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PubMed1989

Loci for act recall: contextual influence on the processing of action events.

A problem-solving account of act memory predicts stronger impacts of context than theories that explain act memory by reference to automatic processing or by reference to the operation of modality-specific code systems. This prediction was tested in three experiments, all using the loci memotechnique to provide contexts for memorization of subject-performed tasks (SPTs). The results of the three experiments did not provide unambiguous evidence for or against any of the rival theories. Most consistent, however, was the observation that memory under motor-encoding conditions profits less on contexts than memory under nonmotor-encoding conditions, a finding which by itself lends more support to a multicode than to a problem-solving interpretation.

Adolescent↗
PubMed1992

Nucleotide sequence of the complementary DNA for human Pit-1/GHF-1.

Human cDNA clones encoding Pit-1/GHF-1, a pituitary-specific DNA binding factor, were obtained by PCR following reverse transcription of human pituitary RNA. It is approx. 1.3 kb in size with 0.1 kb 5' non-coding region, 0.9 kb protein-coding region and 0.3 kb 3' non-coding region. The predicted human Pit-1/GHF-1 peptide structure has 291 amino acids and is highly conserved among mouse, rat and bovine. In addition, the 5' non-coding region is highly conserved with rat pit-1/GHF-1 sequence to the transcription start site.

Amino Acid Sequence↗
PubMed2025

NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction.

Once a suitable reference sequence has been generated, intra-species variation is often assessed by re-sequencing. Variant calling processes can reveal all differences between strains, accessions, genotypes, or individuals. These variants can be enriched with predictions about their functional implications based on available structural annotations, i.e., gene models. Although these functional impact predictions on a per-variant basis are often accurate, some challenging cases require the simultaneous incorporation of multiple adjacent variants into this prediction process. Examples include neighboring variants which modify each other's functional impact. The Neighborhood-Aware Variant Impact Predictor (NAVIP) considers all variants within a given protein coding sequence when predicting the effect. As a proof of concept, variants between the Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1 were annotated. NAVIP is freely available on GitHub (https://github.com/bpucker/NAVIP) and accessible through a web server (https://pbb-tools.de).

Arabidopsis↗
PubMedDate not supplied

[Prediction of protein conformation using a doublet code method].

It is suggested that regions of irregular structure, beta-structure, and alpha-helix are composed of 2, 3, and 5 amino acid residue long elements (structurons), respectively, and that the structurons are encoded solely by residue pairs (doublet codons) (i, i + 1), (i, i + 2), (i, i + 4), respectively. Tables of codons are obtained by statistical analysis of the data on the distribution of these pairs in available secondary structures of 62 proteins. These tables are used to obtain distributions of t-, beta- and alpha-codons for an amino acid sequence of protein. When codons of different structures superpose, that is, include the same sequence regions, selection is performed, the selection being performed so to obtain as much as possible number of the non-superposed codons of different structures. The distributions of structurons obtained after this selection are used for localization of structurons in the sequence and prediction of secondary structure on the basis of this localization. The prediction method is illustrated. An accuracy of the method has been tested on the basis an casual selection of fifteen proteins and found equal 64% for secondary structure on the whole and 79%, 53%, 61% for alpha-helix, beta-structure and coil respectively. This result is similar or better than that communicated for contemporary methods.

Amino Acid Sequence↗
PubMed1992

Expression of the protease gene of equine infectious anemia virus in Escherichia coli: formation of the mature processed enzyme and specific cleavage of the gag precursor.

A 620-bp Bg/II restriction fragment containing the putative protease coding sequence from equine infectious anemia virus (EIAV) proviral DNA was cloned and expressed in E. coli as a Pol precursor protein. In contrast to the 25-kDa fusion protein predicted from the expressed pol sequence, a protein of approximately 10 kDa was generated by apparent autocatalytic processing of the Pol precursor. This mature processed protein was detected in transformed cells using an antisera raised against synthetic peptide from the conserved carboxyl-terminal segment of the predicted EIAV protease coding sequence. Coexpression of this protein with a 35-kDa EIAV Gag-precursor fusion protein resulted in the specific proteolytic processing of the precursor as shown by formation of p26, the major capsid protein of EIAV.

Cloning, Molecular↗
PubMed1989

Chicken protamine genes are intronless. The complete genomic sequence and organization of the two loci.

