James W. Fickett

Human-mouse genome comparisons to locate regulatory sites

Elucidating the human transcriptional regulatory network is a challenge of the post-genomic era. Technical progress so far is impressive, including detailed understanding of regulatory mechanisms for at least a few genes in multicellular organisms, rapid and precise localization of regulatory regions within extensive regions of DNA by means of cross-species comparison, and de novo determination of transcription-factor binding specificities from large-scale yeast expression data. Here we address two problems involved in extending these results to the human genome: first, it has been unclear how many model organism genomes will be needed to delineate most regulatory regions; and second, the discovery of transcription-factor binding sites (response elements) from expression data has not yet been generalized from single-celled organisms to multicellular organisms. We found that 98% (74/75) of experimentally defined sequence-specific binding sites of skeletal-muscle-specific transcription factors are confined to the 19% of human sequences that are most conserved in the orthologous rodent sequences. Also we found that in using this restriction, the binding specificities of all three major muscle-specific transcription factors (MYF, SRF and MEF2) can be computationally identified.

The GenBank genetic sequence databank

The GenBank Genetic Sequence Data Bank contains over 5700 entries for DNA and RNA sequences that have been reported since 1967. This paper briefly describes the contents of the database, the forms in which the database is distributed, and the services we offer to scientists who use the GenBank database.

Discovery and modeling of transcriptional regulatory regions

A complex network of regulatory controls governs the patterns of gene expression. Enabled by the tools of molecular cloning, initial experimental queries into the gene regulatory network elucidated a wide array of transcription factors and their cognate binding sites from hundreds of genes. The recent fusion of genome-scale experimental tools, a more comprehensive gene catalog, and concomitant advances in computational methodology, has extended the range of questions being posed. The potential to further our understanding of the biochemical mechanisms of transcriptional regulation and to accelerate the delineation of regulatory control regions in the human genome is enormous.

Quantitative discrimination of MEF2 sites.

Myocyte-specific enhancer factor 2 (MEF2) is a family of closely related transcription factors that play a key role in the differentiation of muscle tissues and are important in the muscle-specific expression of a number of genes. Given the centrality of MEF2 in muscle differentiation, regulatory regions newly determined to be muscle specific are often studied for potential MEF2 binding sites. Possible sites are often located by comparison to a homologous gene or by matching to the consensus MEF2 sequence. Enough data have accumulated that a richer description of the MEF2 binding site, a position weight matrix, can be reliably constructed and its usefulness can be assessed. It was shown that scores from such a matrix approximate MEF2 binding energy and enable recognition of naturally occurring MEF2 sites with high sensitivity and specificity. Regulation of genes via MEF2-like sites is complicated by the fact that a number of transcription factors are involved. Not only is MEF2 itself a family of proteins, but several other, nonhomologous, transcription factors overlap MEF2 in DNA-binding specificity. Thus, more quantitative methods for recognizing potential sites may help with the lengthy process of disentangling the complex regulatory circuits of muscle-specific expression.

Base compositional structure of genomes.

We model the base compositional structure of the human and Escherichia coli genomes. Three particular properties are first quantified: (1) There is a significant tendency for any region of either genome to have a strand-symmetric base composition. (2) The variation in base composition from region to region, within each genome, is very much larger than expected from common homogeneous stochastic models. (3) A given local base composition tends to persist over a scale of at least kilobases (E. coli) or tens of kilobases (human). Multidomain stochastic models from the literature are reviewed and sharpened. In particular, quantitative measurements of the third property lead us to suggest a significant shift in the style of domain models, in which the variation of A+T content with position is modeled by a random walk with frequent small steps rather than with large quantum jumps. As an application, we suggest a way to reduce the amount of computation in the assembly of large sequences from sequences of randomly chosen fragments.

The gene identification problem: an overview for developers.

The gene identification problem is the problem of interpreting nucleotide sequences by computer, in order to provide tentative annotation on the location, structure, and functional class of protein-coding genes. This problem is of self-evident importance, and is far from being fully solved, particularly for higher eukaryotes. Thus it is not surprising that the number of algorithm and software developers working in the area is rapidly increasing. The present paper is an overview of the field, with an emphasis on eukaryotes, for such developers.

Fast optimal alignment

We show how to speed up sequence alignment algorithms of the type introduced by Needleman and Wunsch (and generalized by Sellers and others). Faster alignment algorithms have been introduced, but always at the cost of possibly getting sub-optimal alignments. Our modification results in the optimal alignment still being found, often in 1/10 the usual time. What we do is reorder the computation of the usual alignment matrix so that the optimal alignment is ordinarily found when only a small fraction of the matrix is filled. The number of matrix elements which have to be computed is related to the distance between the sequences being aligned; the better the optimal alignment, the faster the algorithm runs.

COORDINATE POSITIONING OF MEF2 AND MYOGENIN BINDING SITES

The MEF2 and MyoD families of transcriptional regulatory factors both play central roles in the terminal differentiation of skeletal muscle. Further, binding sites for the two families often occur nearby, and there have been a number of indications that members of the two families may bind coordinately. The present study provides evidence that known binding sites for the two occur with precise geometric restrictions related to the DNA helical repeat unit, that pairs of putative sites following these restrictions are indicative of skeletal muscle-specific transcriptional regulatory regions, and that the geometric relationship can help provide a consistent interpretation for data that has until now been difficult to explain.

CABIOS REVIEW The GenBank nucleic acid sequence database

The GenBank nucleic acid sequence database is a computer-based collection of all published DNA and RNA sequences; it contains over five million bases in close to six thousand sequence entries drawn from four thousand five hundred published articles. Each sequence is accompanied by relevant biological annotation. The database is available either on magnetic tape, on floppy diskettes, on-line or in hardcopy form. We discuss the structure of the database, the extent of the data and the implications of the database for research on nucleic acids.

Evaluation of a cosmid contig physical map of human chromosome 16

A cosmid contig physical map of human chromosome 16 has been developed by repetitive sequence finger-printing of approximately 4000 cosmid clones obtained from a chromosome 16-specific cosmid library. The arrangement of clones in contigs is determined by (1) estimating cosmid length and determining the likelihoods for all possible pairwise clone overlaps, using the fingerprint data, and (2) using an optimization technique to fit contig maps to these estimates. Two important questions concerning this contig map are how much of chromosome 16 is covered and how accurate are the assembled contigs. Both questions can be addressed by hybridization of single-copy sequence probes to gridded arrays of the cosmids. All of the fingerprinted clones have been arrayed on nylon membranes so that any region of interest can be identified by hybridization. The hybridization experiments indicate that approximately 84% of the euchromatic arms of chromosome 16 are covered by contigs and singleton cosmids. Both grid hybridization (26 contigs) and pulsed-field gel electrophoresis experiments (11 contigs) confirmed the assembled contigs, indicating that false positive overlaps occur infrequently in the present map. Furthermore, regional localization of 93 contigs and singleton cosmids to a somatic cell hybrid mapping panel indicates that there is no bias in the coverage of the euchromatic arms.