Comparison of parametric and nonparametric methods to map oligogenes by linkage

A sample of 95 sib pairs affected with insulin-dependent diabetes and typed with their normal parents for 28 markers on chromosome 6 has been analyzed by several methods. When appropriate parameters are efficiently estimated, a parametric model is equivalent to the β model, which is superior to nonparametric alternatives both in single point tests (as found previously) and in multipoint tests. Theory is given for meta-analysis combined with allelic association, and problems that may be associated with errors of map location and/or marker typing are identified. Reducing by multipoint analysis the number of association tests in a dense map can give a 3-fold reduction in the critical lod, and therefore in the cost of positional cloning.

STACK: Sequence Tag Alignment and Consensus Knowledgebase

STACK is a tool for detection and visualisation of expressed transcript variation in the context of developmental and pathological states. The datasystem organises and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index and is accessible via WWW at http://www.sanbi.ac.za/Dbases.html. STACK represents a broadly applicable resource, as it is the only reconstructed transcript database for which the tools for its generation are also broadly available (http://www.sanbi.ac.za/CODES).

Calicheamicin-DNA complexes: warhead alignment and saccharide recognition of the minor groove.

The solution structures of calicheamicin gamma 1I, its cycloaromatized analog (calicheamicin epsilon), and its aryl tetrasaccharide complexed to a common DNA hairpin duplex have been determined by NMR and distance-refined molecular dynamics computations. Sequence specificity is associated with carbohydrate-DNA recognition that places the aryl tetrasaccharide component of all three ligands in similar orientations in the minor groove at the d(T-C-C-T).d(A-G-G-A) segment. The complementary fit of the ligands and the DNA minor groove binding site creates numerous van der Waals contacts as well as hydrogen bonding interactions. Notable are the iodine and sulfur atoms of calicheamicin that hydrogen bond with the exposed amino proton of the 5'- and 3'-guanines, respectively, of the d(A-G-G-A) segment. The sequence-specific carbohydrate binding orients the enediyne aglycone of calicheamicin gamma 1I such that its C3 and C6 proradical centers are adjacent to the cleavage sites. While the enediyne aglycone of calicheamicin gamma 1I is tilted relative to the helix axis and spans the minor groove, the cycloaromatized aglycone is aligned approximately parallel to the helix axis in the respective complexes. Specific localized conformational perturbations in the DNA have been identified from imino proton complexation shifts and changes in specific sugar pucker patterns on complex formation. The helical parameters for the carbohydrate binding site are comparable with corresponding values in B-DNA fibers while a widening of the groove is observed at the adjacent aglycone binding site.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco­protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O-linked oligosaccharides from the last 50 years and most N-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono­isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N- or O-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.

PALI—a database of Phylogeny and ALIgnment of homologous protein structures

PALI (release 1.2) contains three-dimensional (3-D) structure-dependent sequence alignments as well as structure-based phylogenetic trees of homologous protein domains in various families. The data set of homologous protein structures has been derived by consulting the SCOP database (release 1.50) and the data set comprises 604 families of homologous proteins involving 2739 protein domain structures with each family made up of at least two members. Each member in a family has been structurally aligned with every other member in the same family (pairwise alignment) and all the members in the family are also aligned using simultaneous super­position (multiple alignment). The structural alignments are performed largely automatically, with manual interventions especially in the cases of distantly related proteins, using the program STAMP (version 4.2). Every family is also associated with two dendrograms, calculated using PHYLIP (version 3.5), one based on a structural dissimilarity metric defined for every pairwise alignment and the other based on similarity of topologically equivalent residues. These dendrograms enable easy comparison of sequence and structure-based relationships among the members in a family. Structure-based alignments with the details of structural and sequence similarities, superposed coordinate sets and dendrograms can be accessed conveniently using a web interface. The database can be queried for protein pairs with sequence or structural similarities falling within a specified range. Thus PALI forms a useful resource to help in analysing the relationship between sequence and structure variation at a given level of sequence similarity. PALI also contains over 653 ‘orphans’ (single member families). Using the web interface involving PSI_BLAST and PHYLIP it is possible to associate the sequence of a new protein with one of the families in PALI and generate a phylogenetic tree combining the query sequence and proteins of known 3-D structure. The database with the web interfaced search and dendrogram generation tools can be accessed at http://pa uling.mbu.iisc.ernet.in/~pali.

Genome projects and gene pools: New germplasm for plant breeding?

Crop gene pools have adapted to and sustained the demands of agricultural systems for thousands of years. Yet, very little is known about their content, distribution, architecture, or circuitry. The presumably shallow elite gene pools often continue to yield genetic gains while the exotic pools remain mostly untapped, uncharacterized, and underutilized. The concept and content of a crop’s gene pools are being changed by advancements in plant science and technology. In the first generation of plant genomics, DNA markers have refined some perceptions of genetic variation by providing a glimpse of a primary source, DNA polymorphism. The markers have provided new and more powerful ways of assessing genetic relationships, diversity, and merit by infusing genetic information for the first time in many scenarios or in a more comprehensive manner for others. As a result, crop gene pools may be supplemented through more rapid and directed methods from a greater variety of sources. Previously limited by the barriers of sexual reproduction, the native gene pools will soon be complemented by another gene pool (transgenes) and perhaps by other native exotic gene pools through comparative analyses of plants’ biological repertoire. Plant genomics will be an important force of change for crop improvement. The plant science community and crop gene pools may be united and enriched as never before. Also, the genomes and gene pools, the products of evolution and crop domestication, will be reduced and subjected to the vagaries and potential divisiveness of intellectual property considerations. Let the gains begin.

Assembly and transport of a premessenger RNP particle

Salivary gland cells in the larvae of the dipteran Chironomus tentans offer unique possibilities to visualize the assembly and nucleocytoplasmic transport of a specific transcription product. Each nucleus harbors four giant polytene chromosomes, whose transcription sites are expanded, or puffed. On chromosome IV, there are two puffs of exceptional size, Balbiani ring (BR) 1 and BR 2. A BR gene is 35–40 kb, contains four short introns, and encodes a 1-MDa salivary polypeptide. The BR transcript is packed with proteins into a ribonucleoprotein (RNP) fibril that is folded into a compact ring-like structure. The completed RNP particle is released into the nucleoplasm and transported to the nuclear pore, where the RNP fibril is gradually unfolded and passes through the pore. On the cytoplasmic side, the exiting extended RNP fibril becomes engaged in protein synthesis and the ensuing polysome is anchored to the endoplasmic reticulum. Several of the BR particle proteins have been characterized, and their fate during the assembly and transport of the BR particle has been elucidated. The proteins studied are all added cotranscriptionally to the pre-mRNA molecule. The various proteins behave differently during RNA transport, and the flow pattern of each protein is related to the particular function of the protein. Because the cotranscriptional assembly of the pre-mRNP particle involves proteins functioning in the nucleus as well as proteins functioning in the cytoplasm, it is concluded that the fate of the mRNA molecule is determined to a considerable extent already at the gene level.