Biomedical subjects

Yulei Wang

Publications and source records attributed to Yulei Wang.

8 recordsLinked to original sources

PubMed2020

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗

PubMed2006

Effect of various normalization methods on Applied Biosystems expression array system data.

BACKGROUND: DNA microarray technology provides a powerful tool for characterizing gene expression on a genome scale. While the technology has been widely used in discovery-based medical and basic biological research, its direct application in clinical practice and regulatory decision-making has been questioned. A few key issues, including the reproducibility, reliability, compatibility and standardization of microarray analysis and results, must be critically addressed before any routine usage of microarrays in clinical laboratory and regulated areas can occur. In this study we investigate some of these issues for the Applied Biosystems Human Genome Survey Microarrays. RESULTS: We analyzed the gene expression profiles of two samples: brain and universal human reference (UHR), a mixture of RNAs from 10 cancer cell lines, using the Applied Biosystems Human Genome Survey Microarrays. Five technical replicates in three different sites were performed on the same total RNA samples according to manufacturer's standard protocols. Five different methods, quantile, median, scale, VSN and cyclic loess were used to normalize AB microarray data within each site. 1,000 genes spanning a wide dynamic range in gene expression levels were selected for real-time PCR validation. Using the TaqMan assays data set as the reference set, the performance of the five normalization methods was evaluated focusing on the following criteria: (1) Sensitivity and reproducibility in detection of expression; (2) Fold change correlation with real-time PCR data; (3) Sensitivity and specificity in detection of differential expression; (4) Reproducibility of differentially expressed gene lists. CONCLUSION: Our results showed a high level of concordance between these normalization methods. This is true, regardless of whether signal, detection, variation, fold change measurements and reproducibility were interrogated. Furthermore, we used TaqMan assays as a reference, to generate TPR and FDR plots for the various normalization methods across the assay range. Little impact is observed on the TP and FP rates in detection of differentially expressed genes. Additionally, little effect was observed by the various normalization methods on the statistical approaches analyzed which indicates a certain robustness of the analysis methods currently in use in the field, particularly when used in conjunction with the Applied Biosystems Gene Expression System.

Algorithms↗

PubMed2006

Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms.

BACKGROUND: Gene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms. RESULTS: Expression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilent's Whole Human Genome Oligo Microarrays, and the resulting gene expression patterns were analyzed. Both unsupervised and supervised analyses identified the different clinically relevant subtypes of breast tumours, and the results were consistent across all three platforms. Gene classification and biological pathway analyses of the genes differentially expressed between the two main subtypes revealed different molecular mechanisms descriptive of the two expression-based subtypes: Signature genes of the luminal A subtype were over-represented by genes involved in fatty acid metabolism and steroid hormone-mediated signaling pathways, in particular estrogen receptor signaling, while signature genes of the basal-like subtype were over-represented by genes involved in cell proliferation and differentiation, p21-mediated pathway, and G1-S checkpoint of cell cycle-signaling pathways. A minimal set of 54 genes that best discriminated the two subtypes was identified using the combined data sets generated from the three different array platforms. These predictor genes were further verified by TaqMan Gene Expression assays. CONCLUSION: We have identified and validated the two main previously defined clinically relevant subtypes, luminal A and basal-like, in a small set of early stage breast carcinomas. Signature genes characterizing these two subtypes revealed that distinct molecular mechanisms might have been pre-programmed at an early stage in different subtypes of the disease. Our results provide further evidence that these breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies. Finally, validated by multiple gene expression platforms, including quantitative PCR, the set of 54 predictor genes identified in this study may define potential prognostic molecular markers for breast cancer.

Biomarkers, Tumor↗

PubMed2006

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.

BACKGROUND: DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. RESULTS: In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. CONCLUSION: Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.

Gene Expression Profiling↗

PubMed2005

Long versus short oligonucleotide microarrays for the study of gene expression in nonhuman primates.

