slide1
Download
Skip this Video
Download Presentation
welcome!!

Loading in 2 Seconds...

play fullscreen
1 / 64

SAGE TECHNOLOGY AND ITS APPLICATIONS - PowerPoint PPT Presentation


  • 180 Views
  • Uploaded on

welcome!!. SAGE TECHNOLOGY AND ITS APPLICATIONS. PRESENTED BY Dr. R.A.Siddique & Dr.Anand Kumar Animal Biochemistry Division N.D.R.I., Karnal (Haryana)India, 132001 E-mail: [email protected] WHAT IS SAGE?.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'SAGE TECHNOLOGY AND ITS APPLICATIONS' - paul2


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
sage technology and its applications

SAGE TECHNOLOGY AND ITS APPLICATIONS

PRESENTED BY

Dr. R.A.Siddique &

Dr.Anand Kumar

Animal Biochemistry Division

N.D.R.I., Karnal (Haryana)India, 132001

E-mail: [email protected]

what is sage
WHAT IS SAGE?
  • Serial analysis of gene expression (SAGE) is a powerful tool that allows digital analysis of overall gene expression patterns.
  • Produces a snapshot of the mRNA population in the sample of interest.
  • SAGE provides quantitative and comprehensive expression profiling in a given cell population.
slide4
SAGE invented at Johns Hopkins University in USA (Oncology Center) by Dr. Victor Velculescu in 1995.
  • An overview of a cell’s complete gene activity.
  • Addresses specific issues such as determination of normal gene structure and identification of abnormal genome changes.
  • Enables precise annotation of existing genes and discovery of new genes.
need for sage
NEED FOR SAGE…..
  • Gene expression refers to the study of how specific genes are transcribed at a given point in time in a given cell.
  • Examining which transcripts are present in a cell.
  • SAGE enables large scale studies of DNA expression; these can be used to create \'expression profiles‘.
slide6
Allows rapid, detailed analysis of thousands of transcripts in a cell.
  • By comparing different types of cells, generate profiles that will help to understand healthy cells and what goes wrong during diseases.
three principles underlie the sage methodology
THREE PRINCIPLES UNDERLIE THE SAGE METHODOLOGY:
  • A short sequence tag (10-14bp) contains sufficient information to uniquely identify a transcript provided that the tag is obtained from a unique position within each transcript
  • Sequence tags can be linked together to from long serial molecules that can be cloned and sequenced
  • Quantitation of the number of times a particular tag is observed provides the expression level of the corresponding transcript.
pre requisites
PRE REQUISITES:
  • Extensive sequencing techniques
  • Deep bioinformatic knowledge
  • Powerful computer software (assemble and analyze results from SAGE experiments)

Limited use of this sensitive technique in academic research laboratories

steps in brief
STEPS IN BRIEF…..
  • Isolate the mRNA of an input sample (e.g. a tumour).
  • Extract a small chunk of sequence from a defined position of each mRNA molecule.
  • Link these small pieces of sequence together to form a long chain (or concatamer).
slide11
Clone these chains into a vector which can be taken up by bacteria.
  • Sequence these chains using modern high-throughput DNA sequencers.
  • Process this data with a computer to count the small sequence tags.
sage technique in detail
SAGE TECHNIQUE (in detail)

Trap RNAs with beads

  • Messenger RNAs end with a long string of "As" (adenine)
  • Adenine forms very strong chemical bonds with another nucleotide, thymine (T)
  • Molecule that consists of 20 or so Ts acts like a chemical bait to capture RNAs
  • Researchers coat microscopic, magnetic beads with chemical baits i.e. "TTTTT" tails hanging out
  • When the contents of cells are washed past the beads, the RNA molecules will be trapped
  • A magnet is used to withdraw the bead and the RNAs out of the "soup"
cdna synthesis
cDNA SYNTHESIS
  • Double stranded cDNA is synthesized from the extracted
  • mRNA by means of biotinylated oligo (dT) primer.
  • cDNA synthesized is immobilised to streptavidin beads.
enzymatic cleavage of cdna
ENZYMATIC CLEAVAGE OF cDNA.
  • The cDNA molecule is cleaved with a restriction enzyme.
  • Type II restriction enzyme used.
  • Also known as Anchoring enzyme. E.g. NlaIII.
  • Any 4 base recognising enzyme used.
  • Average length of cDNA 256bp with ‘sticky ends’ created.
slide18

The biotinylated 3’ cDNA are affinity purified using strepatavidin

coated magnetic beads.

ligation of linkers to bound cdna
LIGATION OF LINKERS TO BOUND cDNA
  • These captured cDNAs are divided into two halves, then ligated to linkers A and B, respectively at their ends.
  • Linkers also known as ‘docking modules’.
  • They are oligonucleotide duplexes.
  • Linkers contain:
    • NlaIII 4- nucleotide cohesive overhang
    • Type IIS recognition sequence
    • PCR primer sequence (primer A or B).
slide20
Type IIS restriction enzyme – ‘tagging enzyme’.

