Influence of intercodon and base frequencies on codon usage in filarial parasites

Base frequency, codon usage, and intercodon identity were analyzed in five filarial parasite species representing five Onchocercidae genera. Wucheria bancrofti, Brugia malayi, Onchocerca volvulus, Acanthocheilonema viteae, and Dirofilaria immitis gene sequences were downloaded from NCBI, and analysis was performed using locally designed computer programs and other freely available applications. A clear sequence bias was observed among the nematode species examined. At the nucleotide level, AT basepairs were present in gene sequences at higher frequencies than GC. In addition, codons ending in A or T were used proportionately more than those with G or C in the third-codon position. In addition, the amino acids used most often corresponded to codons ending in AT basepairs. Intercodon base proportion was biased in that A was found most often at N4, second only to T in certain specific cases. Since all of these sequence biases were observed in a relatively consistent fashion among all of the organisms studied, we conclude that sequence bias is a genetic characteristic, which is associated with multiple filarial genera.     

TM Finder: a prediction program for transmembrane protein segments using a combination of hydrophobicity and nonpolar phase helicity scales

Based on the principle of dual prediction by segment hydrophobicity and nonpolar phase helicity, in concert with imposed threshold values of these two parameters, we developed the automated prediction program TM Finder that can successfully locate most transmembrane (TM) segments in proteins. The program uses the results of experiments on a series of host-guest TM segment mimic peptides of prototypic sequence KK AAAXAAAAAXAAWAAXAAAKKKK-amide (where X = each of the 20 commonly occurring amino acids) through which an HPLC-derived hydropathy scale, a hydrophobicity threshold for spontaneous membrane insertion, and a nonpolar phase helical propensity scale were determined. Using these scales, the optimized prediction algorithm of TM Finder defines TM segments by first searching for competent core segments using the combination of hydrophobicity and helicity scales, and then performs a gap-joining operation, which minimizes prediction bias caused by local hydrophilic residues and/or the choice of window size. In addition, the hydrophobicity threshold requirement enables TM Finder to distinguish reliably between membrane proteins and globular proteins, thereby adding an important dimension to the program. A full web version of the TM Finder program can be accessed at http://www.bioinformatics-canada.org/TM/.     

The Use of Simulated Annealing in Chromosome Reconstruction Experiments Based on Binary Scoring

We present a method of combinatorial optimization, simulated annealing, to order clones in a library with respect to their position along a chromosome. This ordering method relies on scoring each clone for the presence or absence of specific target sequences, thereby assigning a digital signature to each clone. Specifically, we consider the hybridization of oligonucleotide probes to a clone to constitute the signature. In that the degree of clonal overlap is reflected in the similarity of their signatures, it is possible to construct maps based on the minimization of the differences in signatures across a reconstructed chromosome. Our simulations show that with as few as 30 probes and a clonal density of 4.5 genome equivalents, it is possible to assemble a small eukaryotic chromosome into 33 contiguous blocks of clones (contigs). With higher clonal densities and more probes, this number can be reduced to less than 5 contigs per chromosome.     

Inconsistencies between human genetic cytolocations and those derived using genomic sequence

One result of the publishing of the human genome sequence is the ability to define objects through their position on the consensus sequence. While this has simplified the process of creating order maps for genes on a chromosome, it has created discrepancies between the published cytolocations of human genes, as presented through genetic references, and those locations derived computationally from the genomic sequence. For the 6,830 records with HUGO gene symbols shared between the online version of Mendelian Inheritance in Man and Ensembl, 18% of the records have a discrepancy of at least one cytogenetic band between the datasets. Discordance between data sets at this frequency would have a significant impact on the utility of datasets created by the amalgamation of numerous biological databases.     

Chromosome-specific recombinant DNA libraries from the fungus Aspergillus nidulans.

Development of physical genomic maps is facilitated by identification of overlapping recombinant DNA clones containing long chromosomal DNA inserts. To simplify the analysis required to determine which clones in a genomic library overlap one another, we partitioned Aspergillus nidulans cosmid libraries into chromosome-specific subcollections. The eight A. nidulans chromosomes were resolved by pulsed field gel electrophoresis and hybridized to filter replicas of cosmid libraries. The subcollections obtained appeared to be representative of the chromosomes based on the correspondence between subcollection size and chromosome length. A sufficient number of clones was obtained in each chromosome-specific subcollection to predict the overlap and assembly of individual clones into a limited number of contiguous regions. This approach should be applicable to many organisms whose genomes can be resolved by pulsed field gel electrophoresis.     

The application of Markov chain analysis to oligonucleotide frequency prediction and physical mapping of Drosophila melanogaster.

Here we compare several methods for predicting oligonucleotide frequencies in 691 kb of Drosophila melanogaster DNA. As in previous work on Escherichia coli and Saccharomyces cerevisiae, a relatively simple equation based on tetranucleotide frequencies can be used in predicting frequencies of higher order oligonucleotides. For example, the mean of observed/expected abundances of 4,096 hexamers was 1.07 with a sample standard deviation of .55. This simple predictor arises by considering each base on the sense strand of D. melanogaster to depend only on the three bases 5' to it (a 3rd order Markov chain) and is more accurate than the random predictor. This equation is useful in predicting restriction enzyme fragment sizes, selecting restriction enzymes that cut preferentially in coding vs noncoding regions, and in selecting probes to fingerprint clones in contig mapping. Once again, this equation well predicts the occurrence of higher order oligonucleotides, supporting our hypothesis that this predictor holds in evolutionarily diverse organisms. When ranked from highest to lowest abundance, the observed frequencies of oligomers of a given length are closely tracked by the predicted abundances of a 3rd order Markov chain. Through use of the dependence of oligomer frequencies on base composition, we report a list of oligomers that will be useful for the completion of a cosmid physical map of D. melanogaster. Presently, the library is such that it will be possible to construct large contigs using only 30 oligonucleotide probes to fingerprint cosmids.     

The GDB human genome data base anno 1993.

Version 5.0 of the Genome Data Base (GDB) was released in March 1993. This document describes some of the significant changes to the types of data which are stored within the GDB. In addition to handling a wider scope of data, the GDB 5.0 application software now supports the X-Windows protocol. Although the GDB software still remains the most widely utilized method for accessing the data, alternate methods of access are now available, including direct SQL (Structured Query Language) queries, FTP (Internet File Transfer Protocol), WAIS (Wide Area Information Server), and other tools produced by third-party developers.     

The GDB Human Genome Data Base anno 1994.

In 1991 the Genome Data Base at Johns Hopkins University School of Medicine was selected as the central repository for mapping data from the Human Genome Project, and was funded by NIH and DOE under a three year award. GDB has now finished 28 months of Federally funded operation. During this period a great deal of progress and many internal changes have taken place. In addition, many changes have also occurred in the external environment, and GDB has adapted its strategies to play an appropriate role in those changes as well. Recognizing the central role of mapping information in the genome project, it is important that GDB respond aggressively to the increasing demands of genomic researchers, as well as formulate a program of response to a number of long standing, but still unmet, needs of that community. It is even more important that GDB provide leadership in the genome informatics enterprise. Three themes described here are dominant in our future plans and represent the essence of the major changes made in the past year. They include: enhanced data acquisition, better map representation, and full integration into the collection of genomic databases.