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PubMed1990

Purification, biological properties and partial sequence analysis of 67-kDa calcimedin and its 34-kDa fragment from chicken gizzard.

Calcimedin is a group of proteins, originally isolated from chicken gizzard, which are able to bind to several hydrophobic matrices in the presence of Ca2+. Although the molecular properties have been partially discovered, the physiological functions of calcimedins have not yet been clearly defined. In this study, we describe the isolation and characterization of 67-kDa calcimedin and its 34-kDa fragment from chicken gizzard. Both structural and functional studies establish that 67-kDa calcimedin is a member of the calpactin/lipocortin family: it displays phospholipase A2 inhibitory activity, Ca2(+)-dependent F-actin binding and phospholipid binding activity similar to those of calpactins (lipocortins). By comparing the sequence of 67-kDa calcimedin with the predicted sequence of 67-kDa calelectrin, we concluded that the primary structure of these 67-kDa proteins is highly conserved. In particular, the sequences GLGTDEGAIIXVLTQR and EGAGTDESTLIEIMATR conform with the annexin consensus sequence which is characteristic of the calpactin/lipocortin family. A 34-kDa fragment of 67-kDa calcimedin was also purified and their relatedness has been confirmed by antibody cross-reactivity. The sequence data further support that the 34-kDa fragment is derived from the C-terminal portion of 67-kDa calcimedin by limited proteolysis. The 34-kDa fragment, which contains the annexin consensus sequence, preserves the phospholipase A2 inhibitory activity, and binds F-actin and phospholipids.

Actins↗
PubMed1991

Biologic properties and nucleotide sequence analysis of human papillomavirus type 51.

Human papillomaviruses (HPVs) may be grouped according to the site from which they are isolated and the disease with which they are associated. We recently identified and cloned HPV type 51 (HPV-51) from a low-grade precancerous lesion (G. Nuovo, E. DeVilliers, R. Levine, S. Silverstein, and C. Crum. J. Virol. 62:1452-1455, 1988). Molecular epidemiologic analysis of cervical lesions, including condylomata and low- and high-grade precancers, revealed that HPV-51 was present in about 5% of the samples we examined. We have now determined the complete nucleotide sequence of this virus and compared it with other sequenced HPVs. Our analysis reveals that the 7,808-bp genome is composed of eight open reading frames which are encoded on the same strand and that this virus is most closely related to HPV-31. Sequence comparisons place this virus in the group of high-risk viruses (those with an increased risk of progressing to malignancy) along with HPV-16, -18, -31, and -33. Morphologic transformation experiments demonstrated that HPV-51 had transformation potential and that transformed cells contained RNAs homologous to E6 and E7.

Amino Acid Sequence↗
PubMed2004

Bioinformatics in reproductive biology--functional annotation based on comparative sequence analysis.

Recent studies of the genomes of a variety of model organisms have provided an unprecedented opportunity to identify and characterize all signaling molecules in the human genome. Regardless of the approaches used to decipher gene characteristics and their role in physiology, pairwise sequence comparison represents the fundamental bioinformatic tool for initial functional annotation of newly identified genes. Because genes evolved from duplication and adapted to different evolutionary niches for each organism during speciation, detailed sequence analysis could provide additional information on the biochemical and biological characteristics of novel genes. In addition, the integration of sequence-based gene discovery with phylogeny-based function prediction leads to a more complete understanding of the signaling pathways. For example, detailed pairwise sequence analysis has led to the identification of (1) stresscopin (SCP) and stresscopin-related peptides (SRP) as the CRH-related genes, (2) multiple relaxin-like factor genes, and (3) the novel glycoprotein hormone subunit family genes, alpha2 and beta5. Furthermore, based on the understanding that ligands and receptors coevolved during evolution, we have identified a variety of novel extracellular signaling polypeptides including (1) stresscopin and stresscopin-related peptides as selective ligands for the type 2 CRH receptor, (2) the pregnancy hormone, relaxin, and related peptides that activate two orphan G protein-coupled receptors (GPCRs), LGR7 and LGR8, and (3) alpha2 and beta5 that form a heterodimer capable of activating the TSH receptor. Thus, detailed studies on the characteristics and evolution of gene sequences have provided an inroad to the elucidation of novel signaling polypeptides and the associated signal transduction pathways.

