Cryptic diversity in Cladosporium cladosporioides resulting from sequence-based species delimitation analyses

Cladosporium cladosporioides is an extremely widespread fungus involved in associations ranging from mutualistic to pathogenic and is the most frequently represented Cladosporium species in sequence databases, such as Genbank. The taxonomy of Cladosporium species, currently based on the integration of molecular data with morphological and cultural characters, is in frequent need of revision. Hence, the recently developed species delimitation methods can be helpful to explore cryptic diversity in this genus. Considering a previous study that reported several hypothetical species within C. cladosporioides, we tested four methods of species delimitation using the combined DNA barcodes internal transcribed spacers, translation elongation factor 1-α and actin 1. The analyses involved 105 isolates, revealing that currently available sequences of C. cladosporioides in GenBank actually represent more than one species. Moreover, we found that eight isolates from this set should be ascribed to Cladosporium anthropophilum. Our results revealed a certain degree of discordance among species delimitation methods, which can be efficiently treated using conservative approaches in order to minimize the risk of considering false positives

Multispecies Coalescent and its Applications to Infer Species Phylogenies and Cross-Species Gene Flow

Multispecies coalescent (MSC) is the extension of the single-population coalescent model to multiple species. It integrates the phylogenetic process of species divergences and the population genetic process of coalescent, and provides a powerful framework for a number of inference problems using genomic sequence data from multiple species, including estimation of species divergence times and population sizes, estimation of species trees accommodating discordant gene trees, inference of cross-species gene flow and species delimitation. In this review, we introduce the major features of the MSC model, discuss full-likelihood and heuristic methods of species tree estimation and summarize recent methodological advances in inference of cross-species gene flow. We discuss the statistical and computational challenges in the field and research directions where breakthroughs may be likely in the next few years

Untangling the Hypogeococcus pungens species complex (Hemiptera: Pseudococcidae) for Argentina, Australia, and Puerto Rico based on host plant associations and genetic evidence

Hypogeococcus pungens, a mealybug native of southern South America, is devastating native cacti in Puerto Rico and threatening cactus diversity in the Caribbean, and potentially in Central and North America. The taxonomic status of H. pungens is controversial since it has been reported feeding not only on Cactaceae but also on other plant families throughout its distribution range. However, in Australia, where the species had been exported from Argentina to control weedy American cacti, it was never found on host plants other than Cactaceae. These conflicting pieces of evidence not only cast doubt on the species identity that invaded Puerto Rico, but also have a negative impact on the search for natural enemies to be used in biological control programs against this pest. Here we present reproductive incompatibility and phylogenetic evidences that give support to the hypothesis that H. pungens is a species complex in which divergence appears to be driven by the host plants. The nuclear EF1a and 18S and the mitochondrial COI genes were used as markers to evaluate the phylogenetic relationships among H. pungens populations collected in Argentina, Australia and Puerto Rico feeding on Cactaceae and/or Amaranthaceae. Additionally, we conducted reciprocal crosses between mealybugs from both hosts. Species delimitation analysis revealed two well-supported putative species within H. pungens, one including mealybugs feeding on Amaranthaceae (H. pungens sensu stricto), and a new undescribed species using Cactaceae as hosts. Additionally, we found asymmetric reproductive incompatibility between these putative species suggesting recent reproductive isolation. The Bayesian species delimitation also suggested that the Australian mealybug population may PLOS ONE derive from another undescribed species. Overall, the patterns of genetic differentiation may be interpreted as the result of recent speciation events prompted by host plant shifts. Finally, the finding of a single haplotype in the Puerto Rico population suggests only one invasive event. We still need to identify the geographical origin of the pest in order to enable the use of biological control to reduce the threat to cacti diversity in the Caribbean.Fil: Poveda Martínez, Daniel Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina. Universidad del Quindío; Colombia. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Calderón, Pablo Luciano Sebastian. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: de la Colina, María Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Hight, Stephen. United States Department of Agriculture; Estados UnidosFil: Triapitsyn, Serguei V.. University of California; Estados UnidosFil: Diaz Soltero, Hilda. United States Department of Agriculture; Estados UnidosFil: Hasson, Esteban Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentin

Methods and Algorithms for Inference Problems in Population Genetics

Inference of population history is a central problem of population genetics. The advent of large genetic data brings us not only opportunities on developing more accurate methods for inference problems, but also computational challenges. Thus, we aim at developing accurate method and fast algorithm for problems in population genetics. Inference of admixture proportions is a classical statistical problem. We particularly focus on the problem of ancestry inference for ancestors. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of appropriation of an individual\u27s admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. We show that the distribution and lengths of admixture tracts in a genome contain information about the admixture proportions of the ancestors of an individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. To better understand population, we further study the species delimitation problem. It is a problem of determining the boundary between population and species. We propose a classification-based method to assign a set of populations to a number of species. Our new method uses summary statistics generated from genetic data to classify pairwise populations as either \u27same species\u27 or \u27different species\u27. We show that machine learning can be used for species delimitation and scaled for large genomic data. It can also outperform Bayesian approaches, especially when gene flow involves in the evolutionary process

Coalescent-based species delimitation in the sand lizards of the Liolaemus wiegmannii complex (Squamata: Liolaemidae)

Coalescent-based algorithms coupled with the access to genome-wide data have become powerful tools forassessing questions on recent or rapid diversification, as well as delineating species boundaries in the absence of reciprocal monophyly. In southern South America, the diversification of Liolaemus lizards during the Pleistocene is well documented and has been attributed to the climatic changes that characterized this recent period of time. Past climatic changes had harsh effects at extreme latitudes, including Patagonia, but habitat changes at intermediate latitudes of South America have also been recorded, including expansion of sand fields over northern Patagonia and Pampas). In this work, we apply a coalescent-based approach to study the diversification of the Liolaemus wiegmannii species complex, a morphologically conservative clade that inhabits sandy soils across northwest and south-central Argentina, and the south shores of Uruguay. Using four standard sequence markers (mitochondrial DNA and three nuclear loci) along with ddRADseq data we inferred species limits and a time calibrated species tree for the L. wiegmannii complex in order to evaluate the influence of Quaternary sand expansion/retraction cycles on diversification. We also evaluated the evolutionary independence of the recently described L. gardeli and inferred its phylogenetic position relative to L. wiegmannii. We find strong evidence for six allopatric candidate species within L. wiegmannii, which diversified during the Pleistocene. The Great Patagonian Glaciation (∼1 million years before present) likely split the species complex into two main groups: one composed of lineages associated with sub-Andean sedimentary formations, and the other mostly related to sand fields in the Pampas and northern Patagonia. We hypothesize that early speciation within L. wiegmannii was influenced by the expansion of sand dunes throughout central Argentina and Pampas. Finally, L. gardeli is supported as a distinct lineage nested within the L. wiegmannii complex.Fil: Villamil, Joaquín. Universidad de la República. Facultad de Ciencias; UruguayFil: Avila, Luciano Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico para el Estudio de los Ecosistemas Continentales; ArgentinaFil: Morando, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico para el Estudio de los Ecosistemas Continentales; ArgentinaFil: Sites, Jack W.. University Brigham Young; Estados UnidosFil: Leaché, Adam D.. University of Washington; Estados UnidosFil: Maneyro, Raúl. Universidad de la República. Facultad de Ciencias; UruguayFil: Camargo Bentaberry, Arley. Universidad de la República; Urugua

A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data

Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyzes. We show from simulated data as well are real data from the literature that our method estimates parameters accurately and improves alternative approaches in many situations. The interest of this method is exemplified using an intricate case of inter- and intra-species differentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on {\em Myodes} voles from Sweden. A computer program is made available as an extension of the R package Geneland

Cox1 barcoding versus multilocus species delimitation: validation of two mite species with contrasting effective population sizes

Abstract Background The cox1-barcoding approach is currently extensively used for high-throughput species delimitation and discovery. However, this method has several limitations, particularly when organisms have large effective population sizes. Paradoxically, most common, abundant, and widely distributed species may be misclassified by this technique. Results We conducted species delimitation analyses for two host-specific lineages of scab mites of the genus Caparinia, having small population sizes. Cox1 divergence between these lineages was high (7.4–7.8%) while that of nuclear genes was low (0.06–0.53%). This system was contrasted with the medically important American house dust mite, Dermatophagoides farinae, a globally distributed species with very large population size. This species has two distinct, sympatric cox1 lineages with 4.2% divergence. We tested several species delimitation algorithms PTP, GMYC, ABGD, BPP, STACEY and PHRAPL, which inferred different species boundaries for these entities. Notably, STACEY recovered the Caparinia lineages as two species and D. farinae as a single species. BPP agreed with these results when the prior on ancestral effective population sizes was set to expected values, although delimitation of Caparinia was still equivocal. No other cox1 species delimitation algorithms inferred D. farinae as a single species, despite the fact that the nuclear CPW2 gene shows some evidence for introgression between the cox1 groups. This indicates that the cox1-barcoding approach may result in excessive species splitting. Conclusions Our research highlights the importance of using nuclear genes and demographic characteristics to infer species boundaries rather than relying on a single-gene barcoding approach, particularly for putative species having large effective population sizes.https://deepblue.lib.umich.edu/bitstream/2027.42/146770/1/13071_2018_Article_3242.pd

