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PubMed2006

Expression profiling of glycosyltransferases and related enzymes using gene microarrays.

Gene expression analysis has become a standard tool for studies of biological models of disease processes, growth, and development and has been used increasingly in the field of clinical research. The completion of the human genome sequence is now providing the glycomics research community with the tools to develop a synergism with related fields such as MS glycan profiling and proteomics. The use of microarray technology to measure changes in gene expression is a useful approach for the study of the expression profiles of glycosyltransferases, carbohydrate binding proteins, and related enzymes. The availability of standardized microarray platforms, high-quality reagents for sample preparation and hybridization, and image and statistical analysis tools has contributed to recent advances in the application of this technology to glycobiology. Most microarray experiments today are done within specialized core facilities equipped with instrumentation, software, and personnel with expertise in their application. The focus of this chapter is on aspects of microarray analysis common to all platforms and within the realm of the glycobiologist: consideration of experimental design issues and methods for the preparation of RNA samples from a variety of tissue sources suitable for microarray analysis.

Animals↗
PubMed2004

Reliability of t7-based mRNA linear amplification validated by gene expression analysis of human kidney cells using cDNA microarrays.

Genome wide gene expression analysis by cDNA microarrays is often limited by minute amounts of starting RNA. We therefore tested an optimized linear RNA amplification protocol using the RiboAmp amplification kit in the setting of cDNA microarrays. We isolated mRNA from a human kidney cell line (HK-2; ATCC) and from Universal Human Reference RNA (STR; Stratagene). After performing one and two rounds of linear RNA amplification, respectively, the amplified RNAs were co-hybridized to cDNA microarrays. Linearity and reproducibility of the individual experiments were then assessed by calculating the Pearson correlation. The intra-amplification consistency showed a correlation of 0.968 for the first round, 0.907 for the second round and 0.912 for two successive rounds of amplification. If the first round was compared to unamplified material, r was 0.925. The second round amplification yielded a correlation of 0.897 if compared to unamplified mRNA. Two rounds of amplification starting from 200 pg of mRNA compared to unamplified material resulted in a correlation of 0.868. These results indicate that linear amplification using RiboAmp kit yields amplified RNA with a high degree of linearity and reproducibility.

Cell Line↗
PubMed2025

Integrating RNA sequencing with deep learning-based metabolic toxicity prediction: A new perspective on screening prioritized liquid crystal monomers.

Nearly 99 % of liquid crystal monomers (LCMs) toxicological data remains gaps, especially to aquatic organisms. Herein, this study proposes a rapid and high-throughput screening method for identifying priority LCMs in natural water. Using six fluorinated LCMs (LCMsF) with significant enrichment characteristics in zebrafish as examples, RNA sequencing revealed that LCMsF-induced metabolic disturbances are predominant, including 28 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway abnormalities attributed to 498 differentially expressed genes. Notably, the intricate sequencing process resulted in the inability to rapid identify additional 857 LCMsF that may induce metabolic disturbances. To address this, LCMsT-MTP, a predictive deep learning model based on RNA sequencing, was developed. This model integrates a comprehensive representation of LCMsF structures and metabolic toxicity target sequences. LCMsT-MTP improves upon traditional methods that are limited to single targets and mechanisms by facilitating the simultaneous identification of 21 metabolic toxicities induced by LCMsF. In addition, the LCMsT-MTP model was further applied to non-fluorinated LCMs (LCMsNone F) that satisfy the applicability domains test. Accordingly, a metabolic toxicity priority list of LCMs was proposed, with ∼95 % of LCMs classified as high or medium risk. Priority list validation by molecular dynamics confirmed that the interactions of LCMsF/LCMsNone F and metabolic toxicity targets in representative KEGG pathways were distinct.

Animals↗
PubMed1997

A variant of Plasmodium ovale; analysis of its 18S ribosomal RNA gene sequence.

We report here a new variant of human malaria parasite found by comparison of diagnostic results obtained from a new DNA diagnostic method named microtiter plate-hybridization (MPH) and traditional microscopic method. Total five cases of malaria were diagnosed as microscopy-positive but MPH-negative; one case was found in epidemiological research in Vietnam and four cases were obtained from imported malaria in Japan. Although they were quite similar to typical P. ovale morphologically in microscopy, sequence analysis of PCR-amplified DNA fragment revealed that their 18S ribosomal RNA gene sequence was different from published sequence of P. ovale. Combination of MPH and microscopic examination provides us a new method for detection of a new type of malaria parasite which is difficult to distinguish morphologically.

