Biomedical subjects

Ernest S Kawasaki

Publications and source records attributed to Ernest S Kawasaki.

9 recordsLinked to original sources

PubMed2006

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Equipment Design↗

PubMed2006

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project.

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Equipment Design↗

PubMed2006

Comparisons between transcriptional regulation and RNA expression in human embryonic stem cell lines.

Recent studies have focused on transcriptional regulation and gene expression profiling of human embryonic stem cells (hESCs). However, little information is available regarding the relationship between RNA expression and transcriptional regulation, which is critical in the complete understanding of pluripotency and differentiation of hESCs. In the current study, we determined RNA expression of three different hESC lines compared to Human universal reference RNA expression (HuU-RNA) using a full genome expression microarray, and compared our results to target genes previously identified using ChIP-on-chip analysis. The objective was to identify genes common between the two methods, and generate a more reliable list of embryonic signature genes. Even though hESCs were obtained from different sources and maintained under different conditions, a considerable number of genes could be identified as common between RNA expression and transcriptional regulation analyses. As an example, results from ChIP-on-chip studies show that OCT4, SOX2, and NANOG co-occupy SOX2, OCT4, TDGF1, GJA1, SET, and DPPA4 genes. The results are consistent with RNA expression analyses that demonstrate these genes as differently expressed in our hESC lines, further substantiating their role across cell types and confirming their importance as embryonic signatures. In addition, we report the differential expression of growth arrest-specific (GAS) family of genes in hESC. GAS2L1 and GAS3 members of this family appear to be transcriptionally regulated by OCT4, SOX2, or NANOG, whereas GAS5 and GAS6 are not; all of the genes are differentially expressed, as determined by microarray and validated via quantitative (Q)- PCR. Collectively, these data provide insight into the relationship between gene expression and transcriptional regulation, resulting in a reliable list of genes associated with hESCs.

DNA-Binding Proteins↗

PubMed2006

The end of the microarray Tower of Babel: will universal standards lead the way?

Microarrays are the most common method of studying global gene expression, and may soon enter the realm of FDA-approved clinical/diagnostic testing of cancer and other diseases. However, the acceptance of array data has been made difficult by the proliferation of widely different array platforms with gene probes ranging in size from 25 bases (oligonucleotides) to several kilobases (complementary DNAs or cDNAs). The algorithms applied for image and data analysis are also as varied as the microarray platforms, perhaps more so. In addition, there is a total lack of universally accepted standards for use among the different platforms and even within the same array types. Due to this lack of coherency in array technologies, confusion in interpretation of data within and across platforms has often been the norm, and studies of the same biological phenomena have, in many cases, led to contradictory results. In this commentary/review, some of the causes of this confusion will be summarized, and progress in overcoming these obstacles will be described, with the goal of providing an optimistic view of the future for the use of array technologies in global expression profiling and other applications.

Control Groups↗

PubMed2005

Three microarray platforms: an analysis of their concordance in profiling gene expression.

BACKGROUND: Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25-30 base), long oligonucleotide (50-80 base), and cDNA (highly variable in length). The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. RESULTS: The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%. CONCLUSION: Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.

Cell Line↗

PubMed2005

The External RNA Controls Consortium: a progress report.

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

Animals↗

PubMed2004

Microarrays and the gene expression profile of a single cell.

With completion of the human genome sequence, it is now possible to study the expression of the entire human gene complement of approximately 30,000-35,000 genes. To accomplish this goal, microarrays have become the leading methodology for the analysis of global gene expression. Improvements in technology have increased the sensitivity of microarrays to the point where it is feasible to study gene expression in a small number of cells and even at the single cell level. A summary of developments in the area of expression profiling in single cells will be described, and the rationale for these types of studies will be presented. In addition, from a biologist's point of view, some bioinformatic challenges of expression analysis of single cells will be discussed.

Cell Physiological Phenomena↗

PubMed2004

Laser capture microdissection, microarrays and the precise definition of a cancer cell.

Most expression profiling studies of solid tumors have used biopsy samples containing large numbers of contaminating stromal and other cell types, thereby complicating any precise delineation of gene expression in nontumor versus tumor cell types. Combining laser capture microdissection, RNA amplification protocols, microarray technologies and our knowledge of the human genome sequence, it is possible to isolate pure populations of cells or even a single cell and interrogate the expression of thousands of sequences for the purpose of more precisely defining the biology of the tumor cell. Although many of the studies that currently allow for characterization of small sample preparations and single cells were performed utilizing noncancer cell types, and in some cases isolation protocols other than laser capture microdissection, a list of protocols are described that could be used for the expression analysis of individual tumor cells. Application of these experimental approaches to cancer studies may permit a more accurate definition of the biology of the cancer cell, so that ultimately, more specific targeted therapies can be developed.

B-Lymphocytes↗

PubMed2003

Microarrays: the use of oligonucleotides and cDNA for the analysis of gene expression.

Completion of the human genome sequence has made it possible to study the expression of the entire human gene complement (>30,000 estimated genes). Aiding in this remarkable feat, DNA microarrays have become the main technological workhorse for gene expression studies. To date, detection platforms for most microarrays have relied on short (25 base) oligonucleotides synthesized in situ, or longer, highly variable length DNAs from PCR amplification of cDNA libraries. A third choice, long (50-80 base) oligonucleotide arrays, is now available and might eventually eliminate the use of cDNA arrays. The technology has advanced to such a point that researchers now demand microarrays that are cost-effective and have flexibility and quality assurance. Short- and long-oligonucleotide technologies offer such advantages, and could possibly become the major competing platform in the near future.

Animals↗