Constraint Trees Research Articles

Phylogenetic relationships in Hypomyces and allied genera, with emphasis on species growing on wood-decaying homobasidiomycetes

To infer phylogenetic relationships among species of Hypomyces (Fr.) Tul and allied genera, partial sequences of the 28S rDNA were obtained for 21 strains representing 19 species. On the basis of these data and 38 sequences obtained from GenBank, phylogenetic analyses were performed using the programs PAUP and Pee-Wee. Hypomyces appears to be paraphyletic, with species having wet-conidial phialidic anamorphs more closely related to other genera. Hypomyces chrysostomus Berk & Broome is a sister group to the clade that includes species of Aphysiostroma Barrasa et al., Arachnocrea Moravec, and Hypocrea Fr. Based on morphological and molecular evidence, a new genus, Sporophagomyces, is described for Hypomyces chrysostomus and two allied species. Hypomyces broomeanus Tul. forms one clade with species of Sphaerostilbella Sacc. and is transferred to this genus. The recognition of Arachnocrea is justified. The integration of Cladobotryum Nees species that are not known to undergo sexual reproduction with Hypomyces species that possess Cladobotryum anamorphs receives strong support, but the whole complex of these species appears to be paraphyletic. However, constraint trees, which require monophyly of all these ana- and pleo-morphic species, do not appear significantly less likely than the other trees obtained under maximum likelihood or parsimony criteria. For the remaining species of Hypomyces, four distinct lineages are distinguished.

Probabilistic Deduction with Conditional Constraints over Basic Events

We study the problem of probabilistic deduction with conditional constraints over basic events. We show that globally complete probabilistic deduction with conditional constraints over basic events is NP-hard. We then concentrate on the special case of probabilistic deduction in conditional constraint trees. We elaborate very efficient techniques for globally complete probabilistic deduction. In detail, for conditional constraint trees with point probabilities, we present a local approach to globally complete probabilistic deduction, which runs in linear time in the size of the conditional constraint trees. For conditional constraint trees with interval probabilities, we show that globally complete probabilistic deduction can be done in a global approach by solving nonlinear programs. We show how these nonlinear programs can be transformed into equivalent linear programs, which are solvable in polynomial time in the size of the conditional constraint trees.

Decay analysis of large sets of phylogenetic data

SummaryMorgan, D. R.: Decay analysis of large sets of phylogenetic data. – Taxon 46: 509‐517. 1997. – ISSN 0040‐0262.Decay analysis provides an alternative, or supplement, to bootstrap analysis for obtaining estimates of the reliability of groups resulting from a phylogenetic analysis. This approach, which consists of examining trees longer than the shortest and noting the tree lengths at which groups of interest are no longer monophyletic, is used increasingly. One serious shortcoming of decay analysis as often implemented is that the number of trees that need to be saved and examined can be much larger than the capacities of hardware and software that have been available. A data matrix was constructed so that all trees up to five steps longer than the shortest could be saved and examined. A series of decay analyses was then conducted with this data set to determine the effects produced in the results when all trees are not found and to evaluate methods that could be used to conduct decay analyses of large data sets. Limiting the number of trees to be saved resulted in overestimates of support for monophyletic groups, a problem that became substantial when only 33% of all trees were examined. Two methods of decay analysis that use constraint trees to save a subset of all trees were evaluated. Decay index values resulting from both methods were identical to those obtained from examination of all trees, indicating that these approaches should be useful in conducting decay analyses of large data sets.

Is Penicillium Monophyletic? An Evaluation of Phylogeny in the Family Trichocomaceae from 18S, 5.8S and ITS Ribosomal DNA Sequence Data

Using ribosomal DNA sequences from 17 fungi, we evaluated the monophylly of Penicillium and the phylogeny in the ascomycete family Trichocomaceae (= Eurotiaceae). We determined the 5.8S and internal transcribed spacer rDNA sequences for 13 species, and the 18S rDNA sequences for Eupenicillium javanicum and Neosartorya fischeri. After including additional published 18S, 5.8S and ITS rDNA sequences, our data set consisted of 2204 aligned sites for 17 taxa and yielded 16 equally parsimonious trees, each requiring 609 nucleotide substitutions. Indicating that Penicillium is not monophyletic, all the trees show Eupenicillium javanicum (with a Penicillium state) grouping with the Aspergillus-producing taxa Neosartorya fischeri and Eurotium rubrum rather than the Penicillium-producing Talaromyces flavus var. macrosporus or Talaromyces bacillisporus. The branch separating Eupenicillium javanicum from Talaromyces flavus and Talaromyces bacillisporus received 98% bootstrap support. Providing further statistical evidence that Penicillium is not monophyletic, constraint trees forcing the penicillia to appear monophyletic were significantly less likely (using the maximum likelihood program DNAML) than trees allowing the penicillia to cluster into two groups. Aspergillus may be monophyletic, nested among species with Paecilomyces and Penicillium states. Monascus purpureus, although usually placed in a separate family, grouped with Eupenicillium and the Aspergillus species in the Trichocomaceae. Species in the Onygenales are basal to the Trichocomaceae. Coding regions varied little in length, were readily alignable and provided most of the evolutionary “signal” present in the data set, while the spacer regions varied in length from 309 to 447 base pairs and encompassed much unalignable data. We found evidence of higher levels of mutational saturation in the internal transcribed spacer regions than in the coding regions when we compared the pair-wise percent substitution, with and without correction for repeated substitutions at the same site, for the two data subsets.

18S rRNA Gene Sequences and Supraordinal Classification of the Erysiphales

The Erysiphales (powdery mildews) exhibit conflicting morphologies and have been classified as either Pyrenomycetes or Plectomycetes. The nuclear small subunit ribosomal RNA gene was sequenced for two isolates of Blumeria graminis forma speciales hordei in order to help resolve this classification controversy. A single most parsimonious tree was obtained grouping the Erysiphales with neither the Plectomycetes nor the Pyrenomycetes, but rather placing the powdery mildews in amongst a basal assemblage of apothecial and pseudothecial fungi. Maximum likelihood tests were conducted on constraint trees exhibiting three possible morphological classifications. The results rejected the placement of the Erysiphales amongst both the Plectomycetes and Pyrenomycetes but could not reject placement amongst the Discomycetes; therefore, the powdery mildews are not Pyrenomycetes nor Plectomycetes. However, higher order classification of the Erysiphales remains unresolved, since there is no strong bootstrap support for the Erysiphales amongst the basal assemblage of apothecial and pseudothecial fungi.

面拘束関係によるＣＳＧ形状自動修正法

This paper presents an automatic shape modification method using surface constraints on CSG (constructive solid geometry). In this method, surface constraints are classified into two categories : explicit constraints which belong to spatial relations between CSG primitives and implicit constraints which belong to individual geometric characteristics of each primitive class. The geometric database is composed of two kinds of trees, i. e. a CSG tree and a set of trees representing the explicit surface constraints. The CSG tree and the constraint trees are linked to each other. The shape modification is performed automatically by tracing the trees. A prototyping has proved the algorithm is easy to handle and efficient to execute.