Linker/docking module:

PRIMER TE AE TAG

cleavage with tagging enzyme
CLEAVAGE WITH TAGGING ENZYME
  • Tagging enzyme, usually BmsFI cleave DNA 14-15 nucleotides, releasing the linker –adapted SAGE tag from each cDNA.
  • Repair of ends to make blunt ended tags using DNA polymerase (Klenow) and dNTPs.
formation of ditags
FORMATION OF DITAGS
  • What is left is a collection of short tags taken from each molecule.
  • Two groups of cDNAs are ligated to each other, to create a “ditag” with linkers on either end.
pcr amplification of ditags
PCR AMPLIFICATION OF DITAGS
  • The linker-ditag-linker constructs are amplified by PCR using primers specific to the linkers.
isolation of ditags
ISOLATION OF DITAGS
  • The cDNA is again digested by the AE.
  • Breaking the linker off right where it was added in the beginning.
  • This leaves a “sticky” end with the sequence GTAC (or CATG on the other strand) at each end of the ditag.
concatamerization of ditags
CONCATAMERIZATION OF DITAGS
  • Tags are combined into much longer molecules, called concatemers.
  • Between each ditag is the AE site, allowing the scientist and the computer to recognize where one ends and the next begins.
cloning concatamers and sequencing
CLONING CONCATAMERS AND SEQUENCING
  • Lots of copies are required- So the concatemers are put into bacteria, which act like living "copy machines" to create millions of copies from the original
  • These copies are then sequenced, using machines that can read the nucleotides in DNA. The result is a long list of nucleotides that has to be analyzed by computer
  • Analysis will do several things: count the tags, determine which ones come from the same RNA molecule, and figure out which ones come from known, well-studied genes and which ones are new
how does sage work

2.(a) Add biotin-labeled dT primer:

1. Isolate mRNA.

2.(b) Synthesize ds cDNA.

3.(a) Bind to streptavidin-coated beads.

3.(b) Cleave with “anchoring enzyme”.

4.(a) Divide into two pools and add linker sequences:

4.(b) Ligate.

5. Cleave with “tagging enzyme”.

6. Combine pools and ligate.

7. Amplify ditags, then cleave with anchoring enzyme.

8. Ligate ditags.

How does SAGE work?

3.(c) Discard loose fragments.

9. Sequence and record the tags and frequencies.

slide31
Vast amounts ofdata is produced, which must be sifted and ordered for useful information tobecome apparent.

Sage reference databases:

  • SAGE map
  • SAGE Genie

http://www.ncbi.nlm.nih.gov/cgap

from tags to genes
FROM TAGS TO GENES……
  • Collect sequence records from GenBank
  • Assign sequence orientation (by finding poly-A tail or poly-A signal or from annotations)
  • Extract 10-bases -adjacent to 3’-most CATG
  • Assign UniGene identifier to each sequence with a SAGE tag
  • Record (for each tag-gene pair)
    • #sequences with this tag
    • #sequences in gene cluster with this tag

Maps available at http://www.ncbi.nlm.nih.gov/SAGE

differential gene expression by sage
DIFFERENTIAL GENE EXPRESSION BY SAGE
  • Identification of differentially expressed genes in samples from different physiological or pathological conditions.
  • Application of many statistical methods
    • Poisson approximation
    • Bayesian method
    • Chi square test.
slide36
SAGE software searches GenBank for matches to each tag
  • This allows assignment to 3 categories of tags:
    • mRNAs derived from known genes
    • anonymous mRNAs, also known as expressed sequence tags (ESTs)
    • mRNAs derived from currently unidentified genes
sage vs microarray
SAGE VS MICROARRAY
  • SAGE – An open system which detects both known and unknown transcripts and genes.
comparison
SAGE

Detects 3’ region of transcript. Restriction site is determining factor.

Collects sequence information and copy no.

Sequencing error and quantitation bias.

MICROARRAY

Targets various regions of the transcript.Base composition for specificity of hybridization.

Fluorescent signals and signal intensity.

Labeling bias and noise signals.