A positive cosmid clone obtained from a pwe15-rooster DNA library using a chicken protamine cDNA probe reveals the complete sequence of the two loci for the rooster protamine genes. The organization of these two loci within the cosmid clone matches that of genomic DNA. The copy number per haploid genome is two. The sequence for the rooster protamine predicted from the coding region shows differences from that previously determined at the protein level (Nakano, M., Tobita, T., and Ando, T. (1976) Int. J. Peptide Protein Res. 8, 565-578). A recent re-determination of the rooster protamine amino acid sequence (28 residues from the N terminus) matches that predicted from the genome rather than the sequence of Nakano et al. (1976). Both loci are intronless and the gene is extremely GC-rich (88% in the coding region). The 5' region of the gene contains a typical TATAAA box, several CG boxes, as well as other characteristic motifs. The 3' region of the gene contains the polyadenylation signal and several GT repeats of known Z-DNA forming potential. A correlation between the functional map of the gene and the tendency of the DNA to bend or to adopt the Z-conformation is presented and possible roles for these conformations in the transcription of this gene are discussed.

Amino Acid Sequence↗
PubMed1991

Identification of a gene encoding the predicted ribosomal protein L7b divergently transcribed from POL1 in fission yeast Schizosaccharomyces pombe.

A 0.85 Kb RNA molecule is transcribed in the region upstream from the 5'-end of the S. pombe POL1 gene encoding the catalytic subunit of DNA polymerase alpha. The nucleotide sequence of the DNA region hybridizing with the 0.85 Kb transcript allowed us to identify an open reading frame coding for a predicted peptide which shows 50% identity with the rat ribosomal protein L7 and which is transcribed divergently from POL1. We have named this gene RPL7b because of the existence in S. pombe of a different sequence, named RPL7, which also codes for a putative protein showing homology with the rat ribosomal protein L7. The RPL7b gene includes a 291 bp-long intron containing the sequences necessary for intron excision and RNA splicing in S. pombe. The precise location of the intron was established by amplification and sequencing of a partial cDNA copy of the mRNA, whereas the initiation site of transcription was determined by reverse transcription of the 5' region of the mRNA. The 320 bp separating the starting methionine codons of RPL7b and POL1 genes should contain the signals necessary for their divergent transcription and regulation. The sequence 5'-AAGACAGTCACA-3', whose primary structure is homologous to a conserved block present in the 5'-untranscribed regions of other S. pombe genes of ribosomal proteins, is located about 50 bp upstream the transcription initiation site of RPL7b.

Amino Acid Sequence↗
PubMed1988

Rate coding model for discrimination of simple tones in the presence of noise.

The predictions of a rate coding model for frequency and amplitude jnd's in the presence of noise are presented for a 1-kHz, 100-ms tone. The model for the neural response incorporates physiological data on dynamic range distribution and rate suppression. A central processor is assumed to estimate the tone frequency, or amplitude, from the tone-evoked rate increment profile. This central processor acts like an ideal detector with respect to the neural noise. The effects of the neural noise as well as the signal variability on the discrimination performance level are evaluated, and the signal variability is found to be significant. The combined effect of threshold distribution, rate suppression, and signal variability make the jnd's practically invariant with noise level, in accordance with published psychophysical data. The values of the frequency jnd at high signal-to-noise ratio, however, are borderline in their consistency with the data. A more obvious discrepancy exists between the model and the psychophysical data regarding the ratio of frequency to amplitude Weber fractions, which can be resolved only by modifying the model auditory filters to be five times sharper than those measured in cats.

Acoustic Stimulation↗
PubMed1980

The nucleotide sequence of adenovirus type 5 early region E1: the region between map positions 8.0 (HindIII site) and 11.8 (SmaI site).

The nucleotide sequence of the region between map positions 8.0 (HindIII site) and 11.8 (SmaI site) of adenovirus type 5 (Ad5) has been determined. Together with the sequences reported earlier (Van Ormondt et al., 1978; Maat and Van Ormondt, 1979) it encompasses the entire leftmost early region E1 of Ad5 DNA (4126 base pairs). The total sequence revealed a number of potential regulatory signals (promoter sites, ribosome binding sites, 3'-poly(A)-associated sequences), which confirm that region E1 is divided into subregions, E1a and E1b, and a region coding for semi-late viral protein IX. By taking into account the adenovirus 2 (Ad2) RNA-splicing data of Perricaudet et al. (1979; 1980) and the Ad2 RNA mapping data of Chow et al. (1979) we predict that E1a codes for polypeptides of 32, 26 and ca. 13 kd, and subregion E1b for polypeptides of 67 kd and 20 kd; the expected molecular weight of protein IX is 14.4 kd.

