billions and billions of bases how does a biologist maintain a grip on reality?

Billions and Billions of Bases

How does a biologist maintain a grip on reality?

46 chromosomes~3 billion nucleotides

The Human Genome Project

One millionth of total

The Human Genome ProjectTGAGACACATATTTTTGATATTCCAGTTGTTGCAATCGAATGTAAAACATATTTAGATCTTTAAATGTATGGTACATTCAAGATCCAACCTTCATTCTAGTGTTTAAAGAGAACTGATTTGTTTGCAGGGGCAGGAGGCTTTGGTTTAGGTTTTGAAATGGCAGGCTTCTCTGTACCTTTATCTGTTGAAATTGATACCTGGGCTTGTGATACACTACGCTACAACCGCCCTGATTCAACAGTTATTCAAAATGATATCGGTAACTTTAGTACAGAAAATGACGTTAAGAATATCTGCAACTTTAAACCTGATATTATTATTGGCGGGCCTCCATGCCAGGGATTTAGTATTGCTGGGCCAGCCCAAAAAGATCCTAAAGATCCTAGAAATGGTTTATTCATCAACTTTGCACAATGGATAAAATTTCTTGAACCTAAAGCGTTTGTCATGGAAAACGTAAAAGGATTGCTATCAAGGAAAAATGCAGAAGGTTTTAAAGTTATAGATATTATTAAGAAAACATTTGAAGAACTTGGTTATTTTGTCGAAGTATGGGTTTTAAATGCTGCGGAATATGGCATTCCGCAAATTAGAGAACGTATTTTTATTGTTGGCAATAAAAAAGGTAAAGTACTAGGTATTCCTAAAAAAACACATTCTCTGCAATTTTTAAATTTAAATAGGTCTCAATTATCGATCTTCGATGATATGAGTATTATACCTGCACTAACTTTGTGGGACGCAATATCAGACTTACCAGAACTTAATGCGCGTGAAGGAAGTGAAGAGCAACCCTATCATTTAAAACCTCAAAATACTTATCAGACTTGGGCTAGAAATGGTAGTGCTACGCTTTACAATCATGTTGCAATGG

AACATTCTGACCGTTTAGTAGAACGTTTCCGGCATATAAAATGGGGTGAATCCAGTTCGGATGTATCTAAAGAACATGGAGCTAGACGACGTAGTGGTAATGGTGAATTATCAAACAAATCATATGATCAGAATAATCGCCGTTTAAATCCTCATAAACCGTCTCACACTATTGCTGCGTCATTCTATGCTAATTTTGTCC

ATCCTTTTCAACATCGAAATTTAACAGCCCGTGAAGGAGCTAGAATCCAATCTTTTCCAGATAACTATAGATTTTTTGGAAAAAAAACTGTCGTATCTCATAAACTATTGCATCGA GAAGAAAGATTTGATGAAAAATTTCTTTGTCAATATAATCAAATCGGTAATGCTGTACCCCCTCTTCTCGCTAAAGTAATTGCACATCATCTTCTAGAGAAATTAGAGTTATGCCAACAACTGATAGAAATCCTCTAGTGCATGGATCAAATCTTGAACAAAAAGAGAATCATCGTACAAAATACAGAGATACTGAAAGCAGGACTTTCCTTAGAGAAATCAGAACTGAATATGACAAATGGCATAAAGCAAATATGAACCTGGTTGGACCAAAATCAGAAATTACTGACCAAGATGATTCAATTATTACTCAAAGAGTGGAACTTCTCACTAAATATAAAGATTTTTTAGATCAGCAGCATTATGCAGAAAAATTTGATTCAAGATCCAACCTTCATTCTAGTGTTTTAGAGACCATTTATAAAGTAAATCTTTAGACGACTAGACGACGTAGCATAATACGAGTCATAACGGCATATATG GCAGCCTCACTCATTTCTGGGAGACGCTCATAATCCTTACTGAGACGACGGTACTGGTTTAACCAGCCAAATGTTCTTTCTACTACCCACCGTTTGGGCAAAACCTGAAATTCTTGATTAGTACGCCGGATTACCTCAACATGAGCTTGAATCATCAGCCAAACAGAGAGCGCAAATTTATCACCGTCATAGCCGGAATCAACCCAGATGACTTCAACTTTTTCCAGTAATTCTGGACGCTCTTCTAACAGTTCCATCAAAGTATAGGCGGCAAGTAATCTTTCTCCAGCATTTGCTTCACTTACAACCACTTTTAACAAAAGTCCCAGACTATCAACCAAAGTTTGCCGCTTTCGTCCTTTTACCTTCTTGCCACCATCAAAACCGTACACATCCCCCTTTTTTCAGTCGTTTTTACCGACTGGCTGTCTGCCGCGATCGCCGTGGGTTGAGTTGACTTCCCCATTTTTTGACGAACTTGATCGCGCAAAGTATGATTCATTTCAGTTGAACTAGGAGGAAAATCCCCTGGAAGCATATCCCACTGACAACCTGTTTT

