The trilobite family Nileidae: morphology and classification

Species of genera currently referred to Nileidae are reviewed, and those of Hemibarrandia , Lakaspis , Peraspis and Symphysurina are excluded from the family. Nileidae are united in having a distinctive form of the hypostome, the glabellar organ, in the shallowness or absence of external furrows on the axial and pleural regions, and in the development of strong ventral ridges on the axial region. It is contended that the glabellar organ of nileids and illaenids may not be homologous with the glabellar tubercle of asaphids, that the median ventral suture is not exclusively a character of Asaphina, and doubt is cast on the identification of an asaphoid protaspis as being that of Nileus . These arguments provide a case for allying Nileidae with the Illaenidae, rather than with the Asaphina.     

Genome-wide comparative gene family classification

Correct classification of genes into gene families is important for understanding gene function and evolution. Although gene families of many species have been resolved both computationally and experimentally with high accuracy, gene family classification in most newly sequenced genomes has not been done with the same high standard. This project has been designed to develop a strategy to effectively and accurately classify gene families across genomes. We first examine and compare the performance of computer programs developed for automated gene family classification. We demonstrate that some programs, including the hierarchical average-linkage clustering algorithm MC-UPGMA and the popular Markov clustering algorithm TRIBE-MCL, can reconstruct manual curation of gene families accurately. However, their performance is highly sensitive to parameter setting, i.e. different gene families require different program parameters for correct resolution. To circumvent the problem of parameterization, we have developed a comparative strategy for gene family classification. This strategy takes advantage of existing curated gene families of reference species to find suitable parameters for classifying genes in related genomes. To demonstrate the effectiveness of this novel strategy, we use TRIBE-MCL to classify chemosensory and ABC transporter gene families in C. elegans and its four sister species. We conclude that fully automated programs can establish biologically accurate gene families if parameterized accordingly. Comparative gene family classification finds optimal parameters automatically, thus allowing rapid insights into gene families of newly sequenced species.     

A new classification scheme for the family Araliaceae

The present paper deals with the following three aspects: 1. It attempts to discuss the problems on primitive forms of the family Araliaceae. The genus Tupidanthus Hook. f. & Thoms. was considered by H. Harms (1894) and H. L. Li (1942) as primitive, whilst another genus Plerandra A. Gray was regarded as primitive by R. H. Eyde & C. C. Tseng in 1971. Having made a detailed comparison of the taxonomical characters of these two genera, the present authors believe that both genera are not the most primitive in the Araliaceae. Their affinit yis not close enough and they possibly evolved in parallel lines from a common ancestor which is so far unknown yet. 2. By studying the systems of the past, the present authors believe that none of them is entirely satisfactory. Bentham (1867) recognized five ‘series’ (in fact, equivalent to ‘tribe’ with the ending-eae of names) based on the petaline arrangement in the bud, the numbers of stamen and the types of endospem. This is a plausible fundamental treatment for the Araliaceae, but choosing the endosperm as a criteria in dividing tribe is artifical. As we know today, both ruminate and uniform endosperm are usually presente in the same genus. Seemann’s system (1868) divided the Hederaceae (excl. Trib. Aralieae) into five tribes, in addition to the locules of ovary. The criteria are essentially the same as Bentham’s. The system of Hams (1894) divided the family into three tribes. Two tribes, Aralieae and Mackinlayeae, of Bentham are retained, but other groups were combined in the Trib. Schefflereae. However, Harms did not retain one of those three oldest legitimate names which had named by Bentham, that is contrary to the law of priority in the International Code of Botanical Nomenelature. Hutchinson (1967) adopted seven tribes for the family. The criteria essentially follow those of Bentham, but the inflorescence is overstressed. The inflorescence is an artifical taxonomical character in dividing tribes, because of some dioecious plants, such as Meryta sinclairii (Hook. f.) Seem., have two types of inflorescence in male and female plants. According to Hutchinson’s arrangement, the male and female plants would be put in separate tribes. 3. The present authors are of the opinion that in the study of a natural classification of plant groups emphasis should be laid not only on the characters of the reproductive organs, but on those of vegetative organs as well. The present revised system is based principally upon the characters of both flowers and leaves of the five tribes as follows: Trib. 1. Plerandreae Benth. emend. Hoo & Tseng Trib. 2. Tetraplasandreae Hoo & Tseng Trib. 3. Mackinlayeae Benth. Trib. 4. Aralieae Benth. Trib. 5. Panaceae Benth. emend. Hoo & Tseng     