Animals↗
PubMed2002

Sequence analysis of measles virus nucleocapsid transcripts in patients with Paget's disease.

It has been debated for almost 30 years whether Paget's disease of bone results from paramyxoviral infection of osteoclasts (OCs). Paramyxoviral-like nuclear inclusions are found in OCs from patients with Paget's disease, and measles virus (MV) or canine distemper virus (CDV) messenger RNA (mRNA) transcripts have been detected by in situ hybridization in bone cells from pagetic lesions. Furthermore, immunocytochemical studies have shown the presence of several paramyxoviral species in OCs from patients with Paget's disease. However, others have been unable to detect paramyxoviral transcripts in bone samples from patients with Paget's disease or marrow cultures from involved sites of patients with Paget's disease. Furthermore, no one has been able to isolate an infectious virus from pagetic bone samples or marrow cells from patients with Paget's disease, and a full-length viral gene has not been sequenced from pagetic samples. In this study, we have obtained the full-length sequence for the MV nucleocapsid (MVNP) gene in bone marrow from an involved site from a patient with Paget's disease and more than 700 base pairs (bps) of MVNP sequence in 3 other patients with Paget's disease. These sequences were undetectable in four normal marrow samples studied simultaneously. The sequences from the patients contained multiple mutations that differed from the Edmonston strain MVNP gene. These findings are consistent with the presence of a chronic MV infection in affected sites from these patients with Paget's disease.

Aged↗
PubMed2025

scPlantLLM: A Foundation Model for Exploring Single-cell Expression Atlases in Plants.

Single-cell RNA sequencing (scRNA-seq) provides unprecedented insights into plant cellular diversity by enabling high-resolution analyses of gene expression at the single-cell level. However, the complexity of scRNA-seq data, including challenges in batch integration, cell type annotation, and gene regulatory network (GRN) inference, demands advanced computational approaches. To address these challenges, we developed scPlantLLM, a Transformer model trained on millions of plant single-cell data points. Using a sequential pretraining strategy incorporating masked language modeling and cell type annotation tasks, scPlantLLM generates robust and interpretable single-cell data embeddings. When applied to Arabidopsis thaliana datasets, scPlantLLM excels in clustering, cell type annotation, and batch integration, achieving an accuracy of up to 0.91 in zero-shot learning scenarios. Furthermore, the model demonstrates an ability to identify biologically meaningful GRNs and subtle cellular subtypes, showcasing its potential to advance plant biology research. Compared to traditional methods, scPlantLLM outperforms in key metrics such as adjusted rand index (ARI), normalized mutual information (NMI), and silhouette score (SIL), highlighting its superior clustering accuracy and biological relevance. scPlantLLM represents a foundation model for exploring plant single-cell expression atlases, offering unprecedented capabilities to resolve cellular heterogeneity and regulatory dynamics across diverse plant systems. The code used in this study is available at https://github.com/compbioNJU/scPlantLLM.

Single-Cell Analysis↗
PubMed1996

Assessing dissimilarity of genes by comparing their RNAse A mismatch cleavage patterns.

We propose a simple algorithm for estimating the number of nucleotide differences between a pair of RNA or DNA sequences through comparison of their RNAse A mismatch cleavage patterns. In the RNAse A mismatch cleavage technique two or more sample sequences are hybridized to the same RNA probe, the hybrids are partially digested with RNAse A, and the digestion products are compared on an electrophoretic gel. Here we provide an algorithm for converting the numbers of unique and matching electrophoretic bands into an estimate of the number of nucleotide differences between the sequences. Computer simulation indicates that the proposed method yields a robust estimate of the genetic distance despite stochastic errors and occasional violation of certain assumptions. Our study suggests that the method performs best when the distance between the sequences is < 15 differences. When the sequences under analysis are likely to have larger distances, we advise to substitute one long riboprobe with a set of shorter nonoverlapping probes. The new algorithm is applied to infer the proximity of several strains of pseudorabies virus.

Algorithms↗
PubMed2002

Analysis of result variability from high-density oligonucleotide arrays comparing same-species and cross-species hybridizations.

