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      Discovering multiple transcripts of human hepatocytes using massively parallel signature sequencing (MPSS)

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          Abstract

          Background

          The liver is the largest human internal organ – it is composed of multiple cell types and plays a vital role in fulfilling the body's metabolic needs and maintaining homeostasis. Of these cell types the hepatocytes, which account for three-quarters of the liver's volume, perform its main functions. To discover the molecular basis of hepatocyte function, we employed Massively Parallel Signature Sequencing (MPSS) to determine the transcriptomic profile of adult human hepatocytes obtained by laser capture microdissection (LCM).

          Results

          10,279 UniGene clusters, representing 7,475 known genes, were detected in human hepatocytes. In addition, 1,819 unique MPSS signatures matching the antisense strand of 1,605 non-redundant UniGene clusters (such as APOC1, APOC2, APOB and APOH) were highly expressed in hepatocytes.

          Conclusion

          Apart from a large number of protein-coding genes, some of the antisense transcripts expressed in hepatocytes could play important roles in transcriptional interference via a cis-/ trans-regulation mechanism. Our result provided a comprehensively transcriptomic atlas of human hepatocytes using MPSS technique, which could be served as an available resource for an in-depth understanding of human liver biology and diseases.

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          Most cited references20

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          Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays.

          We describe a novel sequencing approach that combines non-gel-based signature sequencing with in vitro cloning of millions of templates on separate 5 microm diameter microbeads. After constructing a microbead library of DNA templates by in vitro cloning, we assembled a planar array of a million template-containing microbeads in a flow cell at a density greater than 3x10(6) microbeads/cm2. Sequences of the free ends of the cloned templates on each microbead were then simultaneously analyzed using a fluorescence-based signature sequencing method that does not require DNA fragment separation. Signature sequences of 16-20 bases were obtained by repeated cycles of enzymatic cleavage with a type IIs restriction endonuclease, adaptor ligation, and sequence interrogation by encoded hybridization probes. The approach was validated by sequencing over 269,000 signatures from two cDNA libraries constructed from a fully sequenced strain of Saccharomyces cerevisiae, and by measuring gene expression levels in the human cell line THP-1. The approach provides an unprecedented depth of analysis permitting application of powerful statistical techniques for discovery of functional relationships among genes, whether known or unknown beforehand, or whether expressed at high or very low levels.
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            Widespread occurrence of antisense transcription in the human genome.

            An increasing number of eukaryotic genes are being found to have naturally occurring antisense transcripts. Here we study the extent of antisense transcription in the human genome by analyzing the public databases of expressed sequences using a set of computational tools designed to identify sense-antisense transcriptional units on opposite DNA strands of the same genomic locus. The resulting data set of 2,667 sense-antisense pairs was evaluated by microarrays containing strand-specific oligonucleotide probes derived from the region of overlap. Verification of specific cases by northern blot analysis with strand-specific riboprobes proved transcription from both DNA strands. We conclude that > or =60% of this data set, or approximately 1,600 predicted sense-antisense transcriptional units, are transcribed from both DNA strands. This indicates that the occurrence of antisense transcription, usually regarded as infrequent, is a very common phenomenon in the human genome. Therefore, antisense modulation of gene expression in human cells may be a common regulatory mechanism.
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              Transcription of antisense RNA leading to gene silencing and methylation as a novel cause of human genetic disease.

              Nearly all human genetic disorders result from a limited repertoire of mutations in an associated gene or its regulatory elements. We recently described an individual with an inherited form of anemia (alpha-thalassemia) who has a deletion that results in a truncated, widely expressed gene (LUC7L) becoming juxtaposed to a structurally normal alpha-globin gene (HBA2). Although it retains all of its local and remote cis-regulatory elements, expression of HBA2 is silenced and its CpG island becomes completely methylated early during development. Here we show that in the affected individual, in a transgenic model and in differentiating embryonic stem cells, transcription of antisense RNA mediates silencing and methylation of the associated CpG island. These findings identify a new mechanism underlying human genetic disease.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                2007
                2 July 2007
                : 8
                : 207
                Affiliations
                [1 ]Department of Chemistry of Fudan University & Shanghai-Ministry Key Laboratory of Disease and Health Genomics, Chinese National Human Genome Center at Shanghai, 351 Guo Shou-Jing Road, Shanghai 201203, China
                [2 ]SCBIT-Inforsense Joint Lab, Shanghai Center for Bioinformation Technology, 100 Qinzhou Road, Shanghai 200235, China
                [3 ]School of Life Science, Fudan University, 220 Handan Road, Shanghai 200433, China
                [4 ]Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
                [5 ]International Co-operation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute, the Second Military Medical University, Shanghai 200438, China
                [6 ]MOE Key Laboratory of Bioinformatics, Department of Automation, Tsinghua University, Beijing 100084, China
                Article
                1471-2164-8-207
                10.1186/1471-2164-8-207
                1929076
                17601345
                33405c8a-64a5-4b90-9143-e2b32441c715
                Copyright © 2007 Huang et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 November 2006
                : 2 July 2007
                Categories
                Research Article

                Genetics
                Genetics

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