Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feat...Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feature to improve the accuracy and efficiency when they are used for pattern recognition and clustering analysis. A Poisson Model-based Kernel (PMK) was proposed based on the Poisson distribution of the SAGE data. Kernel Principle Component Analysis (KPCA) with PMK was proposed and used in feature-extract analysis of mouse retinal SAGE data. The computa-tional results show that this algorithm can extract feature effectively and reduce dimensions of SAGE data.展开更多
Objective: To monitor the systemic gene expression profile in a murine model of lipopolysaccharide-induced acute lung injury. Methods: Acute lung injury was induced by intratracheal injection of lipopolysaccharide in ...Objective: To monitor the systemic gene expression profile in a murine model of lipopolysaccharide-induced acute lung injury. Methods: Acute lung injury was induced by intratracheal injection of lipopolysaccharide in 3 mice. Another 3 normal mice receiving same volume of normal saline were taken as the controls. The comprehensive gene expression profile was monitored by the recently modified long serial analysis of gene expression. Results: A total of 24 670 tags representing 12 168 transcripts in the control mice and 26 378 tags representing 13 397 transcripts in the mice with lung injury were identified respectively. There were 11 transcripts increasing and 7 transcripts decreasing more than 10 folds in the lipopolysaccharide-treated mice. The most overexpressed genes in the mice with lung injury included serum amyloid A3, metallothionein 2, lipocalin 2, cyclin-dependent kinase inhibitor 1A, lactate dehydrogenase 1, melatonin receptor, S100 calcium-binding protein A9, natriuretic peptide precursor, etc. Mitogen activated protein kinase 3, serum albumin, complement component 1 inhibitor, and ATP synthase were underexpressed in the lung injury mice. Conclusions: Serial analysis of gene expression provides a molecular characteristic of acute lung injury.展开更多
This study examined the gene expression patterns of peripheral blood mononuclear cells （PBMCs） in patients with systemic lupus erythematosus （SLE） by using serial analysis of gene expression （SAGE） technology. F...This study examined the gene expression patterns of peripheral blood mononuclear cells （PBMCs） in patients with systemic lupus erythematosus （SLE） by using serial analysis of gene expression （SAGE） technology. Following the construction of serial analysis of gene expression （SAGE） library of PBMCs collected from 3 cases of familial SLE patients, a large scale of tag Sequencing was performed. The data extracted from sequencing files was analyzed with SAGE 2000 V 4.5 software. The top 30 expressed genes of SLE patients were uploaded to http：//david.niaid.nih.gov/david/ease.htm and the functional classification of genes was obtained. The differences among those expressed gene were analyzed by Chi-square tests. The results showed that a total of 1286 unique SAGE tags were identified from 1814 individual SAGE tags. Among the 1286 unique tags, 86.8% had single copy, and only 0.2% tags had more than 20 copies. And 68.4% of the tags matched known expressed sequences, 41.1% of which matched more than one known expressed sequence. About 31.6% of the tags had no match and could represent potentially novel genes. Approximately one third of the top 30 genes were ribosomal protein, and the rest were genes related to metabolism or with unknown functions. Eight tags were found to express differentially in SAGE library of SLE patients. This study draws a profile of gene expression patterns of PBMCs in patients with SLE. Comparison of SAGE database from PBMCs between normal individuals and SLE patients will help us to better understand the pathogenesis of SLE.展开更多
The development of genomic sequencing technology,from conventional techniques to state-of-the-art inventions,has greatly improved our understanding of genetic material.This review examines important advancements in se...The development of genomic sequencing technology,from conventional techniques to state-of-the-art inventions,has greatly improved our understanding of genetic material.This review examines important advancements in sequencing techniques and how they have revolutionized genomics research.Highthroughput capabilities made possible by next-generation sequencing(NGS)have enabled quick and affordable genomic analysis.Digital gene expression profiling was made possible by methods such as serial analysis of