There exists a significant limitation in the variety of organismsfor which microarrays have been developed because of a lack of genomic sequence data. A near-term solution to this limitation is to use microarrays designed for one species to analyze RNA samples from closely related species. The assumption is that conservation of gene sequences between species will be sufficient to generate a reasonable amount of good-quality data. While there have been relatively few published reports describing the use of microarrays for cross-species hybridizations, this technique is potentially a powerful tool for understanding genomics in model organisms such as nonhuman primates. Here we describe the analysis and comparison of hybridization characteristics and data variability from a set of cross-species (rhesus macaque) and same-species (human) hybridization experiments using human high-density Affymetrix oligonucleotide arrays. The data reveal that a large fraction of probe sets are effective at transcript detection in the cross-species hybridization, validating the application of cross-species hybridizations for nonhuman primate genomics research.

Analysis of Variance↗
PubMed2006

Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences.

MOTIVATION: In 2001 and 2002, we published two papers (Bioinformatics, 17, 282-283, Bioinformatics, 18, 77-82) describing an ultrafast protein sequence clustering program called cd-hit. This program can efficiently cluster a huge protein database with millions of sequences. However, the applications of the underlying algorithm are not limited to only protein sequences clustering, here we present several new programs using the same algorithm including cd-hit-2d, cd-hit-est and cd-hit-est-2d. Cd-hit-2d compares two protein datasets and reports similar matches between them; cd-hit-est clusters a DNA/RNA sequence database and cd-hit-est-2d compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences and can be hundreds of times faster than methods based on the popular sequence comparison and database search tools, such as BLAST.

Algorithms↗
PubMed1995

Nucleotide sequence analysis of the 23S ribosomal RNA-encoding gene of Bartonella bacilliformis.

We report the cloning and characterization of the 23S ribosomal RNA (rRNA)-encoding gene (rDNA) of Bartonella bacilliformis (Bb). The 2821-bp gene is preceded by an 11-nucleotide (nt) inverted repeat (IR) located 81 nt upstream in the tRNA(Ala)-23S rDNA intergenic spacer. The gene is followed by an 8-nt IR, five nt downstream in the 23S-5S rDNA intergenic spacer. The nt sequence of the Bb 23S rDNA is most similar to the 23S rDNA of Rhodopseudomonas palustris (Rp), with 85.4% sequence identity. The Bb 23S rDNA has 77.8% identity to the same gene from Escherichia coli (Ec). Secondary structure predictions indicate that the large subunit (LSU) Bb rRNA contains two smaller stem-loops at nt 1459-1544 and 1658-1685, as compared to the corresponding loops from Ec (nt 1405-1597 and 1707-1751, respectively). In addition, the Bb 23S rRNA has a large 72-nt stem-loop at nt 130-201, as compared to the Ec 18-nt stem-loop (nt 131-148). There is no Bb homologue of the 15-nt stem-loop at the 3' end of the Ec molecule (nt 2791-2805). The Bb 23S rRNA lacks the large stem-loop present in the LSU rRNA of closely related Rhodobacter sphaeroides (Rs) (nt position 1225-1331) which is thought to be involved in cleavage of 23S RNA precursor molecules into 16S and 14S rRNA species. This is the first LSU rDNA nt sequence for any member of the Bartonellaceae family.

Bartonella↗
PubMed2004

Microarray analysis in clinical oncology: pre-clinical optimization using needle core biopsies from xenograft tumors.

