2005Science in China Series C Life SciencesRequires access

Large scale of identification of differentially expressed genes in the regenerating rat liver after SISPH

Cunshuan Xu

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Abstract

Extensive gene expression analysis was carried out after a 0, 4, 36, 72, 96 h short interval successive partial hepatectomy (SISPH) was performed. A total of 185 elements were identified as differing by more than two-fold in their expression levels at one or more time points. Of these 185 elements, 103 were up-regulated, 82 were down-regulated and 86 elements were unreported genes. Quite a few genes were previously unknown to be involved in liver regeneration (LR). Using cluster and general analysis, we found that the genes at five time points of the SISPH share eight different types of different expression profiles and eight distinct temporal induction or suppression patterns. A comparison of the gene expression in SISPH with that after PH found that 41 genes were specifically altered in SISPH, and 144 genes were simultaneously up-regulated or down-regulated in SISPH and after PH, but they were present in different amounts at the different time points. The conclusions are that (i) microarrays combined with suppressive subtractive hybridization (SSH) can effectively identify genes involved in LR on a large scale; (ii) more genes were up-regulated than down-regulated; (iii) there are fewer abundantly expressed genes than those with increased levels of 2-5 fold.

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Extensive gene expression analysis was carried out after a 0, 4, 36, 72, 96 h short interval successive partial hepatectomy (SISPH) was performed. A total of 185 elements were identified as differing by more than two-fold in their expression levels at one or more time points. Of these 185 elements, 103 were up-regulated, 82 were down-regulated and 86 elements were unreported genes. Quite a few genes were previously unknown to be involved in liver regeneration (LR). Using cluster and general analysis, we found that the genes at five time points of the SISPH share eight different types of different expression profiles and eight distinct temporal induction or suppression patterns. A comparison of the gene expression in SISPH with that after PH found that 41 genes were specifically altered in SISPH, and 144 genes were simultaneously up-regulated or down-regulated in SISPH and after PH, but they were present in different amounts at the different time points. The conclusions are that (i) microarrays combined with suppressive subtractive hybridization (SSH) can effectively identify genes involved in LR on a large scale; (ii) more genes were up-regulated than down-regulated; (iii) there are fewer abundantly expressed genes than those with increased levels of 2-5 fold.

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Available abstract

Extensive gene expression analysis was carried out after a 0, 4, 36, 72, 96 h short interval successive partial hepatectomy (SISPH) was performed. A total of 185 elements were identified as differing by more than two-fold in their expression levels at one or more time points. Of these 185 elements, 103 were up-regulated, 82 were down-regulated and 86 elements were unreported genes. Quite a few genes were previously unknown to be involved in liver regeneration (LR). Using cluster and general analysis, we found that the genes at five time points of the SISPH share eight different types of different expression profiles and eight distinct temporal induction or suppression patterns. A comparison of the gene expression in SISPH with that after PH found that 41 genes were specifically altered in SISPH, and 144 genes were simultaneously up-regulated or down-regulated in SISPH and after PH, but they were present in different amounts at the different time points. The conclusions are that (i) microarrays combined with suppressive subtractive hybridization (SSH) can effectively identify genes involved in LR on a large scale; (ii) more genes were up-regulated than down-regulated; (iii) there are fewer abundantly expressed genes than those with increased levels of 2-5 fold.

Key concepts: Gene, Suppression subtractive hybridization, Biology, Gene expression, DNA microarray, Gene expression profiling, Genetics, Fold change

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