Phylogenetics and classification of the pantropical fern family Lindsaeaceae

The classification and generic definition in the tropical–subtropical fern family Lindsaeaceae have been uncertain and have so far been based on morphological characters only. We have now studied the evolutionary history of the Lindsaeaceae by simultaneously optimizing 55 morphological characters, two plastid genes (rpoC1 and rps4) and three non‐coding plastid intergenic spacers (trnL‐F, rps4‐trnS and trnH‐psbA). Our data set included all genera associated with Lindsaeaceae, except Xyropteris, and c. 73% of the currently accepted species. The phylogenetic relationships of the lindsaeoid ferns with two enigmatic genera that have recently been included in the Lindsaeaceae, Cystodium and Lonchitis, remain ambiguous. Within the monophyletic lindsaeoids, we found six well‐supported and diagnostic clades that can be recognized as genera: Sphenomeris, Odontosoria, Osmolindsaea, Nesolindsaea, Tapeinidium and Lindsaea. Sphenomeris was shown to be monotypic; most taxa formerly placed in that genus belong to the Odontosoria clade. Ormoloma is embedded within Lindsaea and therefore does not merit recognition as a genus. Tapeinidium is sister to a clade with some species formerly placed in Lindsaea that are morphologically distinct from that genus and are transferred to Osmolindsaea and Nesolindsaea, proposed here as two new genera. We do not maintain the current subgeneric classification of Lindsaea itself, because neither of the two generally accepted subgenera (Lindsaea and Odontoloma) is monophyletic, and most of the sections also appear unnatural. Nesolindsaea shows an ancient biogeographical link between Sri Lanka and the Seychelles and many of the main clades within Lindsaea have geographically disjunct distributions. © 2010 The Linnean Society of London, Botanical Journal of the Linnean Society, 2010, 163 , 305–359.     

The Trypanosoma cruzi ribosomal P protein family: classification and antigenicity

The multi-copy ribosomal P proteins have been identified on the ribosomes of prokaryotic and eukaryotic cells, and their antigenicity is an important feature of human Trypanosoma cruzi infection. In this review, Mariano Levin, Martin Vazquez, Dan Kaplan and Alejandro Schijman give a rational basis for the classification of these proteins, and discuss their inter-relationship.     

吸虱亚目非典型线粒体基因组研究进展

吸虱是真兽类哺乳动物体表的专性寄生虫,在全世界广泛分布,物种数量高达540种。近年来随着分子生物学的飞速发展,在NCBI中已收录15种吸虱线粒体基因组序列,其独特的非典型线粒体基因组发生剧烈的裂化现象,形成数目不等的微环染色体。本文综述了15种吸虱线粒体基因组的结构和组成、RNA基因、非编码区以及对吸虱祖先线粒体核型推测的方法和结果。探讨了不同种属间以及与其它昆虫的差异,提出今后对吸虱亚目线粒体基因组研究的展望。     

An evolving hierarchical family classification for glycosyltransferases

Glycosyltransferases are a ubiquitous group of enzymes that catalyse the transfer of a sugar moiety from an activated sugar donor onto saccharide or non-saccharide acceptors. Although many glycosyltransferases catalyse chemically similar reactions, presumably through transition states with substantial oxocarbenium ion character, they display remarkable diversity in their donor, acceptor and product specificity and thereby generate a potentially infinite number of glycoconjugates, oligo- and polysaccharides. We have performed a comprehensive survey of glycosyltransferase-related sequences (over 7200 to date) and present here a classification of these enzymes akin to that proposed previously for glycoside hydrolases, into a hierarchical system of families, clans, and folds. This evolving classification rationalises structural and mechanistic investigation, harnesses information from a wide variety of related enzymes to inform cell biology and overcomes recurrent problems in the functional prediction of glycosyltransferase-related open-reading frames.     