Animals↗
PubMed1978

Isolation and partial characterization of the allergen in mountain cedar pollen.

A biologically active fraction from a crude extract of mountain cedar pollen has been purified and partially chemically characterized. An ammonium bicarbonate extract of commercial defatted pollen was fractionated by G-100 Sephadex chromatography and the biologically active fraction was found to be homogeneous by polyacrylamide gel electrophoresis and N-terminal amino acid sequence analysis. The biologically active component is a 50,000 dalton protein whose N-terminal amino acid sequence is Asp--Asn--Pro--Ile--Asp. These findings provide a further purified pollen allergen for immunologic studies and the first such purified allergen having clinical significance in a limited geographic region.

Allergens↗
PubMed2025

De novo clustering of large long-read transcriptome datasets with isONclust3.

MOTIVATION: Long-read sequencing techniques can sequence transcripts from end to end, greatly improving our ability to study the transcription process. Although there are several well-established tools for long-read transcriptome analysis, most are reference-based. This limits the analysis of organisms without high-quality reference genomes and samples or genes with high variability (e.g. cancer samples or some gene families). In such settings, analysis using a reference-free method is favorable. The computational problem of clustering long reads by region of common origin is well-established for reference-free transcriptome analysis pipelines. Such clustering enables large datasets to be split roughly by gene family and, therefore, an independent analysis of each cluster. There exist tools for this. However, none of those tools can efficiently process the large amount of reads that are now generated by long-read sequencing technologies. RESULTS: We present isONclust3, an improved algorithm over isONclust and isONclust2, to cluster massive long-read transcriptome datasets into gene families. Like isONclust, isONclust3 represents each cluster with a set of minimizers. However, unlike other approaches, isONclust3 dynamically updates the cluster representation during clustering by adding high-confidence minimizers from new reads assigned to the cluster and employs an iterative cluster-merging step. We show that isONclust3 yields results with higher or comparable quality to state-of-the-art algorithms but is 10-100 times faster on large datasets. Also, using a 256 Gb computing node, isONclust3 was the only tool that could cluster 37 million PacBio reads, which is a typical throughput of the recent PacBio Revio sequencing machine. AVAILABILITY AND IMPLEMENTATION: https://github.com/aljpetri/isONclust3.

Algorithms↗
PubMed2026

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗
PubMed2006

Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods.

Prediction of the biological effect of missense substitutions has become important because they are often observed in known or candidate disease susceptibility genes. In this paper, we carried out a 3-step analysis of 1514 missense substitutions in the DNA-binding domain (DBD) of TP53, the most frequently mutated gene in human cancers. First, we calculated two types of conservation scores based on a TP53 multiple sequence alignment (MSA) for each substitution: (i) Grantham Variation (GV), which measures the degree of biochemical variation among amino acids found at a given position in the MSA; (ii) Grantham Deviation (GD), which reflects the 'biochemical distance' of the mutant amino acid from the observed amino acid at a particular position (given by GV). Second, we used a method that combines GV and GD scores, Align-GVGD, to predict the transactivation activity of each missense substitution. We compared our predictions against experimentally measured transactivation activity (yeast assays) to evaluate their accuracy. Finally, the prediction results were compared with those obtained by the program Sorting Intolerant from Tolerant (SIFT) and Dayhoff's classification. Our predictions yielded high prediction accuracy for mutants showing a loss of transactivation ( approximately 88% specificity) with lower prediction accuracy for mutants with transactivation similar to that of the wild-type (67.9 to 71.2% sensitivity). Align-GVGD results were comparable to SIFT (88.3 to 90.6% and 67.4 to 70.3% specificity and sensitivity, respectively) and outperformed Dayhoff's classification (80 and 40.9% specificity and sensitivity, respectively). These results further demonstrate the utility of the Align-GVGD method, which was previously applied to BRCA1. Align-GVGD is available online at http://agvgd.iarc.fr.

