Conversion of nucleotides sequences into genomic signals

An original tetrahedral representation of the Genetic Code (GC) that better describes its structure, degeneration and evolution trends is defined. The possibility to reduce the dimension of the representation by projecting the GC tetrahedron on an adequately oriented plane is also analyzed, leading to some equivalent complex representations of the GC. On these bases, optimal symbolic-to-digital mappings of the linear, nucleic acid strands into real or complex genomic signals are derived at nucleotide, codon and amino acid levels. By converting the sequences of nucleotides and polypeptides into digital genomic signals, this approach offers the possibility to use a large variety of signal processing methods for their handling and analysis. It is also shown that some essential features of the nucleotide sequences can be better extracted using this representation. Specifically, the paper reports for the first time the existence of a global helicoidal wrapping of the complex representations of the bases along DNA sequences, a large scale trend of genomic signals. New tools for genomic signal analysis, including the use of phase, aggregated phase, unwrapped phase, sequence path, stem representation of components'relative frequencies, as well as analysis of the transitions are introduced at the nucleotide, codon and amino acid levels, and in a multiresolution approach.     

Statistical analysis of yeast genomic downstream sequences reveals putative polyadenylation signals

The study of a few genes has permitted the identification of three elements that constitute a yeast polyadenylation signal: the efficiency element (EE), the positioning element and the actual site for cleavage and polyadenylation. In this paper we perform an analysis of oligonucleotide composition on the sequences located downstream of the stop codon of all yeast genes. Several oligonucleotide families appear over-represented with a high significance (referred to herein as ‘words’). The family with the highest over-representation includes the oligonucleotides shown experimentally to play a role as EEs. The word with the highest score is TATATA, followed, among others, by a series of single-nucleotide variants (TATGTA, TACATA, TAAATA . . .) and one-letter shifts (ATATAT). A position analysis reveals that those words have a high preference to be in 3′ flanks of yeast genes and there they have a very uneven distribution, with a marked peak around 35 bp after the stop codon. Of the predicted ORFs, 85% show one or more of those sequences. Similar results were obtained using a data set of EST sequences. Other clusters of over-represented words are also detected, namely T- and A-rich signals. Using these results and previously known data we propose a general model for the 3′ trailers of yeast mRNAs.     

Field-effect devices for detecting cellular signals

The integration of living cells together with silicon field-effect devices challenges a new generation of biosensors and bioelectronic devices. Cells are representing highly organised complex systems, optimised by millions of years of evolution and offering a broad spectrum of bioanalytical receptor “tools” such as enzymes, nucleic acids proteins, etc. Their combination with semiconductor-based electronic chips allows the construction of functional hybrid systems with unique functional and electronic properties for both fundamental studies and biosensoric applications. This review article summarises recent advances and trends in research and development of cell/transistor hybrids (cell-based field-effect transistors) as well as light-addressable potentiometric sensors.     

Isolation of two genomic sequences encoding the Mr = 14,000 subunit of rat prostatein

Complementary DNAs to rat ventral prostate poly(A) RNA were cloned into pBR322 by the "dG-dC tailing" procedure. Clones containing cDNAs to the mRNAs coding for each of the three subunits of a major secretory protein (prostatein) were identified by hybrid-arrested translation. A 457-nucleotide base pair cDNA (E45) and a portion of a 365-base pair cDNA (E85) were analyzed to determine the composite complete DNA coding sequence for the Mr = 14,000 (C3) subunit of prostatein. A sequence of 12-nucleotide bases (TTTGCTGCTATG) in the signal peptide of C3 was noted to be homologous to signal peptide nucleotide sequences reported in cDNAs coding for the other two prostatein subunits, Mr = 6,000 (C1) and 10,000 (C2). Complementary DNA coding for the C3 subunit was used as a hybridization probe to screen an EcoRI rat genomic DNA library. Two unique 12-kilobase genomic clones, each containing mRNA coding sequences within 2.5-3-kilobase fragments, were identified by restriction enzyme mapping and Southern blot analysis. Restriction enzyme sites within the coding regions of both genes were analogous to the cDNA. Differences in restriction enzyme sites in regions of intervening sequences and flanking DNA established the uniqueness of the two genes. It is suggested that both genes may be transcribed in vivo.     

Expression of amplified cDNA and genomic sequences encoding human interleukin 2 in Chinese hamster ovary cells

Expression of human interleukin 2 (IL-2) at high levels has been achieved in Chinese hamster ovary (CHO) cells by amplification of transfected sequences. Plasmids containing the human IL-2 cDNA or genomic DNA and mouse dihydrofolate reductase (DHFR) cDNA were transfected into DHFR-negative CHO cells. Transformants expressing DHFR were selected in media lacking nucleosides, and cells which amplified both DHFR and IL-2 genes were obtained by exposure to increasing methotrexate (MTX) concentrations. These cell lines constitutively expressed elevated levels of IL-2 at a concentration of 2 mg/liter. These cell lines continued to produce IL-2 stably through at least 1 month, even in the absence of MTX.     

EGID: an ensemble algorithm for improved genomic island detection in genomic sequences

Genomic islands (GIs) are genomic regions that are originally transferred from other organisms. The detection of genomic islands in genomes can lead to many applications in industrial, medical and environmental contexts. Existing computational tools for GI detection suffer either low recall or low precision, thus leaving the room for improvement. In this paper, we report the development of our Ensemble algorithm for Genomic Island Detection (EGID). EGID utilizes the prediction results of existing computational tools, filters and generates consensus prediction results. Performance comparisons between our ensemble algorithm and existing programs have shown that our ensemble algorithm is better than any other program. EGID was implemented in Java, and was compiled and executed on Linux operating systems. EGID is freely available at http://www5.esu.edu/cpsc/bioinfo/software/EGID.     