Protein family classification with partial least squares

The quality of protein function predictions relies on appropriate training of protein classification methods. Performance of these methods can be affected when only a limited number of protein samples are available, which is often the case in divergent protein families. Whereas profile hidden Markov models and PSI-BLAST presented significant performance decrease in such cases, alignment-free partial least-squares classifiers performed consistently better even when used to identify short fragmented sequences.     

Enzyme family classification by support vector machines

One approach for facilitating protein function prediction is to classify proteins into functional families. Recent studies on the classification of G-protein coupled receptors and other proteins suggest that a statistical learning method, Support vector machines (SVM), may be potentially useful for protein classification into functional families. In this work, SVM is applied and tested on the classification of enzymes into functional families defined by the Enzyme Nomenclature Committee of IUBMB. SVM classification system for each family is trained from representative enzymes of that family and seed proteins of Pfam curated protein families. The classification accuracy for enzymes from 46 families and for non-enzymes is in the range of 50.0% to 95.7% and 79.0% to 100% respectively. The corresponding Matthews correlation coefficient is in the range of 54.1% to 96.1%. Moreover, 80.3% of the 8,291 correctly classified enzymes are uniquely classified into a specific enzyme family by using a scoring function, indicating that SVM may have certain level of unique prediction capability. Testing results also suggest that SVM in some cases is capable of classification of distantly related enzymes and homologous enzymes of different functions. Effort is being made to use a more comprehensive set of enzymes as training sets and to incorporate multi-class SVM classification systems to further enhance the unique prediction accuracy. Our results suggest the potential of SVM for enzyme family classification and for facilitating protein function prediction. Our software is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.     

Phylogenetic classification of the family Heteroderidae (Nematoda: Tylenchida)

Summary The family Heteroderidae is revised. On the basis of shared, derived characters sister groups are established and arranged in a phylogenetic tree. A hypothetical, primitive ancestor for the family is defined. The genus Verutus has a large equatorial vulval slit and is considered to be the most primitive form. The genus Meloidodera developed by a reduction in vulval size. Genera which developed later exhibit a subterminally located vulval slit and progressively lost the annulation of the female cuticle. In this process four evolutionary lines emerge: (i) a posterior shift of the vulva and the formation of more or less distinct vulval lips gave rise to the genera Zelandodera and Cryphodera; (ii) changes in the lip configuration of the second-stage juvenile gave rise to the genera Hylonema, Afrodera n.g., Heterodera and Bidera; (iii) changes in the composition of the female cuticle resulted in the genera Thecavermiculatus, Atalodera, Sherodera, Sarisodera and Bellodera n.g. and; (iv) a reduction in vulval slit size led to the development of the genera Dolichodera, Globodera, Cactodera and Punctodera. The genera Ephippiodera and Rhizonema are synonymized with Bidera and Sarisodera respectively. Verutus and Meloidodera are recognized as subfamilies Verutinae and Meloidoderinae and the genera in the four evolutionary lines are recognized as subfamilies Cryphoderinae, Heteroderinae, Ataloderinae and Punctoderinae respectively.Two new genera, Afrodera and Bellodera, are erected for species originally described in Sarisodera and Cryphodera. Both new genera are characterized by a depressed vulval slit and the anus located on the dorsal side of the vulval cone. Differences in lip configuration of the infective juvenile and a postulated difference in female cuticle justifies their placement in different subfamilies. The lip configuration of the infective juveniles in the subfamilies Verutinae, Meloidoderinae, Cryphoderinae, Ataloderinae and Punctoderinae remains basically unchanged. The possible development of this character in the subfamily Heteroderinae is discussed and illustrated. The family Heteroderidae, its six subfamilies and 17 genera are defined or redefined, and for each of the genera the nominal species and their synonyms are listed. New synonyms introduced are: Heterodera rumicis and H. scleranthi of H. trifolii, H. ustinova of Bidera avenae and H. mali of Globodera chaubattia. Cactodera acnidae (Schuster & Brezina, 1979) n. comb. and Dolichodera andinus (Golden, Franco, Jatala & Astogaza, 1983) n. comb. are transferred from Heterodera and Thecavermiculatus respectively. Keys are provided for all taxa for which no suitable keys are available in the literature. Species inquirendae are listed. ac]19840606     

