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Analysis of transcript and protein overlap in a human osteosarcoma cell line
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0003-0198-7137
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0001-7034-0850
KTH, School of Biotechnology (BIO), Gene Technology.ORCID iD: 0000-0002-8879-9245
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2010 (English)In: BMC Genomics, ISSN 1471-2164, Vol. 11, no 1, 684- p.Article in journal (Refereed) Published
Abstract [en]

Background: An interesting field of research in genomics and proteomics is to compare the overlap between the transcriptome and the proteome. Recently, the tools to analyse gene and protein expression on a whole-genome scale have been improved, including the availability of the new generation sequencing instruments and high-throughput antibody-based methods to analyze the presence and localization of proteins. In this study, we used massive transcriptome sequencing (RNA-seq) to investigate the transcriptome of a human osteosarcoma cell line and compared the expression levels with in situ protein data obtained in-situ from antibody-based immunohistochemistry (IHC) and immunofluorescence microscopy (IF).

Results: A large-scale analysis based on 2749 genes was performed, corresponding to approximately 13% of the protein coding genes in the human genome. We found the presence of both RNA and proteins to a large fraction of the analyzed genes with 60% of the analyzed human genes detected by all three methods. Only 34 genes (1.2%) were not detected on the transcriptional or protein level with any method. Our data suggest that the majority of the human genes are expressed at detectable transcript or protein levels in this cell line. Since the reliability of antibodies depends on possible cross-reactivity, we compared the RNA and protein data using antibodies with different reliability scores based on various criteria, including Western blot analysis. Gene products detected in all three platforms generally have good antibody validation scores, while those detected only by antibodies, but not by RNA sequencing, generally consist of more low-scoring antibodies.

Conclusion: This suggests that some antibodies are staining the cells in an unspecific manner, and that assessment of transcript presence by RNA-seq can provide guidance for validation of the corresponding antibodies.

Place, publisher, year, edition, pages
2010. Vol. 11, no 1, 684- p.
Keyword [en]
antibody detection, article, cancer cell culture, controlled study, cross reaction, gene expression, gene identification, genetic association, genetic transcription, human, human cell, immunofluorescence microscopy, immunohistochemistry, osteosarcoma cell, RNA sequence, Western blotting
National Category
Other Biological Topics
URN: urn:nbn:se:kth:diva-11444DOI: 10.1186/1471-2164-11-684ISI: 000285887400001ScopusID: 2-s2.0-78649536411OAI: diva2:276128
Knut and Alice Wallenberg FoundationSwedish Research Council
QC 20100723 Uppdaterad från manuskript till artikel (20110207).Available from: 2009-11-10 Created: 2009-11-10 Last updated: 2011-02-07Bibliographically approved
In thesis
1. On Transcriptome Sequencing
Open this publication in new window or tab >>On Transcriptome Sequencing
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis is about the use of massive DNA sequencing to investigate the transcriptome. During recent decades, several studies have made it clear that the transcriptome comprises a more complex set of biochemical machinery than was previously believed. The majority of the genome can be expressed as transcripts; and overlapping and antisense transcription is widespread. New technologies for the interroga- tion of nucleic acids have made it possible to investigate such cellular phenomena in much greater detail than ever before. For each application, special requirements need to be met. The work presented in this thesis focuses on the transcrip- tome and the development of technology for its analysis. In paper I, we report our development of an automated approach for sample preparation. The procedure was benchmarked against a publicly available reference data set, and we note that our approach outperformed similar manual procedures in terms of reproducibility. In the work reported in papers II-IV, we used different massive sequencing technologies to investigate the transcriptome. In paper II we describe a concatemerization approach that increased throughput by 65% using 454 sequencing,and we identify classes of transcripts not previously described in Populus. Papers III and IV both report studies based on SOLiD sequencing. In the former, we investigated transcripts and proteins for 13% of the human gene and detected a massive overlap for the upper 50% transcriptional levels. In the work described in paper IV, we investigated transcription in non-genic regions of the genome and detected expression from a high number of previ- ously unknown loci.

Place, publisher, year, edition, pages
Stockholm: KTH, 2009. 52 p.
Trita-BIO-Report, ISSN 1654-2312 ; 2009:26
Transcriptome, RNA-seq, DNA sequencing, gene expression profiling, non-coding RNA, small RNA
National Category
Other Biological Topics Bioinformatics and Systems Biology Genetics Biochemistry and Molecular Biology Cell and Molecular Biology
urn:nbn:se:kth:diva-11446 (URN)978-91-7415-490-0 (ISBN)
Public defence
2009-12-18, Oscar Klein (FR4), Roslagstullsbacken 21, Albanova University Center, Stockholm, 09:00 (Swedish)
QC 20100723Available from: 2009-12-03 Created: 2009-11-10 Last updated: 2010-07-23Bibliographically approved

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