Towards resolving the complete fern tree of life

In the past two decades, molecular systematic studies have revolutionized our understanding of the evolutionary history of ferns. The availability of large molecular data sets together with efficient computer algorithms, now enables us to reconstruct evolutionary histories with previously unseen completeness. Here, the most comprehensive fern phylogeny to date, representing over one-fifth of the extant global fern diversity, is inferred based on four plastid genes. Parsimony and maximum-likelihood analyses provided a mostly congruent results and in general supported the prevailing view on the higher-level fern systematics. At a deep phylogenetic level, the position of horsetails depended on the optimality criteria chosen, with horsetails positioned as the sister group either of Marattiopsida-Polypodiopsida clade or of the Polypodiopsida. The analyses demonstrate the power of using a 'supermatrix' approach to resolve large-scale phylogenies and reveal questionable taxonomies. These results provide a valuable background for future research on fern systematics, ecology, biogeography and other evolutionary studies.     

Phylogenetic signal in nucleotide data from seed plants: implications for resolving the seed plant tree of life

Effects of taxonomic sampling and conflicting signal on the inference of seed plant trees supported in previous molecular analyses were explored using 13 single-locus data sets. Changing the number of taxa in single-locus analyses had limited effects on log likelihood differences between the gnepine (Gnetales plus Pinaceae) and gnetifer (Gnetales plus conifers) trees. Distinguishing among these trees also was little affected by the use of different substitution parameters. The 13-locus combined data set was partitioned into nine classes based on substitution rates. Sites evolving at intermediate rates had the best likelihood and parsimony scores on gnepine trees, and those evolving at the fastest rates had the best parsimony scores on Gnetales-sister trees (Gnetales plus other seed plants). When the fastest evolving sites were excluded from parsimony analyses, well-supported gnepine trees were inferred from the combined data and from each genomic partition. When all sites were included, Gnetales-sister trees were inferred from the combined data, whereas a different tree was inferred from each genomic partition. Maximum likelihood trees from the combined data and from each genomic partition were well-supported gnepine trees. A preliminary stratigraphic test highlights the poor fit of Gnetales-sister trees to the fossil data.     

Phylogenomic analysis identifies red algal genes of endosymbiotic origin in the chromalveolates

Endosymbiosis has spread photosynthesis to many branches of the eukaryotic tree; however, the history of photosynthetic organelle (plastid) gain and loss remains controversial. Fortuitously, endosymbiosis may leave a genomic footprint through the transfer of endosymbiont genes to the "host" nucleus (endosymbiotic gene transfer, EGT). EGT can be detected through comparison of host genomes to uncover the history of past plastid acquisitions. Here we focus on a lineage of chlorophyll c-containing algae and protists ("chromalveolates") that are postulated to share a common red algal secondary endosymbiont. This plastid is originally of cyanobacterial origin through primary endosymbiosis and is closely related among the Plantae (i.e., red, green, and glaucophyte algae). To test these ideas, an automated phylogenomics pipeline was used with a novel unigene data set of 5,081 expressed sequence tags (ESTs) from the haptophyte alga Emiliania huxleyi and genome or EST data from other chromalveolates, red algae, plants, animals, fungi, and bacteria. We focused on nuclear-encoded proteins that are targeted to the plastid to express their function because this group of genes is expected to have phylogenies that are relatively easy to interpret. A total of 708 genes were identified in E. huxleyi that had a significant Blast hit to at least one other taxon in our data set. Forty-six of the alignments that were derived from the 708 genes contained at least one other chromalveolate (i.e., besides E. huxleyi), red and/or green algae (or land plants), and one or more cyanobacteria, whereas 15 alignments contained E. huxleyi, one or more other chromalveolates, and only cyanobacteria. Detailed phylogenetic analyses of these data sets turned up 19 cases of EGT that did not contain significant paralogy and had strong bootstrap support at the internal nodes, allowing us to confidently identify the source of the plastid-targeted gene in E. huxleyi. A total of 17 genes originated from the red algal lineage, whereas 2 genes were of green algal origin. Our data demonstrate the existence of multiple red algal genes that are shared among different chromalveolates, suggesting that at least a subset of this group may share a common origin.     

