Program of Study Dan Smith

1
Program of Study Dan Smith

• March 30th, 2007

2
Undergraduate Classes
3
Graduate Classes

• Core Curriculum Finished
• MCB 511 Research Perspectives
• MCB 525 Techniques in Molecular and Cellular
  Biology
• MCB 553 Structure and Function of Eukaryotic
  Cells
• MCB 554 Genome Organization, Structure, and
  Maintenance
• MCB 555 Genome Expression and Regulation
• MCB 556 Cell Signaling and Development
• MCB 557 Scientific Skills and Ethics
• MCB 610 Internship (rotations)
• Electives Taken So Far
• BB 650 Protein Evolution
• MB 534 Virology

4
Thesis

• Chapter 1 Prediction of Transcription Factor
  Binding Sites
• Chapters 2 3 Undecided
• A few ideas

5
Chapter 1 Regulons

• Goal
• To identify novel transcription factor binding
  sites in silico, then
• Verify predictions with wet-lab experiments.
• Why
• A common binding site may imply a common
  expression pattern, allowing
• Metabolic modeling
• Insight into protein coordination.

6
Chapter 1 Regulons

• Site Criteria
• Within 300nt upstream of a gene.
• Common to at least three genes.
• Similarly conserved in environmental fragments.
• Example

C134_0635 _at_-16 AGAAC(AAAACA)AGAAC SOS txn
repressor 0634
umuC C134_0921 _at_-40 AGAAC(ACTTGT)AGAAC
repressor LexA C134_1160 _at_-68
AGAAC(ATTTAT)AGAAC phosphomannomutase
7
Chapter 1 Regulons

• Wet-Lab Experimental Validation

Likely Transcription Factor, with added His-Tag,
is bound to column
8
Chapter 1 Regulons

• Wet-Lab Experimental Validation

DNA with predicted binding sites is added, then
washed.
9
Chapter 1 Regulons

• Wet-Lab Experimental Validation

Bound DNA is analyzed for length, which indicates
the binding site on it.
10
Chapters 2 3

• Some work already done on assembling
  environmental fragments.
• Longest contig so far is 19,214 nt
• combined 357 fragments 18x coverage
• Similar to Extreme Assembly method by Rusch,
  Venter, et al. (PLoS, Mar 07)
• tBLASTx (me) vs. Celera nucleotide (them)
• Mate-Pairs (me) vs. No Mate-Pairs (them)
• They got contigs up to 900,000 nt long.

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Chapters 2 3

• Other Ideas?

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13
Supplementary Slides
14
How Predictions are Made

• Align environmental fragments of the upstream
  region for each SAR11 gene.

SAR11 Genome
Gene of Interest
1
tBLASTn (1e-50)
BLASTn (1e-5)
Environmental Fragment
2
Add to alignment
3
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How Predictions are Made

• Make a position-specific scoring matrix (PSSM)

Seq1 T G A A C A G A A C C Seq2 A
G A A C T G A A C C Seq3 A G A A C
G G A A C T Seq4 T G A A C A G A
A C C Seq5 C G A A C A G A A C T
1
A .4 0 1 1 0 .6 0 1 1 0 0 T .4
0 0 0 0 .2 0 0 0 0 .4 C .2 0 0 0 1
0 0 0 0 1 .6 G 0 1 0 0 0 .2 1 0
0 0 0
2
3
16
How Predictions are Made

• Align PSSMs from different genes (all vs. all)

A .2 0 1 1 0 .2 0 1 1 0 0 T 0 0 0
0 0 .2 0 0 0 0 .4 C .2 0 0 0 1 0 0 0
0 1 .4 G .6 1 0 0 0 .6 1 0 0 0 .2 ?
.6 0 0 0 0 .4 0 0 0 0 .2
.4 0 1 1 0 .6 0 1 1 0 0 .4 0 0 0 0
.2 0 0 0 0 .4 .2 0 0 0 1 0 0 0 0 1
.6 0 1 0 0 0 .2 1 0 0 0 0
1
No difference between PSSMs for these 8
nucleotide positions.
2
3
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