; Benton et al. 2009; Heads 2011). The assertion that incorrect calibrations will negatively influence divergence-dating studies is not controversial. Attempts to identify incorrect calibrations through the use of a posteriori methods are available (e.g., Near and Sanderson 2004; Near et al. 2005; Rutschman et al. 2007; Marshall 2008; Pyron 2010; Dornburg et al. 2011). These methods avoid the need for molecular systematists to interpret the unfamiliar and often obscure literature of paleontology, stratigraphy, and geochronology. Most a posteriori methods assess the consistency among calibrations on different nodes and reject inconsistent calibrations. However, consistency among fossil calibrations (or lack thereof) may be the consequence of temporal or geographical biases in the rock record. For example, all dates could be equally underestimated because of missing rock units or missing fossils in a particular time interval. In these instances, cross validation could lead to the rejection of calibrations that provide a better approximation of divergence times (Marshall 2008; Benton et al. 2009; Lee et al. 2009). We do not deny that a posteriori methods are a useful means of evaluating calibrations, but there can be no substitute for a priori assessment of the veracity of paleontological data