COMPARISON……
slide40

RECENT SAGE APPLICATIONS

  • Analysis of yeast transcriptome
  • Gene Expression Profiles in Normal and Cancer Cell
  • Insights into p53-mediated apoptosis
  • Identification and classification of p53-regulated genes
  • Analysis of human transcriptomes
  • Serial microanalysis of renal transcriptomes
  • Genes Expressed in Human Tumor Endothelium
  • Analysis of colorectal metastases (PRL-3)
  • Characterization of gene expression in colorectal adenomas and cancer
  • Using the transcriptome to analyze the genome (Long SAGE)
slide41

LIMITATIONS

  • Does not measure the actual expression level of a gene.
  • Average size of a tag produced during SAGE analysis is ten bases and this makes it difficult to assign a tag to a specific transcript with accuracy
  • Two different genes could have the same tag and the same gene that is alternatively spliced could have different tags at the 3\' ends
  • Assigning each tag to an mRNA transcript could be made even more difficult and ambiguous if sequencing errors are also introduced in the process
slide42
Quantitation bias:
      • Contamination of of large quantities of linker-dimer molecules.
      • low efficiency in blunt end ligation.
      • Amplification bias.
  • Depending upon anchoring enzyme and tagging enzyme used, some fraction of mRNA species would be lost.
slide43

Advances over SAGE

  • Generation of longer 3` cDNA from SAGE tags for gene identification (GLGI)
  • Long SAGE
  • Cap Analysis of Gene Expression (CAGE)
  • Gene Identification Signature (GIS)
  • SuperSAGE
  • Digital karyotyping
  • Paired-end ditag
long sage
Long SAGE
  • Increased specificity of SAGE tags for transcript identification and SAGE tag mapping.
  • Collects tags of 21bp
  • Different TypeII restriction enzyme-Mmel
  • Adapts SAGE principle to genomic DNA.
  • Allows localisation of TIS and PAS.
cage capped analysis of gene expression
CAGE (Capped Analysis of Gene Expression)
  • Aims to identify TIS and promoters.
  • Collects 21 bp from 5’ ends of cap purified cDNA.
  • Used in mouse and human transcriptome studies.
  • The method essentially uses full-length cDNAs , to the 5’ends of which linkers are attached.
  • This is followed by the cleavage of the first 20 base pairs by class II restriction enzymes, PCR, concatamerization, and cloning of the CAGE tags
slide47

Reverse transcription

AAAAA

  • Full strand DNA synthesis
  • ssDNA release

Biotin

AAAAA

Biotin

+

  • ssDNA capture
  • Second strand synthesis

x

Biotin

MmeI digestion of dsDNA

Mmel

+

Biotin

Ligation to second linker

Xma JI

Biotin

Mmel-PCR

PCR amplification

Biotin

Uni-PCR

  • Concatenation
  • Cloning
  • Sequencing

XmaJI tag1 tag2 XmaJI

micro sage
Micro SAGE
  • Requires 500-5000 fold less starting input RNA.
  • Simplifies by the incorporation of a ‘one tube’ procedure for all steps.
  • Characterization of expression profiles in tissue biopsies, tumor metastases or in cases where tissue is scarce.
  • Generation of region-specific expression profiles of complex heterogeneous tissues.
  • Limited number of additional PCR cycles are performed to generate sufficient ditag.
slide49
An expression profile can be obtained from as little as 1-5 ng of mRNA.
  • Comparison between the two…
supersage
SuperSAGE
  • Increases the specificity of SAGE tags and use of tags as microarray probes.
  • Type III RE EcoP15I – tag releasing
  • Collects 26 bp tags
  • Has been used in plant SAGE studies.
  • Study of gene expression in which sequence information is not available.
gene identification signature gis
Gene Identification Signature (GIS)
  • Identifies gene boundaries.
  • Collects 20bp LongSAGE tags from 3’ and 5’ end of the transcript.
  • Applied to human and mouse transcription studies.
digital karyotyping
DIGITAL KARYOTYPING
  • Analyses gene structure.
  • Identification amplification and deletion in several cancers.

