Dataset Information

High-resolution transcriptome of human macrophages.

ABSTRACT: Macrophages are dynamic cells integrating signals from their microenvironment to develop specific functional responses. Although, microarray-based transcriptional profiling has established transcriptional reprogramming as an important mechanism for signal integration and cell function of macrophages, current knowledge on transcriptional regulation of human macrophages is far from complete. To discover novel marker genes, an area of great need particularly in human macrophage biology but also to generate a much more thorough transcriptome of human M1- and M1-like macrophages, we performed RNA sequencing (RNA-seq) of human macrophages. Using this approach we can now provide a high-resolution transcriptome profile of human macrophages under classical (M1-like) and alternative (M2-like) polarization conditions and demonstrate a dynamic range exceeding observations obtained by previous technologies, resulting in a more comprehensive understanding of the transcriptome of human macrophages. Using this approach, we identify important gene clusters so far not appreciated by standard microarray techniques. In addition, we were able to detect differential promoter usage, alternative transcription start sites, and different coding sequences for 57 gene loci in human macrophages. Moreover, this approach led to the identification of novel M1-associated (CD120b, TLR2, SLAMF7) as well as M2-associated (CD1a, CD1b, CD93, CD226) cell surface markers. Taken together, these data support that high-resolution transcriptome profiling of human macrophages by RNA-seq leads to a better understanding of macrophage function and will form the basis for a better characterization of macrophages in human health and disease.

SUBMITTER: Beyer M

PROVIDER: S-EPMC3448669 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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High-resolution transcriptome of human macrophages.

Beyer Marc M Mallmann Michael R MR Xue Jia J Staratschek-Jox Andrea A Vorholt Daniela D Krebs Wolfgang W Sommer Daniel D Sander Jil J Mertens Christina C Nino-Castro Andrea A Schmidt Susanne V SV Schultze Joachim L JL

PloS one 20120921 9

Macrophages are dynamic cells integrating signals from their microenvironment to develop specific functional responses. Although, microarray-based transcriptional profiling has established transcriptional reprogramming as an important mechanism for signal integration and cell function of macrophages, current knowledge on transcriptional regulation of human macrophages is far from complete. To discover novel marker genes, an area of great need particularly in human macrophage biology but also to ...[more]

PMID: 23029029

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Project description:BackgroundCommercially available microarrays have been used in many settings to generate expression profiles for a variety of applications, including target selection for disease detection, classification, profiling for pharmacogenomic response to therapeutics, and potential disease staging. However, many commercially available microarray platforms fail to capture transcript diversity produced by alternative splicing, a major mechanism for driving proteomic diversity through transcript heterogeneity.ResultsThe human Genome-Wide SpliceArray(TM) (GWSA), a novel microarray platform, utilizes an existing probe design concept to monitor such transcript diversity on a genome scale. The human GWSA allows the detection of alternatively spliced events within the human genome through the use of exon body and exon junction probes to provide a direct measure of each transcript, through simple calculations derived from expression data. This report focuses on the performance and validation of the array when measured against standards recently published by the Microarray Quality Control (MAQC) Project. The array was shown to be highly quantitative, and displayed greater than 85% correlation with the HG-U133 Plus 2.0 array at the gene level while providing more extensive coverage of each gene. Almost 60% of splice events among genes demonstrating differential expression of greater than 3 fold also contained extensive splicing alterations. Importantly, almost 10% of splice events within the gene set displaying constant overall expression values had evidence of transcript diversity. Two examples illustrate the types of events identified: LIM domain 7 showed no differential expression at the gene level, but demonstrated deregulation of an exon skip event, while erythrocyte membrane protein band 4.1 -like 3 was differentially expressed and also displayed deregulation of a skipped exon isoform.ConclusionSignificant changes were detected independent of transcriptional activity, indicating that the controls for transcript generation and transcription are distinct, and require novel tools in order to detect changes in specific transcript quantity. Our results demonstrate that the SpliceArray(TM) design will provide researchers with a robust platform to detect and quantify specific changes not only in overall gene expression, but also at the individual transcript level.

Dataset Information

High-resolution transcriptome of human macrophages.

Publications

High-resolution transcriptome of human macrophages.

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