gene expression(SAGE),whereas long-read capabilities without amplification were analyzed by single-molecule sequencing,as demonstrated by Oxford Nanopore’s nanopore-based sequencing and PacBio’s single-molecule real-time(SMRT)technology.Synthetic long-read sequencing is one example of a hybrid technique that enhances genome assembly.New techniques,such as epigenetic sequencing,have revealed that DNA alterations are essential for gene control,and spatial transcriptomics has connected gene expression to tissue-specific patterns.Target analysis and knowledge of microbial ecosystems were further enhanced via the use of sophisticated techniques,including metagenomics and CRISPRCas9-based sequencing.When combined,these techniques allow researchers to examine microbial communities,transcriptome diversity,genomic structure,and epigenetic changes with new clarity.For example,single-cell sequencing has shown molecular heterogeneity between cells,and long-read sequencing has revealed intricate isoform variants.Personalized medicine has advanced owing to spatial transcriptomics,which targets gene expression in specific organs.Digital sequencing has also improved the sensitivity of mutation identification,transforming the diagnosis of the disease.The convergence of sequencing technologies has ushered in a new era of genomic studies,opening the door to groundbreaking findings in ecology,biology,and medicine.Future developments will improve knowledge of human genetics by further improving sequencing accuracy,affordability,and applicability.展开更多
Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal hist...Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal histopathological results and clinical parameters. However, this information is not sufficient to predict CKD progression risk reliably or to guide preventive interventions. Nowadays, the appearance of systems biology has brought forward the concepts of ＂-omics＂ technologies, including genomics, transcriptomics, proteomics, and metabolomics. Systems biology, together with molecular analysis approaches such as microarray analysis, genome-wide association studies （GWAS）, and serial analysis of gene expression （SAGE）, has provided the framework for a comprehensive analysis of renal disease and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. In particular, analysis of urinary mRNA and protein levels is rapidly evolving as a non-invasive approach for CKD monitoring. All these systems biological molecular approaches are required for application of the concept of ＂personalized medicine＂ to progressive CKD, which will result in tailoring therapy for each patient, in contrast to the ＂one-size-fits-all＂ therapies currently in use.展开更多
基金Supported by the National Natural Science Foundation of China (No. 50877004)
文摘Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feature to improve the accuracy and efficiency when they are used for pattern recognition and clustering analysis. A Poisson Model-based Kernel (PMK) was proposed based on the Poisson distribution of the SAGE data. Kernel Principle Component Analysis (KPCA) with PMK was proposed and used in feature-extract analysis of mouse retinal SAGE data. The computa-tional results show that this algorithm can extract feature effectively and reduce dimensions of SAGE data.
文摘Objective: To monitor the systemic gene expression profile in a murine model of lipopolysaccharide-induced acute lung injury. Methods: Acute lung injury was induced by intratracheal injection of lipopolysaccharide in 3 mice. Another 3 normal mice receiving same volume of normal saline were taken as the controls. The comprehensive gene expression profile was monitored by the recently modified long serial analysis of gene expression. Results: A total of 24 670 tags representing 12 168 transcripts in the control mice and 26 378 tags representing 13 397 transcripts in the mice with lung injury were identified respectively. There were 11 transcripts increasing and 7 transcripts decreasing more than 10 folds in the lipopolysaccharide-treated mice. The most overexpressed genes in the mice with lung injury included serum amyloid A3, metallothionein 2, lipocalin 2, cyclin-dependent kinase inhibitor 1A, lactate dehydrogenase 1, melatonin receptor, S100 calcium-binding protein A9, natriuretic peptide precursor, etc. Mitogen activated protein kinase 3, serum albumin, complement component 1 inhibitor, and ATP synthase were underexpressed in the lung injury mice. Conclusions: Serial analysis of gene expression provides a molecular characteristic of acute lung injury.
