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Biomedical subjects

Eugene Chudin

Publications and source records attributed to Eugene Chudin.

10 recordsLinked to original sources

Human embryonic stem cells have a unique epigenetic signature.

Human embryonic stem (hES) cells originate during an embryonic period of active epigenetic remodeling. DNA methylation patterns are likely to be critical for their self-renewal and pluripotence. We compared the DNA methylation status of 1536 CpG sites (from 371 genes) in 14 independently isolated hES cell lines with five other cell types: 24 cancer cell lines, four adult stem cell populations, four lymphoblastoid cell lines, five normal human tissues, and an embryonal carcinoma cell line. We found that the DNA methylation profile clearly distinguished the hES cells from all of the other cell types. A subset of 49 CpG sites from 40 genes contributed most to the differences among cell types. Another set of 25 sites from 23 genes distinguished hES cells from normal differentiated cells and can be used as biomarkers to monitor differentiation. Our results indicate that hES cells have a unique epigenetic signature that may contribute to their developmental potential.

Cell Differentiation↗

Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines.

BACKGROUND: In order to compare the gene expression profiles of human embryonic stem cell (hESC) lines and their differentiated progeny and to monitor feeder contaminations, we have examined gene expression in seven hESC lines and human fibroblast feeder cells using Illumina bead arrays that contain probes for 24,131 transcript probes. RESULTS: A total of 48 different samples (including duplicates) grown in multiple laboratories under different conditions were analyzed and pairwise comparisons were performed in all groups. Hierarchical clustering showed that blinded duplicates were correctly identified as the closest related samples. hESC lines clustered together irrespective of the laboratory in which they were maintained. hESCs could be readily distinguished from embryoid bodies (EB) differentiated from them and the karyotypically abnormal hESC line BG01V. The embryonal carcinoma (EC) line NTera2 is a useful model for evaluating characteristics of hESCs. Expression of subsets of individual genes was validated by comparing with published databases, MPSS (Massively Parallel Signature Sequencing) libraries, and parallel analysis by microarray and RT-PCR. CONCLUSION: we show that Illumina's bead array platform is a reliable, reproducible and robust method for developing base global profiles of cells and identifying similarities and differences in large number of samples.

Carcinoma, Embryonal↗

High-throughput DNA methylation profiling using universal bead arrays.

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

Base Sequence↗

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↗

Using RNA sample titrations to assess microarray platform performance and normalization techniques.

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.

Algorithms↗

Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays.

We recently developed a sensitive and flexible gene expression profiling system that is not dependent on an intact poly-A tail and showed that it could be used to analyze degraded RNA samples. We hypothesized that the DASL (cDNA-mediated annealing, selection, extension and ligation) assay might be suitable for the analysis of formalin-fixed, paraffin-embedded tissues, an important source of archival tissue material. We now show that, using the DASL assay system, highly reproducible tissue- and cancer-specific gene expression profiles can be obtained with as little as 50 ng of total RNA isolated from formalin-fixed tissues that had been stored from 1 to over 10 years. Further, tissue- and cancer-specific markers derived from previous genome-wide expression profiling studies of fresh-frozen samples were validated in the formalin-fixed samples. The DASL assay system should prove useful for high-throughput expression profiling of archived clinical samples.

Algorithms↗

A versatile assay for high-throughput gene expression profiling on universal array matrices.

We report a flexible, sensitive, and quantitative gene-expression profiling system for assaying more than 400 genes, with three probes per gene, for 96 samples in parallel. The cDNA-mediated annealing, selection, extension and ligation (DASL) assay targets specific transcripts, using oligonucleotides containing unique address sequences that can hybridize to universal arrays. Cell-specific gene expression profiles were obtained using this assay for hormone-treated cell lines and laser-capture microdissected cancer tissues. Gene expression profiles derived from this assay were consistent with those determined by qRT-PCR. The DASL assay has been automated for use with a bead-based 96-array matrix system. The combined high-throughput assay and readout system is accurate and efficient, and can cost-effectively profile the expression of hundreds of genes in thousands of samples.

Androgens↗

A novel, high-performance random array platform for quantitative gene expression profiling.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.

Animals↗

Assessment of the relationship between signal intensities and transcript concentration for Affymetrix GeneChip arrays.

BACKGROUND: Affymetrix microarrays have become increasingly popular in gene-expression studies; however, limitations of the technology have not been well established for commercially available arrays. The hybridization signal has been shown to be proportional to actual transcript concentration for specialized arrays containing hundreds of distinct probe pairs per gene. Additionally, the technology has been described as capable of distinguishing concentration levels within a factor of 2, and of detecting transcript frequencies as low as 1 in 2,000,000. Using commercially available arrays, we assessed these representations directly through a series of 'spike-in' hybridizations involving four prokaryotic transcripts in the absence and presence of fixed eukaryotic background. The contribution of probe-target interactions to the mismatch signal was quantified under various analyte concentrations. RESULTS: A linear relationship between transcript abundance and signal was consistently observed between 1 pM and 10 pM transcripts. The signal ceased to be linear above the 10 pM level and commenced saturating around the 100 pM level. The 0.1 pM transcripts were virtually undetectable in the presence of eukaryotic background. Our measurements show that preponderance of the signal for mismatch probes derives from interactions with the target transcripts. CONCLUSIONS: Landmark studies outlining an observed linear relationship between signal and transcript concentration were carried out under highly specialized conditions and may not extend to commercially available arrays under routine operating conditions. Additionally, alternative metrics that are not based on the difference in the signal of members of a probe pair may further improve the quantitative utility of the Affymetrix GeneChip array.

Oligonucleotide Array Sequence Analysis↗