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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.

There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard ‘dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols. Differential gene expression experiments yield quantitative insight into biological activity and may be important in disease classification and treatment. Here, the authors analyse external spike-in RNA controls to provide a standard method to assess and compare experiment performance.

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.

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.

The Sequencing Quality Control (SEQC) consortium shows that junction discovery and differential gene expression profiling with RNA-seq can be robust but transcript-level and absolute measurements remain challenging. We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

A strategy has been formulated for the site-directed mutagenesis of the Azotobacter vinelandii nifDK genes. These genes encode the α and β subunits of the MoFe protein of nitrogenase, respectively. Six mutant strains, which produce MoFe proteins altered in their α subunit by known single amino acid substitutions, have been produced. Three of these transversion mutations involve cysteine-to-serine changes (at residues 154, 183, and 275), two involve glutamine-to-glutamic acid changes (at residues 151 and 191), and one involves an aspartic acid-to-glutamic acid change (at residue 161). All three possible phenotypic responses are observed within this group--i.e., normal, slow, and no growth in the absence of a fixed-nitrogen source. Two-dimensional gel electrophoresis indicates that all mutants accumulate normal levels of the subunits of both nitrogenase component proteins. Whole-cell and crude-extract acetylene-reduction activities indicate substantial levels of Fe protein activity in all strains. In contrast, MoFe protein activities do not parallel the diazotrophic growth capability for all strains. Two strains appear to exhibit altered substrate discrimination. Such analyses should aid in the identification of metallocluster-binding sites and subunit--subunit interaction domains of the MoFe protein and also provide insight into the mechanistic roles of the various prosthetic groups in catalysis.

Part 1. Nucleotide sequences of the Major Sperm Protein genes from 21 nematode species were surveyed. The results from this study have provided information about the genomic changes of the highly conserved msp gene during nematode evolution. Analysis of the msp sequence data set is presented. An example is given for the utilization of msp sequences as nematode genetic markers. Part 2. A strategy suggested by comparative genomic studies was used to amplify the entire Vibrio proteolyticus (Vp) gene for ribosomal protein L18. This approach should allow rapid characterization of L18 from large numbers of bacteria. Both Vp L18 and Escherichia coli (Ec) L18 were overproduced and purified by His-tag affinity chromatography. The purified L18 fusion proteins, were both found to bind to either the Vp 5S or Ec 5S rRNAs in vitro. Vp L18 protein was also shown to incorporate into Ec ribosomes in vivo. This His-tag strategy likely will have general applicability for the study of ribosomal proteins in vitro and in vivo. Part 3. One of five rRNA gene clusters from Rhodococcus IGTS8 was cloned and the nucleotide sequence determined. Phylogenetic analysis using the 16S rRNA gene suggested this Rhodococcus is a strain or a close relative of an erythropolis species. Complete nucleotide sequence analysis is presented. Part 4. A mini-review of PCR technology provides an introduction to the description of a method for entrapping PCR reagents in a gel matrix. Studies performed to determine its potential as an effective reactant packaging and delivery system are summarized.

There is a critical need for standard approaches to assess, report, and compare the technical performance of genome-scale differential gene expression experiments. We assess technical performance with a proposed \"standard\" dashboard of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates, and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared amongst 12 laboratories with three different measurement processes demonstrated generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias were also comparable amongst laboratories for the same measurement process. Different biases were observed for measurement processes using different mRNA enrichment protocols.