Protein family classification using sparse markov transducers.

We present a method for classifying proteins into families based on short subsequences of amino acids using a new probabilistic model called sparse Markov transducers (SMT). We classify a protein by estimating probability distributions over subsequences of amino acids from the protein. Sparse Markov transducers, similar to probabilistic suffix trees, estimate a probability distribution conditioned on an input sequence. SMTs generalize probabilistic suffix trees by allowing for wild-cards in the conditioning sequences. Since substitutions of amino acids are common in protein families, incorporating wild-cards into the model significantly improves classification performance. We present two models for building protein family classifiers using SMTs. As protein databases become larger, data driven learning algorithms for probabilistic models such as SMTs will require vast amounts of memory. We therefore describe and use efficient data structures to improve the memory usage of SMTs. We evaluate SMTs by building protein family classifiers using the Pfam and SCOP databases and compare our results to previously published results and state-of-the-art protein homology detection methods. SMTs outperform previous probabilistic suffix tree methods and under certain conditions perform comparably to state-of-the-art protein homology methods.     

Analysis and classification of vegetation based on family composition

Plant Ecology - The distributions of 54 plant families in 105 samples were studied to determine their indicator value in the vegetation of the Pacific Northwest. Families may be characteristic of...     

Analysis and classification of vegetation based on family composition

Summary The distributions of 54 plant families in 105 samples were studied to determine their indicator value in the vegetation of the Pacific Northwest. Families may be characteristic of particular environments or geographic conditions or they may distinguish between sets of samples. Principal components analysis, numerical classification, and stepwise discriminant analysis were used in this study.Principal components analysis identifies a family if it is common or dominant and has a distribution concentrated at one extreme of an axis of variation. Families with consistent patterns of distribution are useful in distinguishing between groups of samples previously created by numerical classification methods.Twenty-three families that contain environmental, successional, or geographical information were identified according to one or more methods.Nomenclature for species names in Washington follows Hitchcock & Cronquist (1973). Species names from the Alsek River, Yukon Territory, follows authorities cited by Douglas (1974).This study was funded in part by the U.S. National Science Foundation and by the Graduate School, University of Washington. We thank A.R. Kruckeberg, M.J. Cushman, R.A. Lerner, V. Seymour and A.F. Watson for thoughtful comments and stimulating discussion and R.W. Fonda, R.T. Kuromoto, G.W. Douglas and J.A. Belsky for the use of their data.     

构建适用于蛋白质家族分类的相似性网络

图聚类用于蛋白质分类问题可以获得较好结果,其前提是将蛋白质之间复杂的相互关系转化为适当的相似性网络作为图聚类分类的输入数据。本文提出一种基于BLAST检索的相似性网络构建方法,从目标蛋白质序列出发,通过若干轮次的BLAST检索逐步从数据库中提取与目标蛋白质直接或间接相关的序列,构成关联集。关联集中序列之间的相似性关系即相似性网络,可作为图聚类算法的分类依据。对Pfam数据库中依直接相似关系难以正确分类的蛋白质的计算表明,按本文方法构建的相似性网络取得了比较满意的结果。