Adenoviruses, Human↗
PubMed1992

Color vision in honeybees.

Theoretical and experimental investigations of the color vision system in honeybees are reviewed. Grassmann's model and receptor models of color vision are discussed with respect to the problem of color difference. A recent analysis of the bee's color opponent coding system is presented in brief. Predictions for the spectral sensitivity of color opponent coding neurons derived directly from the color opponent coding (COC) model and predictions for the Bezold-Brücke color shift and the spectral discrimination function derived from the model via color difference formula are presented. The predictions are compared with electrophysiological data and with choice proportions of behavioral experiments, respectively.

Animals↗
PubMed1982

Recognition of protein coding regions in DNA sequences.

We give a test for protein coding regions which is based on simple and universal differences between protein-coding and noncoding DNA. The test is simple enough to use without a computer and is completely objective. The test has been thoroughly proven on 400,000 bases of sequence data: it misclassifies 5% of the regions tested and gives an answer of "No Opinion" one fifth of the time. We predict some new coding and noncoding regions in published sequences.

Computers↗
PubMed1992

Cloning of a complementary DNA coding for the 100-kD antigenic protein of the PM-Scl autoantigen.

Anti-PM-Scl antibodies are associated with polymyositis-scleroderma overlap or either disease alone. Among sera from 39 patients with anti-PM-Scl, 23 recognized the 100-kD band in immunoblot against HeLa cell extract, 16 of which also stained the 70-kD band. A human thymocyte lambda gt11 cDNA expression library was screened with anti-PM-Scl serum, and two clones were identified whose products reacted with 33 and 37 of 39 anti-PM-Scl sera, respectively, but none of 26 negative control sera. Affinity-purified antibody reacting specifically with plaques of the clone stained the 100-kD band on immunoblot, reacted with nucleoli of HEp-2 cells, and immunoprecipitated the PM-Scl protein complex. Partial sequences of both inserts were identical. One insert was fully sequenced, and additional 5' and 3' sequence was obtained using a gene-specific primer to form a cDNA with HeLa cell RNA as template followed by PCR. The complete nucleotide sequence included 2,739-bp coding for a predicted full-length protein of 98,088 D. There was no homology with the PM-Scl 75-kD protein and no significant homology with other proteins. A mixed-charge cluster was identified, with 22 charged amino acids of 37. In conclusion, the full-length cDNA sequence was determined coding for the PM-Scl 100-kD protein, the most commonly antigenic protein of the PM-Scl complex.

Amino Acid Sequence↗
PubMed1990

Generation of diversity in nonerythroid spectrins. Multiple polypeptides are predicted by sequence analysis of cDNAs encompassing the coding region of human nonerythroid alpha-spectrin.

Nonerythroid alpha-spectrin (alpha-fodrin) is a major component of the membrane skeleton in diverse cell types. Overlapping cDNAs have been isolated which encompass the coding region of human lung fibroblast nonerythroid alpha-spectrin. The composite sequence of 7,787 nucleotides encodes a polypeptide of 2,472 amino acids (predicted Mr of 283,964). This sequence has 58% amino acid identity with human erythroid alpha-spectrin, which is encoded on a different gene, and 96% amino acid identity with the full-length sequence of chicken brain alpha-spectrin. We previously reported the variable expression in human fibroblast alpha-spectrin of 20 amino acids between repeats 10 and 11 (McMahon, A. P., Giebelhaus, D. H., Champion, J. E., Bailes, J. A., Lacey, S., Carritt, B., Henchman, S. K., and Moon, R. T. (1987) Differentiation 34, 68-78). In this study, we report additional heterogeneity in fibroblast alpha-spectrin near the carboxyl-terminal end. One of the fibroblast cDNAs (clone 3D) has an in-frame deletion of 18 nucleotides within spectrin repeat 21 when compared to an overlapping fibroblast cDNA (clone 7). As this heterogeneity in amino acid sequence occurs near domains of nonerythroid alpha-spectrin suggested to bind calcium or actin, it is possible that fibroblasts express functionally distinct isoforms of nonerythroid alpha-spectrin.

