Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Estimating accuracy of absolute gene expression measurement by RNA-Seq and microarrays with proteomics

ABSTRACT: Microarrays revolutionized biological research by enabling gene expression comparisons on a transcriptome-wide scale. Microarrays, however, do not estimate absolute expression level accurately. At present, high throughput sequencing is emerging as an alternative methodology for transcriptome studies. Although free of many limitations imposed by microarray design, its potential to estimate absolute transcript levels is unknown. In this study, we evaluate relative accuracy of microarrays and transcriptome sequencing (RNA-Seq) using third methodology: proteomics. We find that RNA-Seq provides a better estimate of absolute expression levels. We first determined whether we could reproduce the agreement between mRNA expression estimates measured by microarrays and by RNA-Seq reported in other studies. For this purpose, we collected mRNA expression data in two independent cerebellar samples, each containing pooled mRNA from 5 adult human individuals, using both methodologies. Next, to test whether biological variation among samples would substantially reduce correlation strength, we compared expression levels determined by RNA-Seq in two pooled samples to the microarray data obtained from different individuals. For this purpose we used expression measurements obtained using Affymetrix Exon Arrays in 5 individual adult human cerebellar samples, none of which were included in the two pooled samples. Further, since technical and stochastic variation are extremely unlikely to result in better correlation between mRNA and protein expression measurements, we argue that the technology resulting in better correlation must provide more accurate measurements.

ORGANISM(S): Homo sapiens

SUBMITTER: Xing Fu

PROVIDER: E-GEOD-13744 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Estimating accuracy of RNA-Seq and microarrays with proteomics.

Fu Xing X Fu Ning N Guo Song S Yan Zheng Z Xu Ying Y Hu Hao H Menzel Corinna C Chen Wei W Li Yixue Y Zeng Rong R Khaitovich Philipp P

BMC genomics 20090416

<h4>Background</h4>Microarrays revolutionized biological research by enabling gene expression comparisons on a transcriptome-wide scale. Microarrays, however, do not estimate absolute expression level accurately. At present, high throughput sequencing is emerging as an alternative methodology for transcriptome studies. Although free of many limitations imposed by microarray design, its potential to estimate absolute transcript levels is unknown.<h4>Results</h4>In this study, we evaluate relative ...[more]

PMID: 19371429

Similar Datasets

Project description:Among other factors, changes in gene expression on the human evolutionary lineage have been suggested to play an important role in the establishment of human-specific phenotypes. However, the molecular mechanisms underlying these expression changes are largely unknown. Here, we have explored the role of microRNA (miRNA) in the regulation of gene expression divergence between adult humans, chimpanzees and rhesus macaques, in two brain regions: prefrontal cortex and cerebellum. Using combination of high-throughput sequencing, miRNA microarrays and Q-PCR, we have shown that up to 11% of the 325 expressed miRNA diverged significantly between humans and chimpanzees and up to 31% - between humans and macaques. Measuring mRNA and protein expression in human and chimpanzee brains, we found a significant inverse relationship between the miRNA and the target genes expression divergence, explaining 2-4% of mRNA and 4-6% of protein expression differences. Notably, miRNA showing human-specific expression localize in neurons and target genes that are involved in neural functions. Enrichment in neural functions, as well as miRNA-driven regulation on the human evolutionary lineage, were further confirmed by experimental validation of predicted miRNA targets in two neuroblastoma cell lines. Finally, we identified a signature of positive selection in the upstream region of one of the five miRNA with human-specific expression, miR-34c-5p. This suggests that miR-34c-5p expression change took place after the split of the human and the Neanderthal lineages and had adaptive significance. Taken together these results indicate that changes in miRNA expression might have contributed to evolution of human cognitive functions. Human, chimpanzee, and rhesus: mRNA, microRNA, and microRNA sequencing. Neuroblastoma cell lines: miRNA transfection experiments were conducted on two human-derived neuroblastoma cell lines (SH-SY5Y and SK-N-SH). Briefly, cells were plated in 0.5ml of growth medium, without antibiotics, 24h prior to transfection. miRNA mimics-Lipofectamine 2000 (Invitrogen) complexes were prepared freshly before transfection according to the manufacturer's protocol. SH-SY5Y and SK-N-SH cells were transfected in six-well plates using miRNA mimics-Lipofectamine 2000 with a final oligonucleotide concentration of 10nmol/L. In parallel, negative control transfections with mock oligonucleotides were conducted according to the manufacturer's protocol. For each cell line, transfections with negative control oligonucleotides were carried out in two independent replicates. Cells were harvested after 24h, total RNA were extracted with Trizol reagent (Invitrogen) and further processed and hybridized to Affymetrix Human Genome U133 Plus 2.0 arrays following the manufacturer's instructions. The gene expression levels were determined using rma in the R Affy package.

Dataset Information

Estimating accuracy of absolute gene expression measurement by RNA-Seq and microarrays with proteomics

Publications

Estimating accuracy of RNA-Seq and microarrays with proteomics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets