Transcriptome

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Transcriptome

• Gene Discovery
• Quantitation of Gene Expression

BIO520 Bioinformatics Jim Lund
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WHY?

• The genes expressed determine the state of the
  cell.
• Signaling.
• Metabolic capabilities.
• Differentiation state (cell type).
• Response to changes in environment.
• Verifies gene predictions.
• Transcriptional regulation
• Normal vs. abnormal
• Conditional expression

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Transcriptome Analysis

• Gene (transcript) discovery
• transcripts
• alternative splicing/processing
• Transcript assays
• Promoter analysis
• Transcription Factors
• Cellular control networks

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Gene Discovery

• Inference from genomic DNA
• Prokaryotes fungi OK
• cDNA characterization
• EST
• SAGE

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EST (Expressed Sequence Tag)

• Sequence cDNA libraries
• proportional libraries
• subtracted or normalized libraries
• Which end?
• 5 or 3 or Whole

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Library Type

• regular or proportional
• Subtracted
• Miss alternate transcripts
• normalized

• Tissue
• Primer
• dT vs random

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Ideal cDNAs
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Real cDNAs
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Which end?

• Whole cDNA
• BEST HARDEST (Long)
• 3-end
• Consistent technically, limited information
• 5end
• Coding identity highest
• 5 AND 3
• Good, but technical informatic challenge

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(No Transcript)
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EST Data Analyses

• Clustering Analysis
• Assemble ESTs into genes.
• Alternative splicing forms
• Find coding SNPs.
• Truncated, unspliced, and junk ESTs can be
  misleading
• Project Unigene
• Program stackPACK
• Frequency analysis
• Digital Differential Display
• DDD is a computational method for comparing
  sequence-based gene representation profiles among
  individual cDNA libraries or pools of libraries.

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EST Results (old)

• Known genes (30)
• Similarities to other ORFs, ESTs (30)
• Infer Function?
• Novel Class (30, ? w/ time)

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Typical Progress/Results

• Humans
• 6,694,833 ESTs
• 124,179 clusters (sets)
• 29,000 sets contain EST and mRNA seqs.
• CGAP EST library plateau broken by
• different tissues, different states
• normalized libraries

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Data Quality Considerations

• 99 correct data (1 errors!).
• Frameshifts-effects depend on tools
• BLASTX tool to find
• How sensitive
• TBLASTX, TBLASTN to use in other projects
• How sensitive

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Gene Expression Assay

• EST (Poor method)
• SAGE
• Microarray Hybridization
• Transcriptional Fusions
• GFP, LacZ fusions

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Serial Analysis of Gene Expression (SAGE)

• Collect mRNA
• Isolate short oligomers from each transcript.
• Ligate together the oligomers and clone them.
• Sequence thousands of clones.
• Map the 1x104 1x105 oligomers to their genes.
• Find which genes are transcribed and their
  relative expression levels.
• http//www.sagenet.org (Vogelstein at JHU)

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SAGE technique

• Prepare biotin labeled cDNA
• Cleave with anchoring enzyme (NlaIII)

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SAGE technique

• Ligate on linkers
• Cleave with tagging enzyme (BsmFI)

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SAGE technique

• Ligate, PCR, and gel purify ditags (102bp).
• Recleave with anchoring enzyme (NlaIII), ligate
  to form concatemers.
• Size select, clone and sequence concatemers.

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Colon cancer vs. normal colon epithelium (SAGE)
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Microarray Hybridization

• Determine gene expression by parallel
  hybridization of labeled cDNA to DNA attached to
  a fixed support.
• http//cmgm.stanford.edu/pbrown/

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Microarray Hybridization

• Producing chips
• Producing probes / reading arrays
• Analyzing and interpreting data

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Transcriptional Array
orf 1
orf 2
orf 3
1
2
3
3 cm
4
5
6
200 spots
7
8
9
2
40,000 dot/9 cm
or
Condition 1
Condition 2
gt All human genes
mRNA
mRNA
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Transcriptional Array-1
orf 1
orf 2
orf 3
1
2
3
3 cm
4
5
6
200 spots
7
8
9
2
40,000 dot/9 cm
or
Condition 1
Condition 2
Condition 2
gt All human genes
mRNA
mRNA
mRNA
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Transcriptional Array-2
orf 1
orf 2
orf 3
1
2
3
3
1
2
3 cm
6
4
5
6
200 spots
7
8
9
7
8
2
40,000 dot/9 cm
or
Condition 1
Condition 2
gt All human genes
mRNA
mRNA
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Microarray Technologies

• Spotted arrays (Brown et al.)
• Spot arrays on glass slides
• PCR fragments
• Long (50-70bp) oligo arrays
• Synthesis
• Affymetrix (www.affymetrix.com)
• High density array of 25 bp oligos
• Made using light directed oligonucleotide
  synthesis and photolithography
• Agilent, CombiMatrix
• Made using light directed oligonucleotide
  synthesis and mirrors.

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Spotted Arrays
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Print Quill
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Spotted microarray image
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Affymetrix photolithographic technology

• Lithographic masks are used to either block or
  transmit light onto specific locations of the
  array.
• The surface is then flooded with a solution
  containing either adenine, thymine, cytosine, or
  guanine, and coupling occurs only in those
  regions on the glass that have been deprotected
  through illumination.
• The coupled nucleotide also bears a
  light-sensitive protecting group, so the cycle
  can be repeated.
• Microarray is built as the probes are synthesized
  through repeated cycles of deprotection and
  coupling.
• Typically ends at 25 bps.)
• Current arrays have 1.3 million unique features
  per array.

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GeneChip Expression Assay Design
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Affymetrix GeneChips Expression Analysis

• Available for humans and model organisms.
• Made only by Affymetrix.
• Chip designs change slowly.
• GeneChips
• Human 50,000 RefSeq genes and ESTs
• C. elegans 22,500 genes (12/00 genome
  annotation)
• Rat 230 30,000 genes, ESTs
• Yeast 6100 gene set
• Tiling arrays for model organisms
• http//affymetrix.com

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Quantitation of fluorescence signals (Image to
data)

• Hybridization, scan in chip image.
• Gridding
• Determine where the spots are.
• Spot intensity and local background
  determination.
• Normalization
• Adjust to make the red and green total signal
  intensities the same.
• Gene expression ratio.
• Red channel/green channel.
• Programs
• ScanAlyze, http//rana.lbl.gov/EisenSoftware.htm
• GenePix, http//www.axon.com/gn_GenePixSoftware.ht
  ml

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Microarray data
Big tables of numbers!
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Viewing microarray data
Clustergram
Scatter plot log(ch1) vs log(ch2)
M vs A signal vs expression change
Volcano plot log(expr) vs p-value