Biomedical subjects

Darrell Conklin

Publications and source records attributed to Darrell Conklin.

5 recordsLinked to original sources

PubMed2005

Gene finding for the helical cytokines.

MOTIVATION: Gene finding remains an open problem well after the sequencing of the human genome. The low gene sensitivity of current methods is a problem for divergent protein families, because fairly accurate exon assemblies are required before sensitive fold recognition algorithms can be applied. This paper presents a new genomic threading algorithm which integrates the gene finding and fold recognition steps into a single process. The method is applicable to evolutionarily divergent protein families that have retained some trace of their common ancestry, number and phase of introns, sizes of exons and placement of structural elements on specific exons. Such conserved structural signals may be visible despite dramatic evolution of protein sequence. RESULTS: The method is evaluated on the family of helical cytokines by cross-validation sensitivity analysis. The method has also been applied to all intergenic regions of the human genome, and an expression and cloning approach has been coupled with the predictions of the method. Two genes discovered by this method are discussed. SUPPLEMENTARY INFORMATION: All data used and the results obtained in the cross-validation analysis are available at http://www.soi.city.ac.uk/~conklin/papers/GT/

Algorithms↗

PubMed2004

Recognition of the helical cytokine fold.

Cytokines are an important class of proteins responsible for intercellular communication. The helical cytokines have a four-helix bundle fold, and they have remained largely intractable for sequence alignment methods due to their high evolutionary divergence. This paper presents a method that is specifically designed to recognize the helical cytokine fold in preprotein sequences such as full-length cDNA translations or transcripts predicted by gene finding methods. A protein fold is modeled by multiple sequence profiles, each representing a structurally conserved region. Nonstructural profiles are used to represent additional signals found in preprotein sequences. Profiles are connected by loop regions, each of a specified minimum and maximum length. A model for the helical cytokines is created by progressively improving a placement of four amphipathic helices onto training sequences. The sensitivity and specificity of the method are evaluated by a cross-validation procedure, demonstrating that cytokines with no intrafamily sequence similarity can be recognized. The method has been successfully used for the discovery of several new helical cytokines in the human genome.

Amino Acid Motifs↗

PubMed2003

A transcriptionally active human type II gonadotropin-releasing hormone receptor gene homolog overlaps two genes in the antisense orientation on chromosome 1q.12.

GnRH-II peptide hormone exhibits complete sequence conservation across vertebrate species, including man. Type-II GnRH receptor genes have been characterized recently in nonhuman primates, but the human receptor gene homolog contains a frameshift, a premature stop codon (UGA), and a 3' overlap of the RBM8A gene on chromosome 1q.12. A retrotransposed pseudogene, RBM8B, retains partial receptor sequence. In this study, bioinformatics show that the human receptor gene promoter overlaps the peroxisomal protein 11-beta gene promoter and the premature UGA is positionally conserved in chimpanzee. A CGA [arginine (Arg)] occurs in porcine DNA, but UGA is shifted one codon to the 5' direction in bovine DNA, suggesting independent evolution of premature stop codons. In contrast to marmoset tissue RNA, exon- and strand-specific probes are required to distinguish differently spliced human receptor gene transcripts in cell lines (HP75, IMR-32). RBM8B is not transcribed. Sequencing of cDNAs for spliced receptor mRNAs showed no evidence for alteration of the premature UGA by RNA editing, but alternative splicing circumvents the frameshift to encode a two-membrane-domain protein before this UGA. A stem-loop motif resembling a selenocysteine insertion sequence and a potential alternative translation initiation site might enable expression of further proteins involved in interactions within the GnRH system.

Adenoma↗

PubMed2002

Association of nucleotide patterns with gene function classes: application to human 3' untranslated sequences.

MOTIVATION: Gene expression is dependent on two main types of signals; one involving transcription factors which initiates gene transcription, and another which regulates the translation of a nascent mRNA. These post-transcriptional events play an important yet incompletely understood role in regulating gene expression and cellular behavior. Many of the identified cis acting elements for translational regulation occur within the 3'untranslated region (3' UTR), and some have been observed to occur with surprising regularity within certain protein function classes. RESULTS: In this study, we present a new association rule mining method for discovering nucleotide sequence patterns that appear in more sequences than expected within protein function classes. The method is applied to a database of human 3' UTR sequences, and some significant associations between nucleotide patterns and protein function classes are discovered. Among previously identified patterns, the AU-Rich Element (ARE) is found here to occur within the 3' UTR of cytokines, providing statistical validation of an association often reported in the literature. The method has also identified some GC-rich patterns, found to occur within the 3' UTR of homeodomain transcription factors and nuclear proteins. The method should be applicable to many types of regulatory element discovery.

3' Untranslated Regions↗

PubMed2002

Structure motif discovery and mining the PDB.

MOTIVATION: Many of the most interesting functional and evolutionary relationships among proteins are so ancient that they cannot be reliably detected through sequence analysis and are apparent only through a comparison of the tertiary structures. The conserved features can often be described as structural motifs consisting of a few single residues or Secondary Structure (SS) elements. Confidence in such motifs is greatly boosted when they are found in more than a pair of proteins. RESULTS: We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the protein's backbone that come close together in the structure and whose spatial conformations are similar. The residues in a pattern need not be close in the protein's sequence. The work described in this paper builds on an earlier reported algorithm for motif discovery. This paper describes a significant improvement of the algorithm which makes it very efficient. The improved efficiency allows us to use it for doing unsupervised learning of patterns occurring in small subsets in a large set of structures, a non-redundant subset of the Protein Data Bank (PDB) database of all known protein structures.

Algorithms↗