Data requirements and data sources for biodiversity priority area selection

The data needed to prioritize areas for biodiversity protection are records of biodiversity features — species, species assemblages, environmental classes — for each candidate area. Prioritizing areas means comparing candidate areas, so the data used to make such comparisons should be comparable in quality and quantity. Potential sources of suitable data include museums, herbariums and natural resource management agencies. Issues of data precision, accuracy and sampling bias in data sets from such sources are discussed and methods for treating data to minimize bias are reviewed.     

Assessing red algal supraordinal diversity and taxonomy in the context of contemporary systematic data

The wondrously diverse eukaryotes that constitute the red algae have been the focus of numerous recent molecular surveys and remain a rich source of undescribed and little known species for the traditional taxonomist. Molecular studies place the red algae in the kingdom Plantae; however, supraordinal classification has been largely confined to debate on subclass vs. class level status for the two recognized subgroups, one of which is widely acknowledged as paraphyletic. This narrow focus has generally masked the extent to which red algal classification needs modification. We provide a comprehensive review of the literature pertaining to the antiquity, diversity, and systematics of the red algae and propose a contemporary classification based on recent and traditional evidence.     

The small-world dynamics of tree networks and data mining in phyloinformatics

MOTIVATION: A noble and ultimate objective of phyloinformatic research is to assemble, synthesize, and explore the evolutionary history of life on earth. Data mining methods for performing these tasks are not yet well developed, but one avenue of research suggests that network connectivity dynamics will play an important role in future methods. Analysis of disordered networks, such as small-world networks, has applications as diverse as disease propagation, collaborative networks, and power grids. Here we apply similar analyses to networks of phylogenetic trees in order to understand how synthetic information can emerge from a database of phylogenies. RESULTS: Analyses of tree network connectivity in TreeBASE show that a collection of phylogenetic trees behaves as a small-world network-while on the one hand the trees are clustered, like a non-random lattice, on the other hand they have short characteristic path lengths, like a random graph. Tree connectivities follow a dual-scale power-law distribution (first power-law exponent approximately 1.87; second approximately 4.82). This unusual pattern is due, in part, to the presence of alternative tree topologies that enter the database with each published study. As expected, small collections of trees decrease connectivity as new trees are added, while large collections of trees increase connectivity. However, the inflection point is surprisingly low: after about 600 trees the network suddenly jumps to a higher level of coherence. More stringent definitions of 'neighbour' greatly delay the threshold whence a database achieves sufficient maturity for a coherent network to emerge. However, more stringent definitions of 'neighbour' would also likely show improved focus in data mining. AVAILABILITY: http://treebase.org     

Large scale data mining approach for gene-specific standardization of microarray gene expression data

MOTIVATION: The identification of the change of gene expression in multifactorial diseases, such as breast cancer is a major goal of DNA microarray experiments. Here we present a new data mining strategy to better analyze the marginal difference in gene expression between microarray samples. The idea is based on the notion that the consideration of gene's behavior in a wide variety of experiments can improve the statistical reliability on identifying genes with moderate changes between samples. RESULTS: The availability of a large collection of array samples sharing the same platform in public databases, such as NCBI GEO, enabled us to re-standardize the expression intensity of a gene using its mean and variation in the wide variety of experimental conditions. This approach was evaluated via the re-identification of breast cancer-specific gene expression. It successfully prioritized several genes associated with breast tumor, for which the expression difference between normal and breast cancer cells was marginal and thus would have been difficult to recognize using conventional analysis methods. Maximizing the utility of microarray data in the public database, it provides a valuable tool particularly for the identification of previously unrecognized disease-related genes. AVAILABILITY: A user friendly web-interface (http://compbio.sookmyung.ac.kr/~lage/) was constructed to provide the present large-scale approach for the analysis of GEO microarray data (GS-LAGE server).     

