Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach

<p>Abstract</p> <p>Background</p> <p>The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functi...

Full description

Bibliographic Details
Main Authors: Lee Yung-Lin, Lee Yun-Shien, Pan Yi-Shin, Lee Wei-Chen, Hsieh Sen-Yung
Format: Article
Language:English
Published: BMC 2006-05-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/7/131
id doaj-8dd3f1278f8f46d980395b74c4a743a7
record_format Article
spelling doaj-8dd3f1278f8f46d980395b74c4a743a72020-11-24T21:39:39ZengBMCBMC Genomics1471-21642006-05-017113110.1186/1471-2164-7-131Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approachLee Yung-LinLee Yun-ShienPan Yi-ShinLee Wei-ChenHsieh Sen-Yung<p>Abstract</p> <p>Background</p> <p>The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes.</p> <p>Results</p> <p>We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis.</p> <p>Conclusion</p> <p>The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies.</p> http://www.biomedcentral.com/1471-2164/7/131
collection DOAJ
language English
format Article
sources DOAJ
author Lee Yung-Lin
Lee Yun-Shien
Pan Yi-Shin
Lee Wei-Chen
Hsieh Sen-Yung
spellingShingle Lee Yung-Lin
Lee Yun-Shien
Pan Yi-Shin
Lee Wei-Chen
Hsieh Sen-Yung
Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
BMC Genomics
author_facet Lee Yung-Lin
Lee Yun-Shien
Pan Yi-Shin
Lee Wei-Chen
Hsieh Sen-Yung
author_sort Lee Yung-Lin
title Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
title_short Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
title_full Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
title_fullStr Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
title_full_unstemmed Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach
title_sort differentially profiling the low-expression transcriptomes of human hepatoma using a novel ssh/microarray approach
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2006-05-01
description <p>Abstract</p> <p>Background</p> <p>The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes.</p> <p>Results</p> <p>We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis.</p> <p>Conclusion</p> <p>The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies.</p>
url http://www.biomedcentral.com/1471-2164/7/131
work_keys_str_mv AT leeyunglin differentiallyprofilingthelowexpressiontranscriptomesofhumanhepatomausinganovelsshmicroarrayapproach
AT leeyunshien differentiallyprofilingthelowexpressiontranscriptomesofhumanhepatomausinganovelsshmicroarrayapproach
AT panyishin differentiallyprofilingthelowexpressiontranscriptomesofhumanhepatomausinganovelsshmicroarrayapproach
AT leeweichen differentiallyprofilingthelowexpressiontranscriptomesofhumanhepatomausinganovelsshmicroarrayapproach
AT hsiehsenyung differentiallyprofilingthelowexpressiontranscriptomesofhumanhepatomausinganovelsshmicroarrayapproach
_version_ 1725930109693591552