A Unifying Model for the Analysis of Phenotypic, Genetic, and Geographic Data

Recognition of evolutionary units (species, populations) requires integrating several kinds of data, such as genetic or phenotypic markers or spatial information in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyses. We show from simulated data as well as real data that our method estimates parameters accurately and is an improvement over alternative approaches in many situations. The power of this method is exemplified using an intricate case of inter- and intraspecies differentiation based on an original data set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Genelan

Speciation, evolution and phylogeny of some shallow-water octocorals (Cnidaria: Anthozoa)

Shallow-water octocorals are among the most abundant macro-benthic organisms inhabiting tropical subtropical and temperate communities. In spite of being worldwide distributed and highly diverse, the systematics of many octocorals remains controversial and the understanding of the processes who led to their diversification is largely unexplored. This study includes five chapters, each dealing with different aspects of the systematics, phylogeny and evolution of six soft coral genera such as Lobophytum, Sarcophyton, Paramuricea, Leptogorgia, Muricea and Pacifigorgia. One of the main goals of the study was to explore, through the use of molecular methods, the genetic variation within species notoriously difficult to identify. Besides the use of standard molecular methods for phylogenetic reconstruction and species delimitation, the effectiveness of Next Generation Sequencing (NGS) technologies was tested for mitogenomic and genotyping analyses. In the first chapter the use of single-locus markers (e.g. COI, mtMutS and 28S rDNA) was investigated and different automated species delimitation methods (e.g. ABGD, bPTP) were employed to assess species richness among soft coral genera from Western Australia. The methods used appeared suitable for preliminary and rapid diversity assessments especially in the presence of species-rich genera such as Lobophytum and Sarcophyton where morphological identification is particularly difficult and time consuming. In the second chapter, along with the sequencing of complete mitogenomes of Mediterranean Paramuricea species (P. clavata and P. macrospina), the biogeography of the genus was investigated. The results revealed nucleotide and genome size polymorphisms, while the biogeographic predictions suggested that the Mediterranean species have resulted from independent speciation events, explaining in part the high phylogenetic divergence detected. In the third chapter, the sequencing of complete mitogenomes of five Leptogorgia species from different geographic areas (eastern Pacific, eastern Atlantic and Mediterranean) was followed by phylogenetic reconstructions based on an extended mtMutS dataset. The phylogenetic tree recovered Leptogorgia polyphyletic with a clear segregation between the eastern Pacific and eastern Atlantic forms. A time calibrated phylogeny provided insights into the evolution of the genus. In chapter four, using NGS approaches, the complete mitochondrial genome of two eastern Pacific Muricea species (M. crassa and M. purpurea) has been sequenced. The recovery of complete mitogenomes allowed to evaluate the presence of variable and informative regions and to infer a more robust phylogeny. Overall, the results showed high nucleotide diversity in the intergenic spacers, making these regions new potential molecular markers for species-level identifications. In the last chapter a genome-wide Single Nucleotide Polymorphisms (SNPs) and a Bayes Factor Delimitation method were used to infer the genetic relationships within species of the genus Pacifigorgia. The data obtained showed incongruence between molecular and morphological investigations suggesting the possibility of alternative taxonomic assignments for these species. This study provides information on the evolution and speciation of ecologically important soft corals, which distribution range from the littoral and sublittoral zones of the Mediterranean to the tropical and subtropical reefs of Western Australia (WA) and eastern Pacific (EP). The use of mitochondrial markers such as MutS allowed to shed some light on the biogeography and evolutionary history of widespread gorgonians with special emphasis on the Mediterranean endemics and the Atlantic species. Concerning the Western Australia, the obtained results will support the management and conservation of under-investigated marine biodiversity hotspots and potentially species-rich localities such as the Kimberley. In terms of species delimitation, the application of genome-wide SNPs and the use of NGS technologies showed a higher resolution when compared with the traditional methods based on DNA barcoding and single-locus phylogenies. The data generated have been used to clarify the systematics of the species investigated and will be considered as a baseline for future studies on population genetics with a closer look on the adaptive processes