An algorithm for searching RNA motifs in genomic sequences

RNA molecules, which are found in all living cells, fold into characteristic structures that account for their diverse functional activities. Many of these RNA structures consist of a collection of fundamental RNA motifs. The various combinations of RNA basic components form different RNA classes and define their unique structural and functional properties. The availability of many genome sequences makes it possible to search computationally for functional RNAs. Biological experiments indicate that functional RNAs have characteristic RNA structural motifs represented by specific combinations of base pairings and conserved nucleotides in the loop regions. The searching for those well-ordered RNA structures and their homologues in genomic sequences is very helpful for the understanding of RNA-based gene regulation. In this paper, we consider the following problem: given an RNA sequence with a known secondary structure, efficiently determine candidate segments in genomic sequences that can potentially form RNA secondary structures similar to the given RNA secondary structure. Our new bottom-up approach searches all potential stem-loops similar to ones of the given RNA secondary structure first, and then based on located stem-loops, detects potential homologous structural RNAs in genomic sequences.     

Markov models for covariate dependence of binary sequences

Suppose that a heterogeneous group of individuals is followed over time and that each individual can be in state 0 or state 1 at each time point. The sequence of states is assumed to follow a binary Markov chain. In this paper we model the transition probabilities for the 0 to 0 and 1 to 0 transitions by two logistic regressions, thus showing how the covariates relate to changes in state. With p covariates, there are 2(p + 1) parameters including intercepts, which we estimate by maximum likelihood. We show how to use transition probability estimates to test hypotheses about the probability of occupying state 0 at time i (i = 2, ..., T) and the equilibrium probability of state 0. These probabilities depend on the covariates. A recursive algorithm is suggested to estimate regression coefficients when some responses are missing. Extensions of the basic model which allow time-dependent covariates and nonstationary or second-order Markov chains are presented. An example shows the model applied to a study of the psychological impact of breast cancer in which women did or did not manifest distress at four time points in the year following surgery.     

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.     

Inconsistencies in Neanderthal genomic DNA sequences

Two recently published papers describe nuclear DNA sequences that were obtained from the same Neanderthal fossil. Our reanalyses of the data from these studies show that they are not consistent with each other and point to serious problems with the data quality in one of the studies, possibly due to modern human DNA contaminants and/or a high rate of sequencing errors.     

Screening techniques for detecting allelic variation in DNA sequences

This article reviews four 'DNA screening techniques', namely heteroduplex analysis, single-strand conformational polymorphism (SSCP), denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) as tools for the study of allelic variation in natural populations. The resolving power, advantages, and limitations of each technique are discussed and compared. We also provide some criteria for choosing among techniques and illustrate some practical issues with examples taken primarily from our own laboratory experience.     

GIST: Genomic island suite of tools for predicting genomic islands in genomic sequences

Genomic Islands (GIs) are genomic regions that are originally from other organisms, through a process known as Horizontal Gene Transfer (HGT). Detection of GIs plays a significant role in biomedical research since such align genomic regions usually contain important features, such as pathogenic genes. We have developed a use friendly graphic user interface, Genomic Island Suite of Tools (GIST), which is a platform for scientific users to predict GIs. This software package includes five commonly used tools, AlienHunter, IslandPath, Colombo SIGI-HMM, INDeGenIUS and Pai-Ida. It also includes an optimization program EGID that ensembles the result of existing tools for more accurate prediction. The tools in GIST can be used either separately or sequentially. GIST also includes a downloadable feature that facilitates collecting the input genomes automatically from the FTP server of the National Center for Biotechnology Information (NCBI). GIST was implemented in Java, and was compiled and executed on Linux/Unix operating systems. AVAILABILITY: The database is available for free at http://www5.esu.edu/cpsc/bioinfo/software/GIST.     

Algorithms for isolating regulatory signals in DNA sequences]

An algorithm is proposed for extracting regulatory signals from DNA sequences. The algorithm complexity is nearly quadratic. The results of testing the algorithm on artificial and natural sequences are presented.     

A space-efficient algorithm for aligning large genomic sequences

SUMMARY: In the segment-by-segment approach to sequence alignment, pairwise and multiple alignments are generated by comparing gap-free segments of the sequences under study. This method is particularly efficient in detecting local homologies, and it has been used to identify functional regions in large genomic sequences. Herein, an algorithm is outlined that calculates optimal pairwise segment-by-segment alignments in essentially linear space. AVAILABILTIY: The program is available at the Bielefeld Bioinformatics Server (BiBiServ) at http://bibiserv.techfak. uni-bielefeld.de/dialign/     

Arabidopsis genomic information for interpreting wheat EST sequences

The resources available from Arabidopsis thaliana for interpreting functional attributes of wheat EST are reviewed. A focus for the review is a comparison between wheat EST sequences, generated from developing endosperm tissue, and the complete genomic sequence from Arabidopsis. The available information indicates that not only can tentative annotations be assigned to many wheat genes but also putative or unknown Arabidopsis gene annotations can be improved by comparative genomics. Electronic Publication