Hostname: page-component-848d4c4894-v5vhk Total loading time: 0 Render date: 2024-06-20T11:34:03.015Z Has data issue: false hasContentIssue false
  • English
  • Français

A modified GLGI method for identification of novel porcine genes from long serial analysis of gene expression tags

Published online by Cambridge University Press:  02 August 2007

Tang Zhong-Lin ,
Li Yong ,
Zhao Shu-Hong ,
Liu Bang ,
Fan Bin  and
Li Kui
Tang Zhong-Lin
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100094, China
Li Yong
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
Zhao Shu-Hong
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
Liu Bang
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
Fan Bin
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
Li Kui*
Affiliation:
Key Laboratory of Animal Heredity and Breeding, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100094, China
*
*Corresponding author. E-mail: likuihau@yahoo.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Combining the long serial analysis of gene expression (LongSAGE) and the generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification (GLGI) technique, a new strategy called modified GLGI (M-GLGI) was developed to isolate unknown 3′ expressed sequence tags (ESTs) and discover novel genes. A 17 bp LongSAGE tag was used as sense primer instead of a 10-base SAGE tag; PCR reaction was performed under an appropriate annealing temperature for each tag; universal DNA polymerase was used in PCR amplification instead of Pfu enzyme; a common cloning strategy using pMD-18T vector and Escherichia coli DH5α cells were used instead of a special vector and competent cells. Moreover, ESTs isolated by M-GLGI had 3′ ends with the polyadenylation signals and poly(dA) tails. This method is more sensitive for identifying genes expressed in low abundance than conventional EST sequencing.

Keywords

long serial analysis of gene expression tagGLGI modificationnovel gene identification
Type
Research Article
Information
Chinese Journal of Agricultural Biotechnology , Volume 4 , Issue 2 , August 2007 , pp. 111 - 115
Copyright
Copyright © China Agricultural University and Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

First published in Journal of Agricultural Biotechnology 2007, 15(1): 15–19

References

Bishop, JO, Morton, JG, Rosbach, M and Richardson, M (1974) Three abundance classes in HeLa cell messenger RNA. Nature 250(463): 199–204.CrossRefGoogle ScholarPubMed
Boon, WM, Beissbarth, T, Hyde, L, et al. (2004) A comparative analysis of transcribed genes in the mouse hypothalamus and neocortex reveals chromosomal clustering. Proceedings of the National Academy of Sciences of the USA 101(41): 14942–14977.CrossRefGoogle ScholarPubMed
Chen, JJ, Rowley, JD and Wang, SM (2000) Generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification. Proceedings of the National Academy of Sciences of the USA 97(1): 349–353.CrossRefGoogle ScholarPubMed
Chen, JJ, Lee, S, Zhou, GL and Wang, SM (2002a) High-throughput GLGI procedure for converting a large number of serial analyses of gene expression tag sequences into 3′ complementary DNAs. Gene, Chromosomes and Cancer 33(3): 252–261.CrossRefGoogle Scholar
Chen, JJ, Sun, M, Lee, S, Zhou, GL, Rowley, JD and Wang, SM (2002b) Identifying novel transcripts and novel genes in the human genome by using novel SAGE tags. Proceedings of the National Academy of Sciences of the USA 99(19): 12257–12262.CrossRefGoogle ScholarPubMed
Halaschek-Wiener, J, Khattra, JS, McKay, S, et al. (2005) Analysis of long-lived C. elegans daf-2 mutants using serial analysis of gene expression. Genome Research 15(5): 603–615.CrossRefGoogle ScholarPubMed
Lee, S, Zhou, G, Clark, T, Chen, J, Rowley, JD and Wang, SM (2001) The pattern of gene expression in human CD15+ myeloid progenitor cells. Proceedings of the National Academy of Sciences of the USA 98(6): 3340–3345.CrossRefGoogle ScholarPubMed
Matsumura, H, Reich, S, Ito, A, et al. (2003) Gene expression analysis of plant host–pathogen interactions by SuperSAGE. Proceedings of the National Academy of Sciences of the USA 100(26): 15718–15723.CrossRefGoogle ScholarPubMed
Ryu, EJ, Angelastro, JM and Greene, LA (2005) Analysis of gene expression changes in a cellular model of Parkinson disease. Neurobiology of Disease 18(1): 54–75.CrossRefGoogle Scholar
Saha, S, Sparks, AB, Rago, C, et al. (2002) Using the transcriptome to annotate the genome. Nature Biotechnology 20(5): 508–512.CrossRefGoogle ScholarPubMed
Siddiqui, AS, Khattra, J, Delaney, AD, et al. (2005) A mouse atlas of gene expression: Large-scale digital gene-expression profiles from precisely defined developing C57BL/6J mouse tissues and cells. Proceedings of the National Academy of USA 102(51): 18485–18490.CrossRefGoogle ScholarPubMed
Sun, M, Zhou, GL, Lee, S, Chen, JJ, Shi, RZ and Wang, SM (2004) SAGE is far more sensitive than EST for detecting low-abundance transcripts. BMC Genomic 5(1): 1.CrossRefGoogle ScholarPubMed
Tang, ZL, Li, Y, Li, K, et al. (2007) Long SAGE analysis of skeletal muscle at three prenatal stages in Tongcheng and Landrace pigs. Genome Biology 8(6): R115.CrossRefGoogle Scholar
Velculesscu, VE, Zhong, L, Vogelstein, B and Kinzler, KW (1995) Serial analysis of gene expression. Science 270(5235): 484–487.CrossRefGoogle Scholar
Velculescu, VE, Zhang, L, Zhou, W, et al. (1997) Characterization of the yeast transcriptome. Cell 88(2): 243–251.CrossRefGoogle ScholarPubMed
Wahl, MB, Caldwell, RB, Kierzek, AM, et al. (2004) Evaluation of the chicken transcriptome by SAGE of B cell and the DT40 cell line. BMC Genomics 5(1): 98.CrossRefGoogle ScholarPubMed
Wang, SM, Fears, SC, Zhang, L, Chen, JJ and Rowley, JD (2000) Screening poly(dA/dT)-cDNAs for gene identification. Proceedings of the National Academy of Sciences of the USA 97(8): 4162–4167.CrossRefGoogle ScholarPubMed
Yamashita, T, Hashimoto, S, Kaneko, S, et al. (2000) Comprehensive gene expression profile of a normal human liver. Biochemical and Biophysical Research Communications 269(1): 110–116.CrossRefGoogle ScholarPubMed
Zhang, L, Zhou, W, Velculescu, VE, et al. (1997) Gene expression profiles in normal and cancer cells. Science 276(5316): 1268–1272.CrossRefGoogle ScholarPubMed