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Analysis of Expressed Sequence Tags (EST) for Gene Expression Profiling in Cancer Research

This document outlines the utility of Expressed Sequence Tags (EST) in gene expression profiling and their significance in cancer research. ESTs are obtained through automated sequencing of cDNA clones, providing valuable data for understanding gene expression patterns in various tissues, including normal and cancerous samples. The analysis covers databases such as dbEST and methodologies like Serial Analysis of Gene Expression (SAGE), highlighting their role in discovering new genes, mapping genomes, and comparing expression profiles. Tools for expression profiling, like NCKU.Xcrunch, are also discussed.

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Analysis of Expressed Sequence Tags (EST) for Gene Expression Profiling in Cancer Research

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  1. EST EXPRESSION PROFILE ANALYSIS何中良 助理教授 國立成功大學醫學院病理學科 國立成功大學分子醫學研究所

  2. EST Expressed Sequence Tags

  3. EST Expressed Sequence Tags are partial, single-pass sequences from either end of a cDNA clone.

  4. Expressed Sequence Tag (EST) were generated by automated partial DNA sequencing of randomly selected cDNA clones from individual cDNA libraries.

  5. EST sequences are real experimental data with about 1% per base error rate.

  6. Statistics • dbEST

  7. Cancer Genome Anatomy Project(CGAP) • Tissue • Normal • Precancer • Cancer

  8. Cancer Genome Anatomy Project(CGAP) • Tissue preparation • Bulk • Microdissected • Cell lines • Flow sorted

  9. Cancer Genome Anatomy Project(CGAP) • cDNA library protocols • Non-normalized • Normalized • Subtraction • (In "native" non-normalized libraries, clone frequency reflects mRNA abundance)

  10. Cancer Genome Anatomy Project(CGAP) • cDNA library protocols

  11. Cancer Genome Anatomy Project(CGAP) • cDNA libraries • Library finder • Library list • Library browser • cDNA Library navigator • Unified library database • Example • Summary

  12. EST cDNA library projects • CGAP • MGC • ORESTES • And others

  13. Serial Analysis of Gene Expression(SAGE) • Diagram 1 • Diagram 2

  14. Serial Analysis of Gene Expression(SAGE) • Restriction enzymes • SAGE vs. EST • Shorter tags (9~13 bp) • Same sequencing power, more information • More sensitive to sequencing error • Tag-gene mapping is much messier

  15. Unigene • Automatic clustering of ESTs • Unique set of human and mouse genes • Unigene and genome mapping • Diagram

  16. Gene Index • TGI: TIGR Gene Indices • EGI: EuroGeneIndexes • MIPS • STACK

  17. EST as tools (1) • Discover new genes • Genome mapping • cDNA assembly • Cluster only: Unigene • Cluster & assemble (alignment; consensus) • TGI; EGI; MIPS; STACK • Assemble & curate • EGAD

  18. EST as tools (2) • Alternative splicing • Expression profile comparison • Digital differential display • Xprofiler • Digital Gene Expression displayer (DGED) • Virtual northern

  19. Expression Profiles • Protein profiles • mRNA profiles

  20. How to obtain expression profiles • Protein • Proteomics • Protien chips • mRNA • EST cDNA libraries • SAGE • Microarray

  21. Tools to use mRNA profiles • Digital differential display • Xprofiler • Digital Gene Expression Displayer (DGED) • Virtual northern • BodyMap

  22. Our tools • NCKU Xcrunch (eXpression profile CRUNCHer) • Digital differential display • Digital FISH • Digital Northern

  23. Our database • Automatically download the expression profiles from Unigene Library Browser • Summary

  24. Digital differential display

  25. Digital FISH (1) • Goal: To narrow down genes responsible for our favorite cancers in certain chromosomal regions.  (For example: renal cancer & chromosome 3p22-23)

  26. Digital FISH (2) • Rationale: Genes related to kidney tumors should be expressed in kidney tissue (normal and/or abnormal), i.e., should be found in kidney related EST cDNA libraries.  (exceptions: viral gene products; Hormone-like effect)

  27. Digital FISH (3) • Step 1: Get the Unigenes located in the chromosomal regions. • Step 2: Get the Unigenes from kidney-related cDNA libraries. • Step 3: What Unigenes are present in both 1 and 2?

  28. Digital Northern

  29. www.binfo.ncku.edu.tw/xcrunch/ • Database • Xcrunch • Some explanation

  30. Acknowledgement • 嚴國何 (the programmer of NCKU Xcrunch) • 李強 教授

  31. The Mammalian Gene Collection(MGC) • NIH • To identify and sequence a representative full open reading frame (ORF) clone for each human and mouse gene

  32. The Mammalian Gene Collection(MGC) • Libraries with up to at least 3 to 4 kb cDNA inserts • EST sequences (5’ & 3”; Accuracy same as ESTs) • Full-length candidates: submitted for full insert sequencing (at least 99.99% accuracy; Same as HGP) Back

  33. ORF expressed sequence tags(ORESTES) • Reverse transcription-PCR using arbitrarily selected, nondegenerae primers under low-stringency • High percentage of fragments in the midportions of genes • Normalization of the sequence population

  34. From Neto et al. Shotgun sequencing of the human transcriptome with ORF expressed sequence tags. 2000. PNAS 97(7) p3491-3496.

  35. Full length cDNA projects • MGC • FLJ • RIKEN • DKFZ

  36. Number of cDNA libraries > 1600 sequences Homo sapiens 6904 312 Mus musculus 536 196 Rattus norvegicus 225 40 Xenopus laevis 52 30 Danio rerio (zebrafish) 45 12 Arabidopsis thaliana 74 8 Back

  37. Back

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