Amino Acid Sequence↗
PubMed2007

Expressed sequence tags-based identification of genes in the biocontrol agent Chaetomium cupreum.

Chaetomium cupreum has a potential as biocontrol agent against a range of plant pathogens on the basis of production of antifungal metabolites, mycoparasitism, competition for space and nutrients, or various combinations of these. To explore genes expressed in C. cupreum, a cDNA library was constructed from mycelium and 3,066 expressed sequence tags (ESTs) were generated. Clusters analysis enabled the identification of 1,471 unigenes with 392 contigs and 1,079 singleton sequences. Putative functions were assigned to 874 unigenes that exhibited strong similarity to genes/ESTs in public databases putatively containing genes involved in cellular component, molecular function, and biological process. Other 597 ESTs representing novel genes showed no significant similarity to public database resource of NCBI. A proportion of genes was identified related to degradation of pathogen cell wall, antifungal metabolite production, as was estimated in the biocontrol fungus. The paper described is a first step towards the knowledge of the C. cupreum genome. The results present the useful application of EST analysis on C. cupreum and provide a preliminary indication of gene expression putatively involved in biocontrol.

Chaetomium↗
PubMed1995

Analysis of tRNA gene sequences by neural network.

The quantitative similarity among tRNA gene sequences was acquired by analysis with an artificial neural network. The evolutionary relationship derived from our results was consistent with those from other methods. A new sequence was recognized to be a tRNA-like gene by a neural network on the analysis of similarity. All of our results showed the efficiency of the artificial neural network method in the sequence analysis for biological molecules.

Animals↗
PubMed2004

Molecular characterization and phylogenetic study of newcastle disease virus isolates from recent outbreaks in eastern Uganda.

Newcastle disease virus isolates from chickens in eastern Uganda in 2001 were found to be velogenic by fusion protein cleavage site sequence analysis and biological characterization; the intracerebral pathogenicity index was 1.8. Analysis of their hemagglutinin-neuraminidase protein gene sequences revealed a novel genotype unrelated to those that caused previous outbreaks.

Amino Acid Sequence↗
PubMed2025

LINNAEUS: Simultaneous Single-Cell Lineage Tracing and Cell Type Identification.

A key goal of biology is to understand the origin of the many cell types that can be observed during diverse processes such as development, regeneration, and disease. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ. However, organizing the resulting taxonomy of cell types into lineage trees to understand the origins of cell states and relationships between cells remains challenging. Here we present LINNAEUS (Spanjaard et al, Nat Biotechnol 36:469-473. https://doi.org/10.1038/nbt.4124 , 2018; Hu et al, Nat Genet 54:1227-1237. https://doi.org/10.1038/s41588-022-01129-5 , 2022) (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences)-a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, LINNAEUS can be used to reconstruct organism-wide single-cell lineage trees. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Single-Cell Analysis↗
PubMed2006

High performance computing in biology: multimillion atom simulations of nanoscale systems.

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nano-scale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail.

Computational Biology↗
PubMed1993

Review: molecular biology of transgenic animals.

The amazing pace of discovery within the field of molecular biology has expanded the understanding of as well as the potential for genetic engineering in laboratory and domestic animals. Recently, specific techniques have been perfected, including recombinant DNA, genetic cloning, analysis of gene expression, and the sequencing of nucleic acids and proteins. These molecular techniques combined with methods allowing transfer of the recombinant genes into living cells and fertilized eggs advent the production of transgenic mice and other animals, the application of which is unlimited.

Animals↗
PubMed2004

Rapid and sensitive dot-matrix methods for genome analysis.

MOTIVATION: Dot-matrix plots are widely used for similarity analysis of biological sequences. Many algorithms and computer software tools have been developed for this purpose. Though some of these tools have been reported to handle sequences of a few 100 kb, analysis of genome sequences with a length of >10 Mb on a microcomputer is still impractical due to long execution time and computer memory requirement. RESULTS: Two dot-matrix comparison methods have been developed for analysis of large sequences. The methods initially locate similarity regions between two sequences using a fast word search algorithm, followed with an explicit comparison on these regions. Since the initial screening removes most of random matches, the computing time is substantially reduced. The methods produce high quality dot-matrix plots with low background noise. Space requirements are linear, so the algorithms can be used for comparison of genome size sequences. Computing speed may be affected by highly repetitive sequence structures of eukaryote genomes. A dot-matrix plot of Yeast genome (12 Mb) with both strands was generated in 80 s with a 1 GHz personal computer.

