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.

MicroRNAs play important roles in animal development, cell differentiation, and metabolism and have been implicated in human cancer. The let-7 microRNA controls the timing of cell cycle exit and terminal differentiation in Caenorhabditis elegans and is poorly expressed or deleted in human lung tumors. Here, we show that let-7 is highly expressed in normal lung tissue, and that inhibiting let-7 function leads to increased cell division in A549 lung cancer cells. Overexpression of let-7 in cancer cell lines alters cell cycle progression and reduces cell division, providing evidence that let-7 functions as a tumor suppressor in lung cells. let-7 was previously shown to regulate the expression of the RAS lung cancer oncogenes, and our work now shows that multiple genes involved in cell cycle and cell division functions are also directly or indirectly repressed by let-7. This work reveals the let-7 microRNA to be a master regulator of cell proliferation pathways. [Cancer Res 2007;67(16):7713–22]

Tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) binds to death receptors 4/5 and selectively induces caspase-dependent apoptosis. The RNA interference screening approach has led to the discovery and characterization of several TRAIL pathway components in human cells. Here, libraries of synthetic small interfering RNA (siRNA) and microRNAs (miRNA) were used to probe the TRAIL pathway. In addition to known genes, siRNAs targeting CDK4, PTGS1, ALG2, CLCN3, IRAK4, and MAP3K8 altered TRAIL-induced caspase-3 activation responses. Introduction of the miRNAs let-7c, mir-10a, mir-144, mir-150, mir-155, and mir-193 also affected the activation of the caspase cascade. Putative targets of these endogenous miRNAs included genes encoding death receptors, caspases, and other apoptosis-related genes. Among the novel genes revealed in the screen, CDK4 was selected for further characterization. CDK4 was the only member of the cyclin-dependent kinase gene family that bore a unique function in apoptotic signal transduction. [Cancer Res 2007;67(22):10782–8]

We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance.

Background: RNA-Seq is the recently developed high-throughput sequencing technology for profiling the entire transcriptome in any organism. It has several major advantages over current hybridization-based approach such as microarrays. However, the cost per sample by RNA-Seq is still prohibitive for most laboratories. With continued improvement in sequence output, it would be cost-effective if multiple samples are multiplexed and sequenced in a single lane with sufficient transcriptome coverage. The objective of this analysis is to evaluate what sequencing depth might be sufficient to interrogate gene expression profiling in the chicken by RNA-Seq. Results: Two cDNA libraries from chicken lungs were sequenced initially, and 4.9 million (M) and 1.6 M (60 bp) reads were generated, respectively. With significant improvements in sequencing technology, two technical replicate cDNA libraries were re-sequenced. Totals of 29.6 M and 28.7 M (75 bp) reads were obtained with the two samples. More than 90% of annotated genes were detected in the data sets with 28.7-29.6 M reads, while only 68% of genes were detected in the data set with 1.6 M reads. The correlation coefficients of gene expression between technical replicates within the same sample were 0.9458 and 0.8442. To evaluate the appropriate depth needed for mRNA profiling, a random sampling method was used to generate different number of reads from each sample. There was a significant increase in correlation coefficients from a sequencing depth of 1.6 M to 10 M for all genes except highly abundant genes. No significant improvement was observed from the depth of 10 M to 20 M (75 bp) reads. Conclusion: The analysis from the current study demonstrated that 30 M (75 bp) reads is sufficient to detect all annotated genes in chicken lungs. Ten million (75 bp) reads could detect about 80% of annotated chicken genes, and RNA-Seq at this depth can serve as a replacement of microarray technology. Furthermore, the depth of sequencing had a significant impact on measuring gene expression of low abundant genes. Finally, the combination of experimental and simulation approaches is a powerful approach to address the relationship between the depth of sequencing and transcriptome coverage.