BACKGROUND: DNA microarray profiling performed on clinical tissue specimens can potentially provide significant information regarding human cancer biology. Biopsy cores, the typical source of human tumor tissue, however, generally provide very small amounts of RNA (0.3-15 microg). RNA amplification is a common method used to increase the amount of material available for hybridization experiments. Using human xenograft tissue, we sought to address the following three questions: 1) is amplified RNA representative of the original RNA profile? 2) what is the minimum amount of total RNA required to perform a representative amplification? 3) are the direct and indirect methods of labeling the hybridization probe equivalent? METHODS: Total RNA was extracted from human xenograft tissue and amplified using a linear amplification process. RNA was labeled and hybridized, and the resulting images yielded data that was extracted into two categories using the mAdb system: "all genes" and "outliers". Scatter plots were generated for each slide and Pearson Coefficients of correlation were obtained. RESULTS: Results show that the amplification of 5 microg of total RNA yields a Pearson Correlation Coefficient of 0.752 (N = 6,987 genes) between the amplified and total RNA samples. We subsequently determined that amplification of 0.5 microg of total RNA generated a similar Pearson Correlation Coefficient as compared to the corresponding original RNA sample. Similarly, sixty-nine percent of total RNA outliers were detected with 5 microg of amplified starting RNA, and 55% of outliers were detected with 0.5 microg of starting RNA. However, amplification of 0.05 microg of starting RNA resulted in a loss of fidelity (Pearson Coefficient 0.669 between amplified and original samples, 44% outlier concordance). In these studies the direct or indirect methods of probe labeling yielded similar results. Finally, we examined whether RNA obtained from needle core biopsies of human tumor xenografts, amplified and indirectly labeled, would generate representative array profiles compared to larger excisional biopsy material. In this analysis correlation coefficients were obtained ranging from 0.750-0.834 between U251 biopsy cores and excised tumors, and 0.812-0.846 between DU145 biopsy cores and excised tumors. CONCLUSION: These data suggest that needle core biopsies can be used as reliable tissue samples for tumor microarray analysis after linear amplification and either indirect or direct labeling of the starting RNA.

Animals↗
PubMed1992

Structural consensus of RNA templates replicated by Q beta replicase.

Q beta replicase replicates a variety of enzyme-specific small RNAs in addition to the phage genomic RNA. The sequence analysis has revealed that all these RNAs are potentially capable of forming a consensus secondary structure element. It represents a stalk which is formed by the 5'-GGG ... and ... CCCA-3' complementary stretches at the termini of the replicating RNA molecules and adjacent 5'- and 3'-hairpins, which may form a stacking with the stalk. The structure found is rather similar to the analogous structure in the tRNA molecule. The genomic RNA of the Q beta phage and other related phages can also form a similar structural element.

Base Sequence↗
PubMed1998

CMIX, a paired-type homeobox gene expressed before and during formation of the avian primitive streak.

We cloned a chicken homeobox gene closely related to the Xenopus Mix. 1 gene. CMIX is expressed early in embryogenis in a sickle-shaped area in the posterior zone of the blastoderm. With the beginning of gastrulation, CMIX transcripts are found in the primitive streak primordium, then in the young and medium-sized streak, however not in the mesoderm after its emergence. In the fully-extended streak, CMIX is restricted to its middle, i.e. the prospective ventral mesoderm. CMIX RNA is undetectable by whole-mount in-situ analysis in later stages. We compare CMIX expression to the early pattern of the brachyury gene.

Amino Acid Sequence↗
PubMed1995

Sequence analysis and evolutionary aspects of piscine alpha-1-microglobulin/bikunin mRNA transcripts.

Studies on mammalian alpha-1-microglobulin/bikunin (AMBP) protein sequences suggest the ancestral AMBP gene arose between 270 and 80 million years ago. Here we report a similar study including recently reported piscine AMBP messenger RNA sequences. The analysis implies a far earlier data for the assembly of the ancestral AMBP gene, more than 450 million years ago. Similarly, a revised date for the origin of the ancestral Kunitz-type protein is estimated at approximately 875 million years ago. Evolutionary conservation is apparent among all the AMBP amino acid sequences. This implies a common functional significance in both teleosts and mammals. However, an unusually rapid rate of evolution is observed for domain II of the piscine bikunin sequences, suggesting that this domain is no longer truly orthologous in fish.

Alpha-Globulins↗
PubMed2003

Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data.

BACKGROUND: Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. METHODS: We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. RESULTS: We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. CONCLUSIONS: The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell carcinogenesis. This highlights the need for rigorous statistical approaches in microarray studies.

Aged↗
PubMed2000

Global analysis of the genetic network controlling a bacterial cell cycle.

This report presents full-genome evidence that bacterial cells use discrete transcription patterns to control cell cycle progression. Global transcription analysis of synchronized Caulobacter crescentus cells was used to identify 553 genes (19% of the genome) whose messenger RNA levels varied as a function of the cell cycle. We conclude that in bacteria, as in yeast, (i) genes involved in a given cell function are activated at the time of execution of that function, (ii) genes encoding proteins that function in complexes are coexpressed, and (iii) temporal cascades of gene expression control multiprotein structure biogenesis. A single regulatory factor, the CtrA member of the two-component signal transduction family, is directly or indirectly involved in the control of 26% of the cell cycle-regulated genes.

Bacterial Proteins↗