The high degree of sequence similarity between human and nonhuman primate (NHP) genomic DNA suggests that human genome sequence-based DNA microarrays may be used effectively to study gene expression in NHP disease models. In the present study, two distinct commercially available human genome microarray platforms, the Affymetrix HG U133A GeneChip System utilizing Human Genome U133A GeneChips and the Applied Biosystems Expression Array System utilizing the Human Genome Survey Microarray, were used to identify and characterize gene expression changes in the anterior cerebellum of a macaque monkey model of human alcoholism. The Affymetrix microarray consists of eleven short oligonucleotide probe sets for each gene while the Applied Biosystems Microarray uses a single long oligonucleotide per gene. Cross-mapping of probes revealed a total of 11,542 genes that are represented on both microarray platforms. Absolute measures of gene expression ("present calls") from the cerebellum RNA samples were 65-70% (Applied Biosystems Expression Array System) and 27-30% (AffymetrixGeneChip System) among these common gene targets. Analysis of variance (ANOVA; p<0.05; >1.2 fold change; detected on at least 50% of the arrays) indicated 932 and 515 differentially expressed genes for the Applied Biosystems and Affymetrix microarrays, respectively. Significance analysis of microarrays (SAM) identified 255 significant genes at 5% false discovery rate (FDR) for the Applied Biosystems data set and five significant genes at 60% FDR (minimum FDR) for the Affymetrix data set. TaqMan assay-based real-time PCR validation of a number of differentially-expressed genes yielded results that agreed well with the array data in the majority of comparisons. This study demonstrates that human sequence-based DNA arrays can be used effectively to detect differential gene expression in an NHP disease model and provides evidence that the use of this long oligonucleotide-based microarray platform may be more suitable for cross-species gene expression studies than a short oligonucleotide-based system.

Alcohol Drinking↗

PubMed2003

Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae.

We have analyzed the translational status of each mRNA in rapidly growing Saccharomyces cerevisiae. mRNAs were separated by velocity sedimentation on a sucrose gradient, and 14 fractions across the gradient were analyzed by quantitative microarray analysis, providing a profile of ribosome association with mRNAs for thousands of genes. For most genes, the majority of mRNA molecules were associated with ribosomes and presumably engaged in translation. This systematic approach enabled us to recognize genes with unusual behavior. For 43 genes, most mRNA molecules were not associated with ribosomes, suggesting that they may be translationally controlled. For 53 genes, including GCN4, CPA1, and ICY2, three genes for which translational control is known to play a key role in regulation, most mRNA molecules were associated with a single ribosome. The number of ribosomes associated with mRNAs increased with increasing length of the putative protein-coding sequence, consistent with longer transit times for ribosomes translating longer coding sequences. The density at which ribosomes were distributed on each mRNA (i.e., the number of ribosomes per unit ORF length) was well below the maximum packing density for nearly all mRNAs, consistent with initiation as the rate-limiting step in translation. Global analysis revealed an unexpected correlation: Ribosome density decreases with increasing ORF length. Models to account for this surprising observation are discussed.

Genome, Fungal↗

PubMed2002

Precision and functional specificity in mRNA decay.

Posttranscriptional processing of mRNA is an integral component of the gene expression program. By using DNA microarrays, we precisely measured the decay of each yeast mRNA, after thermal inactivation of a temperature-sensitive RNA polymerase II. The half-lives varied widely, ranging from approximately 3 min to more than 90 min. We found no simple correlation between mRNA half-lives and ORF size, codon bias, ribosome density, or abundance. However, the decay rates of mRNAs encoding groups of proteins that act together in stoichiometric complexes were generally closely matched, and other evidence pointed to a more general relationship between physiological function and mRNA turnover rates. The results provide strong evidence that precise control of the decay of each mRNA is a fundamental feature of the gene expression program in yeast.

Glycolysis↗

PubMed2002

Ratcheting up vir gene expression in Agrobacterium tumefaciens: coiled coils in histidine kinase signal transduction.

The transmembrane histidine kinase VirA is responsible for the recognition of information from several plant-derived xenognostic signals that control gene transfer between Agrobacterium tumefaciens and its eukaryotic host. As with other histidine autokinases, VirA appears to exist as a homodimer within the inner membrane of the bacterium. In this study, we identify the putative homodimeric coiled-coil-like motifs Helix TM2 (amino acids (aa) 259-288) and Helix C (aa 293-327) within the previously assigned signal input domain. The functional importance of these coiled-coil interactions in signal-mediated VirA activation is investigated by the construction of fusion proteins with the leucine zipper domain of the transcription factor GCN4. Replacement of the membrane-spanning and periplasmic domains of VirA with the GCN4 leucine zipper gave functional proteins with increased signal-induced vir gene expression. When the GCN4 fusion was used to conformationally bias the interface of the Helix C coiled coil, constitutively active chimeras were created. The activity of these constructs was dependent on the interface of the Helix C coiled coil, and a ratchet model is proposed in which VirA activation is achieved by signal-induced switching of the interfaces of the homodimer. Since VirA functions as a transducer and integrates various host cues indirectly, these data highlight its role as an "antenna" for the tumor-inducing (Ti) plasmid, able to monitor the host proteome so as to select for successful xenognostic signaling strategies.

Agrobacterium tumefaciens↗