The structure and formation of host-parasite pit connections between the red algal alloparasiteHarveyella mirabilis and its red algal hostOdonthalia floccosa

Summary Harveyella mirabilis is a colourless red algal alloparasite which grows on and within its photosynthetic hostOdonthalia floccosa. Cells ofHarveyella establish secondary pit connections (PCs) with other parasite cells and with cells of the host. Small, uninucleate conjunctor cells are produced by parasite cells and remain connected to them by PCs. Conjunctor cells may fuse with either an adjacent host or parasite cell, with the parasite-conjunctor cell PC becoming either a host-parasite or parasite-parasite secondary PC. Occasionally the conjunctor cell does not fuse with an adjacent cell (either host or parasite) and degenerates. The secondary pit plug which forms between a parasite cell and its conjunctor cell always develops with two structurally distinct surfaces characteristic of a host-parasite pit plug. Only if the conjunctor cell fuses with another parasite cell will the structure of the pit plug be altered to that of a parasite-parasite pit plug. Fungal hyphae also invade the region of infection, andHarveyella cells respond by producing nonfunctional conjunctor cells that grow towards adjacent hyphae. Evidence suggests that secondary PCs may be induced to form mechanically, by the physical presence of another cell, rather than in direct response to a message received from an adjacent cell. The mechanism of secondary PC formation described here is similar to that reported for the closely related alloparasiteHolmsella and may be common to a number of red algal parasitic associations. Helen Margaret Quirk, B. Sc. (Hons), M. Sc. (1953–1982), student, research assistant and friend, died after a long illness on October 24, 1982.     

Variation in population structure and dynamics of montane forest tree species in Ethiopia guide priorities for conservation and research

The greatest extent of Afromontane environments in the world is found in Ethiopia. These areas support exceptional biodiversity, but forest cover and ecological integrity have declined sharply in recent decades. Conservation and management efforts are hampered in part by an inadequate understanding of the basic ecology of major tree species. We investigated population structure and inferred population dynamics from size frequency distributions of 22 forest tree species encountered in montane forests of Ethiopia. We collected new empirical data from four sites in the Bale Mountains, where some of the country's most extensive and least disturbed forests remain, and conducted a systematic review and analysis of all such studies that reported population structure for one or more of these species in Ethiopia. Thirteen widespread montane tree species showed a reverse‐J size distribution, indicating a relatively stable population structure. Six other species had size‐frequency distributions that indicate episodic recruitment and/or removal of certain size classes. Specific causes of these patterns are uncertain: they may involve timber harvesting, herbivory, fire, or natural disturbances, but patterns were inconsistent and locality dependent. For three other tree species, existing data are inadequate for any interpretation of population structure and dynamics. A species of particular conservation concern that emerged from this analysis was Hagenia abyssinica, which was found in all areas to consist only of larger individuals with no recent recruitment. For management and conservation purposes, the species in most urgent need of new research are those with inadequate or inconsistent data, and H. abyssinica.     

The fine structure of secondary pit connection formation between the red algal alloparasiteHolmsella australis and its red algal hostGracilaria furcellata

Summary Pit connections (PCs) develop between the parasitic red algaHolmsella and its hostGracilaria. Only parasite cells initiate the formation of host-parasite pit connections. The parasite produces a small connecting cell (termed the conjunctor cell) which moves through the cell wall to fuse with either an adjacent host or parasite cell. The parasite secondary PC, which forms between the conjunctor cell and the parasite cell, is structurally different from a parasite primary PC, and has the distinct structure of a host-parasite PC. Only if the conjunctor cell fuses with another parasite cell will the former parasite-conjunctor cell PC be altered to a typical parasite-parasite PC. If the conjunctor cell fuses with an adjacent host cell the PC continues to develop as host-parasite. Occasionally a conjunctor cell fails to fuse with an adjacent cell (whether host or parasite), and the conjunctor cell and PC eventually breakdown in the cell wall. The parasite overcomes several barriers in order to infect the host, including the formation of host-parasite PCs which appear to be a necessary component of the parasiticHolmsella-Gracilaria association.     