基金This project was supported by a grant form the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry (No [2002]247)
文摘This study examined the gene expression patterns of peripheral blood mononuclear cells （PBMCs） in patients with systemic lupus erythematosus （SLE） by using serial analysis of gene expression （SAGE） technology. Following the construction of serial analysis of gene expression （SAGE） library of PBMCs collected from 3 cases of familial SLE patients, a large scale of tag Sequencing was performed. The data extracted from sequencing files was analyzed with SAGE 2000 V 4.5 software. The top 30 expressed genes of SLE patients were uploaded to http：//david.niaid.nih.gov/david/ease.htm and the functional classification of genes was obtained. The differences among those expressed gene were analyzed by Chi-square tests. The results showed that a total of 1286 unique SAGE tags were identified from 1814 individual SAGE tags. Among the 1286 unique tags, 86.8% had single copy, and only 0.2% tags had more than 20 copies. And 68.4% of the tags matched known expressed sequences, 41.1% of which matched more than one known expressed sequence. About 31.6% of the tags had no match and could represent potentially novel genes. Approximately one third of the top 30 genes were ribosomal protein, and the rest were genes related to metabolism or with unknown functions. Eight tags were found to express differentially in SAGE library of SLE patients. This study draws a profile of gene expression patterns of PBMCs in patients with SLE. Comparison of SAGE database from PBMCs between normal individuals and SLE patients will help us to better understand the pathogenesis of SLE.
文摘The development of genomic sequencing technology,from conventional techniques to state-of-the-art inventions,has greatly improved our understanding of genetic material.This review examines important advancements in sequencing techniques and how they have revolutionized genomics research.Highthroughput capabilities made possible by next-generation sequencing(NGS)have enabled quick and affordable genomic analysis.Digital gene expression profiling was made possible by methods such as serial analysis of gene expression(SAGE),whereas long-read capabilities without amplification were analyzed by single-molecule sequencing,as demonstrated by Oxford Nanopore’s nanopore-based sequencing and PacBio’s single-molecule real-time(SMRT)technology.Synthetic long-read sequencing is one example of a hybrid technique that enhances genome assembly.New techniques,such as epigenetic sequencing,have revealed that DNA alterations are essential for gene control,and spatial transcriptomics has connected gene expression to tissue-specific patterns.Target analysis and knowledge of microbial ecosystems were further enhanced via the use of sophisticated techniques,including metagenomics and CRISPRCas9-based sequencing.When combined,these techniques allow researchers to examine microbial communities,transcriptome diversity,genomic structure,and epigenetic changes with new clarity.For example,single-cell sequencing has shown molecular heterogeneity between cells,and long-read sequencing has revealed intricate isoform variants.Personalized medicine has advanced owing to spatial transcriptomics,which targets gene expression in specific organs.Digital sequencing has also improved the sensitivity of mutation identification,transforming the diagnosis of the disease.The convergence of sequencing technologies has ushered in a new era of genomic studies,opening the door to groundbreaking findings in ecology,biology,and medicine.Future developments will improve knowledge of human genetics by further improving sequencing accuracy,affordability,and applicability.
文摘Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal histopathological results and clinical parameters. However, this information is not sufficient to predict CKD progression risk reliably or to guide preventive interventions. Nowadays, the appearance of systems biology has brought forward the concepts of ＂-omics＂ technologies, including genomics, transcriptomics, proteomics, and metabolomics. Systems biology, together with molecular analysis approaches such as microarray analysis, genome-wide association studies （GWAS）, and serial analysis of gene expression （SAGE）, has provided the framework for a comprehensive analysis of renal disease and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. In particular, analysis of urinary mRNA and protein levels is rapidly evolving as a non-invasive approach for CKD monitoring. All these systems biological molecular approaches are required for application of the concept of ＂personalized medicine＂ to progressive CKD, which will result in tailoring therapy for each patient, in contrast to the ＂one-size-fits-all＂ therapies currently in use.