Algorithms↗
PubMed2004

Vector NTI, a balanced all-in-one sequence analysis suite.

Vector NTI is a well-balanced desktop application integrated for molecular sequence analysis and biological data management. It has a centralised database and five application modules: Vector NTI, AlignX, BioAnnotator, ContigExpress and GenomBench. In this review, the features and functions available in this software are examined. These include database management, primer design, virtual cloning, alignments, sequence assembly, 3D molecular viewer and internet tools. Some problems encountered when using this software are also discussed. It is hoped that this review will introduce this software to more molecular biologists so they can make better-informed decisions when choosing computational tools to facilitate their everyday laboratory work. This tool can save time and enhance analysis but it requires some learning on the user's part and there are some issues that need to be addressed by the developer.

Algorithms↗
PubMed2005

The use and implications of ribosomal DNA sequencing for the discrimination of digenean species.

In just over a decade, the use of molecular approaches for the recognition of parasites has become commonplace. For trematodes, the internal transcribed spacer region of ribosomal DNA (ITS rDNA) has become the default region of choice. Here, we review the findings of 63 studies that report ITS rDNA sequence data for about 155 digenean species from 19 families, and then review the levels of variation that have been reported and how the variation has been interpreted. Overall, complete ITS sequences (or ITS1 or ITS2 regions alone) usually distinguish trematode species clearly, including combinations for which morphology gives ambiguous results. Closely related species may have few base differences and in at least one convincing case the ITS2 sequences of two "good" species are identical. In some cases, the ITS1 region gives greater resolution than the ITS2 because of the presence of variable repeat units that are generally lacking in the ITS2. Intraspecific variation is usually low and frequently apparently absent. Information on geographical variation of digeneans is limited but at least some of the reported variation probably reflects the presence of multiple species. Despite the accepted dogma that concerted evolution makes the individual representative of the entire species, a significant number of studies have reported at least some intraspecific variation. The significance of such variation is difficult to assess a posteriori, but it seems likely that identification and sequencing errors account for some of it and failure to recognise separate species may also be significant. Some reported variation clearly requires further analysis. The use of a "yardstick" to determine when separate species should be recognised is flawed. Instead, we argue that consistent genetic differences that are associated with consistent morphological or biological traits should be considered the marker for separate species. We propose a generalised approach to the use of rDNA to distinguish trematode species.

Animals↗
PubMed1997

Computational and biological analysis of 680 kb of DNA sequence from the human 5q31 cytokine gene cluster region.

With the human genome project advancing into what will be a 7- to 10-year DNA sequencing phase, we are presented with the challenge of developing strategies to convert genomic sequence data, as they become available, into biologically meaningful information. We have analyzed 680 kb of noncontiguous DNA sequence from a 1-Mb region of human chromosome 5q31, coupling computational analysis with gene expression studies of tissues isolated from humans as well as from mice containing human YAC transgenes. This genomic interval has been noted previously for containing the cytokine gene cluster and a quantitative trait locus associated with inflammatory diseases. Our analysis identified and verified expression of 16 new genes, as well as 7 previously known genes. Of the total of 23 genes in this region, 78% had similarity matches to sequences in protein databases and 83% had exact expressed sequence tag (EST) database matches. Comparative mapping studies of eight of the new human genes discovered in the 5q31 region revealed that all are located in the syntenic region of mouse chromosome 11q. Our analysis demonstrates an approach for examining human sequence as it is made available from large sequencing programs and has resulted in the discovery of several biomedically important genes, including a cyclin, a transcription factor that is homologous to an oncogene, a protein involved in DNA repair, and several new members of a family of transporter proteins.

Animals↗