Amino Acid Sequence↗
PubMed1987

Structure and expression of the murine L-myc gene.

We have isolated a 12 kb clone from the murine genome which we show by DNA transfection studies to contain an entire functional L-myc gene and the transcriptional promoter sequences necessary for its expression. We have also isolated a 3.1 kb cDNA sequence from a murine brain cDNA library which corresponds to most of the L-myc mRNA. We have identified the L-myc coding region within the genomic clone by a combination of S1 nuclease analyses. Northern blotting analyses and comparative nucleotide sequence analyses with the cDNA clone. The L-myc gene appears to be organized similarly to the other well-characterized myc-family genes, c-myc and N-myc. The predicted amino acid coding sequence of the L-myc gene indicates that the L-myc protein is significantly smaller than c- and N-myc, but is highly related. In particular, comparison of the N- and c-myc protein sequences reveals seven relatively conserved regions interspersed among non-conserved regions; the L-myc gene retains five of these conserved regions but lacks two others. In addition, a portion of one highly conserved region is encoded within a different region of the L-myc gene but, due to changes in the size of L-myc exons relative to those of N- and c-myc, maintains its overall position in the peptide backbone with respect to other conserved regions. We discuss these findings in the context of potential functional domains and the possibility of overlapping and distinct activities of myc-family proteins.

Amino Acid Sequence↗
PubMed1986

Partial nucleotide sequence of the Murray Valley encephalitis virus genome. Comparison of the encoded polypeptides with yellow fever virus structural and non-structural proteins.

The sequence of 5400 bases corresponding to the 5'-terminal half of the Murray Valley encephalitis virus genome has been determined. The genome contains a 5' non-coding region of about 97 nucleotides, followed by a single continuous open reading frame that encodes the structural proteins followed by the non-structural proteins. Amino acid sequence homology between the Murray Valley encephalitis and yellow fever (Rice et al., 1985) polyproteins is 42% over the region sequenced. The start points of the various Murray Valley encephalitis virus-coded proteins have been assigned on the basis of this homology and a consistent set of potential proteolytic cleavage sites identified, the sequences of which are similar in Murray Valley encephalitis and yellow fever. The deduced Murray Valley encephalitis gene order is 5'-C-prM (M)-E-NS1-ns2a-ns2b-NS3-3'. The genome organization of Murray Valley encephalitis and yellow fever appears to be identical and the sizes of the predicted virus-coded proteins similar between the two viruses. Both viruses encode a basic capsid protein followed by three glycoproteins; the glycoproteins appear to have the conventional topology of N terminus outside with a C-terminal membrane-spanning domain. There are conserved glycosylation sites in prM, the precursor to the M protein of the virion, and in NS1, a non-structural protein of uncertain function. The glycosylation sites in E, the major envelope protein of the virion, are not conserved as to position. We predict the existence, in flavivirus-infected cells, of two small, hydrophobic peptides, ns2a and ns2b, which show only limited amino acid sequence homology. Finally, about half of the amino acid sequence of NS3 has been obtained; NS3 is a hydrophilic non-structural protein that shows 55% amino acid sequence similarity between Murray Valley encephalitis and yellow fever over the region sequenced and is probably involved in RNA replication.

Amino Acid Sequence↗
PubMed1989

Complementary DNA cloning of a protein highly homologous to mammalian sarcoplasmic reticulum Ca-ATPase from the crustacean Artemia.

Complementary DNA clones coding for an Artemia ATPase have been isolated using an oligonucleotide probe for a region highly conserved between P-type ATPases. The nucleotide sequence of three overlapping clones, 3309 base-pairs, has been established. This sequence includes 78 nucleotides of 5' untranslated sequence, an open reading frame of 3009 nucleotides and 222 nucleotides of 3' untranslated sequences. The amino acid sequence predicted for the coding region is 71% similar to that of slow and fast twitch rabbit muscle sarcoplasmic reticulum Ca-ATPases. The homology is specially high in some regions of the protein that include the previously described regions that are similar between all known P-type ATPases, as well as transmembrane domains and intra- and extracellular domains adjacent to the membrane that are not conserved in P-type ATPases but have been proposed to be involved in calcium binding and transport in rabbit sarcoplasmic reticulum Ca-ATPases. Probes of this likely sarcoplasmic reticulum Ca-ATPase hybridize to two mRNAs of 5200 and 4500 bases. Although both mRNAs are already present in cryptobiotic embryos, the levels of the 5200 base mRNA decrease after development is reassumed, being undetectable after hatching of the nauplii. The levels of the 4500 base mRNA increase during development; maximal levels are reached by ten hours and are maintained at later stages of development.