PAIRED END DITAG

  • Identifies protein binding sites in genome.
  • Applied to identify p-53 binding sites in the human genome.
1 sage a looking glass for cancer
1. SAGE: A LOOKING GLASS FOR CANCER
  • Deciphering pathways involved in tumor genesisand identifying novel diagnostic tools, prognostic markers,and potential therapeutic targets.
  • SAGE is one of the techniquesused in the National Cancer Institute–funded Cancer GenomeAnatomy Project (CGAP).
  • A database with archived SAGE tag counts and on-line query toolswas created - the largest source of public SAGE data.
  • More than 3 million tags from 88 different librarieshave been deposited on the National Center for BiotechnologyEducation/CGAP SAGEmap web site (http://www.ncbi.nlm.nih.gov/SAGE/).
slide56
Several interesting patterns have emerged.
    • cancerous and normal cells derived from the same tissue typeare very similar.
    • tumors of the same tissue of origin but of differenthistological type or grade have distinct gene expression patterns
    • cancer cells usuallyincrease the expression of genes associated with proliferationand survival and decrease the expression of genes involved indifferentiation.
  • SAGE studies have been performed in patientswith colon, pancreatic, lung, bladder, ovarian, and breast cancers.
  • SAGE experiments validated in multiple tumor and normaltissue pairs using a variety of approaches, including Northernblot analysis, real-time PCR, mRNA in situ hybridization, andimmunohistochemistry.
  • Identification of an ideal tumor marker. E.g. Matrix metalloprotease1 in ovarian cancer is overexpressed.
p53 tumor supressor gene
p53- TUMOR SUPRESSOR GENE
  • p53 is thought to play a rolein the regulation of cell cycle checkpoints, apoptosis, genomicstability, and angiogenesis.
  • Sequence-specific transactivationis essential for p53-mediated tumor suppression.
  • The analysis of transcriptomes after p53 expressionhas determined that p53 exerts its diverse cellular functionsby influencing the expression of a large group of genes.
  • Identification of Previously Unidentified p53-Regulated Genes by SAGE analysis.
  • Variability exists with regardto the extent, timing, and p53 dependence of the expressionof these genes.
2 immunological studies
2. IMMUNOLOGICAL STUDIES
  • Only a few SAGE analysis has been applied for the study of immunological phenomena.
  • SAGE analyses were conducted for human monocytes and their differentiated descendants, macrophages and dendritic cells.
  • DC cDNA library represented more than 17,000 different genes. Genes differentially expressed were those encoding proteins related to cell motility and structure.
  • SAGE has been applied to B cell lymphomas to analyze genes involved in BCR –mediated apoptosis.- polyamine regulation is involved in apoptosis during B cell clonal deletion.
contd1
Contd…
  • LongSAGE has been used to identify genes of T cells with SLE that determine commitment to the disease.
  • Findings indicate that the immatureCD4+ T lymphocytes may be responsible for the pathogenesis of SLE.
  • SAGE has been used to analyze the expression profiles of Th-1 and Th-2 cells, and newly identified numerous genes for which expression is selective in either population.
  • Contributes to understanding of the molecular basis of Th1/Th2 dominated diseases and diagnosis of these diseases.
3 yeast transcriptome
3. YEAST TRANSCRIPTOME
  • Yeast is widely used to clarify the biochemical physiologic parameters underlying eukaryotic cellular functions.
  • Yeast chosen as a model organism to evaluate the power of SAGE technology.
  • Most extensive SAGE profile was made for yeast.
  • Analysis of yeast transcriptome affords a unique view of the RNA components defining cellular life.
4 analysis of tissue transcriptomes
4.ANALYSIS OF TISSUE TRANSCRIPTOMES
  • Used to analyze the transcriptomes of renal, cervical tissues etc.
  • Establishing a baseline of gene expression in normal tissue is key for identifying changes in cancer.
  • Specific gene expression profiles were obtained, and known markers (e.g., uromodulinin the thick ascending limb of Henle\'s loop and aquaporin-2 inthe collecting duct) were found.
references
REFERENCES
  • Maillard, Jean-Charles, et al., Efficiency and limits of the Serial Analysis of Gene Expression., Veterinary Immunol. and Immunopathol. 2005., 108:59-69.
  • Man, M.Z. et al., POWER-SAGE: comparing statistical tests for SAGE experiments., Bioinformatics 2000., 16: 953-959.
  • Polyak, K. and Riggins, G.J., Gene discovery using the serial analysis of gene expression technique: Implications for cancer research., J. of Clin. Oncol. 2001., 19(11):2948-2958.
  • Tuteja and Tuteja., Serial Analysis of Gene Expression: Applications in Human Studies., J. of Biomed. And Biotechnol. 2004., 2: 113-120.
  • Tuteja and Tuteja., Serial analysis of gene expression: application in cancer research., Med. Sci. Monit. 2004., 10(6): 132-140.
  • Velculescu, V.E. et al. Serial analysis of gene expression., Science 1995., 270:484-487.
  • Wing, San Ming., Understanding SAGE data., Trends in Genetics 2006., 23: 1-12.
  • Yamamoto, M., et al., Use of serial analysis of gene expression (SAGE) technology., J. of Immunol. meth.2001., 250:45-66.
ad