Toward resolving the eukaryotic tree: the phylogenetic positions of jakobids and cercozoans

Resolving the global phylogeny of eukaryotes has proven to be challenging. Among the eukaryotic groups of uncertain phylogenetic position are jakobids, a group of bacterivorous flagellates that possess the most bacteria-like mitochondrial genomes known. Jakobids share several ultrastructural features with malawimonads and an assemblage of anaerobic protists (e.g., diplomonads and oxymonads). These lineages together with Euglenozoa and Heterolobosea have collectively been designated "excavates". However, published molecular phylogenies based on the sequences of nuclear rRNAs and up to six nucleus-encoded proteins do not provide convincing support for the monophyly of excavates, nor do they uncover their relationship to other major eukaryotic groups. Here, we report the first large-scale eukaryotic phylogeny, inferred from 143 nucleus-encoded proteins comprising 31,604 amino acid positions, that includes jakobids, malawimonads and cercozoans. We obtain compelling support for the monophyly of jakobids, Euglenozoa plus Heterolobosea (JEH group), and for the association of cercozoans with stramenopiles plus alveolates. Furthermore, we observe a sister-group relationship between the JEH group and malawimonads after removing fast-evolving species from the dataset. We discuss the implications of these results for the concept of "excavates" and for the elucidation of eukaryotic phylogeny in general.     

An experimental approach to study the biosynthesis of brominated metabolites by the red algal genus Laurencia

The production of labeled brominated metabolites with radioactive ⁸²Br in Laurencia species was investigated as part of a study of the biosynthesis of halogenated metabolites from species belonging to the red algal genus Laurencia (Rhodomelaceae, Ceramiales). Radiobromide [⁸²Br], thin-layer chromatography (TLC), and TLC–autoradioluminography (ARLG) were used. When cultured in artificial seawater medium (ASP₁₂NTA including Na⁸²Br) under 16:8 h light:dark (LD) illumination cycles for 24 h, each of the strains of Laurencia, Laurencia japonensis Abe et Masuda, Laurencia nipponica Yamada (laurencin-producing race and laureatin-producing race), and Laurencia okamurae Yamada, produced species- (or race-) specific ⁸²Br-containing metabolites. In the case of the laurencin-producing race of L. nipponica, laurencin and deacetyllaurencin were found to be produced in approximately 1:1 ratio, though laurencin is the major metabolite in the wild sample. Furthermore, when cultured in the dark, the production rates of brominated metabolites in Laurencia spp. were found to be diminished. The present study strongly indicates that the use of radiobromine [⁸²Br] in combination with the TLC–ARLG method is an effective approach for investigating the biosynthesis of brominated metabolites in Laurencia.     

Data Processing System (DPS) software with experimental design,statistical analysis and data mining developed for use in entomological research

Abstract A comprehensive but simple‐to‐use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology.     

A combined approach to data mining of textual and structured data to identify cancer-related targets

Background  

We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez), and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis) was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas.     

Data mining the protein data bank: automatic detection and assignment of carbohydrate structures

Knowledge of the 3D structure of glycans is a prerequisite for a complete understanding of the biological processes glycoproteins are involved in. However, due to a lack of standardised nomenclature, carbohydrate compounds are difficult to locate within the Protein Data Bank (PDB). Using an algorithm that detects carbohydrate structures only requiring element types and atom coordinates, we were able to detect 1663 entries containing a total of 5647 carbohydrate chains. The majority of chains are found to be N-glycosidically bound. Noncovalently bound ligands are also frequent, while O-glycans form a minority. About 30% of all carbohydrate containing PDB entries comprise one or several errors. The automatic assignment of carbohydrate structures in PDB entries will improve the cross-linking of glycobiology resources with genomic and proteomic data collections, which will be an important issue of the upcoming glycomics projects. By aiding in detection of erroneous annotations and structures, the algorithm might also help to increase database quality.