Amino Acid Sequence↗
PubMed1977

Cytotoxic T lymphocytes induced against allogeneic I-region determinants react with Ia molecules on trinitrophenyl-conjugated syngeneic target cells.

The major histocompatibility complex codes for determinants which are recognized by and serve as targets for cytolytic T lymphocytes (CTL) (1). Antigens coded for by the K and D loci of the H-2 complex can activate xenogeneic or allogeneic CTL (2,3). In addition, the H-2K or H-2D gene products function as those molecules against which syngeneic CTL responses specific for chemical, viral, and minor H antigens are directed (4-8). It has recently been shown that Ia determinants can also serve as target antigens for distinct but weaker CTL responses (9-13). Those clones which recognize Ia antigens see them independently of K- or D- coded antigens as shown in genetic studies and by antisera-blocking experiments (12,13). We have proposed that the existence of clones of CTL specific for I-region-coded determinants is not fortuitous; rather these clones specifically recognize Ia determinants and may have an immunoregulatory role. These CTL may affect those immune functions which are at least partially dependent on or controlled by I-region-coded molecules. Two predictions can be made and tested concerning the role of Ia determinants in cytolytic systems and the role, if any, of I-region- specific CTL in regulating the immune response: (a) that if as we and others have shown, certain Ia specificities can serve as a third series of major histocompatibility antigens, then Ia antigens should be susceptible to the same types of antigenic modifications as H-2K- or H-2D-coded structures and thus serve as targets for CTL directed against modified-self in selected systems; and (b) that allogeneically induced I-region-specific CTL should demonstrate cross-reactivity with targets bearing modified syngeneic I-region-coded determinants. Data will be present which demonstrates that trinitrophenyl (TNP)-modified syngeneic I-region determinants can serve as targets for CTL induced by allogeneic Ia antigens.

Animals↗
PubMed2026

hypeR-GEM: connecting metabolite signatures to enzyme-coding genes via genome-scale metabolic models.

MOTIVATION: Enrichment analysis is a cornerstone of "omics" data interpretation, enabling researchers to connect analysis results to biological processes and generate testable hypotheses. Enrichment analysis in metabolomics poses distinct challenges for interpretation and multi-omics integration due to the lack of well-defined and consistent connections to well-curated gene-centered biological knowledge repositories. To address these challenges, we developed hypeR-GEM, a methodology and associated R package that adapts gene set enrichment analysis to metabolomics. hypeR-GEM leverages genome-scale metabolic models (GEMs) to infer reaction-based links between metabolites and enzyme-coding genes, enabling the mapping of metabolite signatures to gene signatures and their subsequent annotation via gene set enrichment analysis. RESULTS: We validated hypeR-GEM using paired metabolomics-proteomics and metabolomics-transcriptomics datasets by assessing whether genes mapped from metabolites significantly overlapped with differentially expressed proteins or transcripts. We further evaluated whether pathways enriched via hypeR-GEM-mapped genes corresponded to those derived from paired proteomic or transcriptomic data. In most datasets analyzed, both the predicted enzyme-coding genes and the associated enriched pathways showed significant concordance with independently derived omics signatures, supporting the utility and robustness of hypeR-GEM. Finally, we applied hypeR-GEM to the analysis of age-associated metabolic signatures from the New England Centenarian Study. The results revealed consistent enrichment of lipid-related pathways, aligning with the well-established role of lipid metabolism in aging, and highlighted additional pathways not captured in the metabolites' annotation, demonstrating hypeR-GEM's practical utility in a real-world use case. AVAILABILITY AND IMPLEMENTATION: The hypeR-GEM R package, documentation, and workflow examples are freely available at https://github.com/montilab/hypeR-GEM and archived at https://doi.org/10.5281/zenodo.20586748.

Metabolomics↗