Dataset Information

RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.

ABSTRACT: Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. This list is enriched for components of the proteasome (ex. PSMA1) and spliceosome (ex. SF3B2), and also includes the translation initiation factor EIF4H, and many heterogeneous nuclear ribonucleoprotein genes (ex. HNRNPL). We have validated the consistency of our new control genes in 1933 cancer and normal tissues using publically available RNA-seq data, and their usefulness in qRT-PCR analysis is clearly demonstrated.

SUBMITTER: Macrae T

PROVIDER: S-EPMC3775772 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.

Macrae Tara T Sargeant Tobias T Lemieux Sébastien S Hébert Josée J Deneault Eric E Sauvageau Guy G

PloS one 20130917 9

Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. Th ...[more]

PMID: 24069164

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Project description:BACKGROUND: Cis-natural antisense transcripts (cis-NATs) are RNAs transcribed from the antisense strand of a gene locus, and are complementary to the RNA transcribed from the sense strand. Common techniques including microarray approach and analysis of transcriptome databases are the major ways to globally identify cis-NATs in various eukaryotic organisms. Genome-wide in silico analysis has identified a large number of cis-NATs that may generate endogenous short interfering RNAs (nat-siRNAs), which participate in important biogenesis mechanisms for transcriptional and post-transcriptional regulation in rice. However, the transcriptomes are yet to be deeply sequenced to comprehensively investigate cis-NATs. RESULTS: We applied high-throughput strand-specific complementary DNA sequencing technology (ssRNA-seq) to deeply sequence mRNA for assessing sense and antisense transcripts that were derived under salt, drought and cold stresses, and normal conditions, in the model plant rice (Oryza sativa). Combined with RAP-DB genome annotation (the Rice Annotation Project Database build-5 data set), 76,013 transcripts corresponding to 45,844 unique gene loci were assembled, in which 4873 gene loci were newly identified. Of 3819 putative rice cis-NATs, 2292 were detected as expressed and giving rise to small RNAs from their overlapping regions through integrated analysis of ssRNA-seq data and small RNA data. Among them, 503 cis-NATs seemed to be associated with specific conditions. The deep sequence data from isolated epidermal cells of rice seedlings further showed that 54.0% of cis-NATs were expressed simultaneously in a population of homogenous cells. Nearly 9.7% of rice transcripts were involved in one-to-one or many-to-many cis-NATs formation. Furthermore, only 17.4-34.7% of 223 many-to-many cis-NAT groups were all expressed and generated nat-siRNAs, indicating that only some cis-NAT groups may be involved in complex regulatory networks. CONCLUSIONS: Our study profiles an abundance of cis-NATs and nat-siRNAs in rice. These data are valuable for gaining insight into the complex function of the rice transcriptome.

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Dataset Information

RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.

Publications

RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.

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