CAGATGGTAGTAGATAGCGTTGCATACTTCTCGCATATCAGTTGTTCGGGGATGCCCACCGCATTTAGCGGGTGGAATCAAAGGAGCTAAAATTGCCCATTCTGAGTCATTAAGGTCTGTAGAATAAGACTTTCGTCTCATTGTTTCCTATGTAAATACACTCTACAAACAGTATCTTATCGCTGCCTTTTTATCTTAGCTCTCCTTTAGATTTACTTTATAAATAGCCTCTTAGAAGAATTTCTTTATTATTTATTTAAAGATTTAGTACAAGATTTCGGGCAGAACGCTCTTATTGGTAAGTCACACACGTTCAAAGATATTTTCTTCGTACCACCAAAATATTCTGAAATGCTCAAGCGACCTTATGCGCGAATTGAGAGAAAAGATCATGATTTCGTAATTGGTGCAACTGTTCAAGCATCGCTTGAAGCAGCACCTCCTCCAGAACAAAACCATGCTTGAGGGATCTTCACGCGCAGCAGAGGATTTAAAAGCGAGAAATCCTAACAGTTTATACCTTGTGGTTATGGAATGGATAAAACTGACCAATGATGTAAATTTACGAAAATATAAAGTTGATCAAATTTATGTACTACGTCAGCAAAAAAATACTGATAGAGAGTTTAGGTATGAGTCAACTTACATAAAAAAT

The Human Genome ProjectAATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT

The Human Genome Project

A Walk in the Forest

* Photo courtesy of www.webshots.com

Observation

* Photos courtesy of www.webshots.com and Peter Smallwood

Experiment

* Photos courtesy of www.webshots.com and Peter Smallwood

Filters: Information reducersSquirrel filter

Filters: Information reducersMolecule filter

Filters: Information reducersSequence filter

How organism is made

How organism works

TCTACTTATA TTCAATCCAC AGGGCTACAC CTAGTTCTTG AAGAGTCTGT TGAATGAACA CATACATGGT TTATCTGTTT TTCTGTCTGC TCTGACCTCT GGCAGCTTTC CACTAGTTTC TGGATTTCGG AACTCTAGCC TGCCCCACTC TTAGATAAAC GAACCTTAGT GACTTCTGCT ATACCAAAGT CTCCACGCCC CTCCGTAAAC CTCTAACATG ATGTCAGCAA ATATTAAAAA TGAATAAACT TTGTTAAAGG TACAAATGAA AATTAGCAAA AAGAGTTTAA AGTTAAAAAC GAATTGCAGT CATTCTAGGG AAACCTGTAT GGTTACATGA ACTGCCTAAA AAACAAGCTA TTATATATTT TAAGAAATTA ATTGCAATTA ATTTCCTGGG CCCCAGCTGT CATTAAAAAG AGGCAAATAC AGCCAAGGAC GACAGCACTG ACCCTCAAGA AGGCACCGGC TGACAGACAG GCTGAAATTC CGCTGAGAGC AGAGTGGTAC ATTGAACCCT CCCTGCACCA GGTCTTTCCT GTGGGCACTG AGTGCAGACA ATGAATGACT GAACGAACGA TTGAATGAAA AGAAATGAGA TATGAGGCAA TCACAGCATC AGGTGACCTT AGTATCTATT CTCGGGAGCG CACGGCTCTA AAGAGGCCCA TATCCAGGCA CCTTTAGATG CAAGAAGGAG GAAACAGCTC GAAATCCCTG AGGCCGGAGG GTCAAGAACT CTCCACCGGC GGCAGCGGCC CCCCGGCCTA AGGCTGCCTG TGCTATAAAT ACGCGGCCCA TTCCCTGGGC TCGGCGGGAC AGATAACATG AATGTGCCCT

CTCCGTAAAC CTCTAAC...

From Sequence to OrganismHow does Nature do it?

ATGACTTATGATCAACGCACAGGGCTA Met-Thr-Tyr-Asp-Gln-Arg-Thr-Gly-Leu...

Genetic code Rules of folding

Active site



Active site

Cell interaction

Metabolism,Architecture




Genetic code

Active site

Gives us:

• Custom antibiotics




Gives us:

• Custom antibiotics • Custom antibodies• Custom enzymes• New materials


Active site



Genetic code

Rules of transcriptional and post-transcriptional control

• Begin transcription• End transcription• Splice transcript• Begin translation

ATGACTTATGATCAACGCACAGGGCTA3%

?

TCTACTTATA TTCAATCCAC AGGGCTACAC CTAGTTCTTG AAGAGTCTGT TGAATGAACA CATACATGGT TTATCTGTTT TTCTGTCTGC TCTGACCTCT GGCAGCTTTC CACTAGTTTC TGGATTTCGG AACTCTAGCC TGCCCCACTC TTAGATAAAC GAACCTTAGT GACTTCTGCT ATACCAAAGT CTCCACGCCC CTCCGTAAAC CTCTAACATG ATGTCAGCAA ATATTAAAAA TGAATAAACT TTGTTAAAGG TACAAATGAA AATTAGCAAA AAGAGTTTAA AGTTAAAAAC GAATTGCAGT CATTCTAGGG AAACCTGTAT GGTTACATGA ACTGCCTAAA AAACAAGCTA TTATATATTT TAAGAAATTA ATTGCAATTA ATTTCCTGGG CCCCAGCTGT CATTAAAAAG AGGCAAATAC AGCCAAGGAC GACAGCACTG ACCCTCAAGA AGGCACCGGC TGACAGACAG GCTGAAATTC CGCTGAGAGC AGAGTGGTAC ATTGAACCCT CCCTGCACCA GGTCTTTCCT GTGGGCACTG AGTGCAGACA ATGAATGACT GAACGAACGA TTGAATGAAA AGAAATGAGA



Genetic code

Rules of transcriptional and post-transcriptional control

TCTACTTATATTCAATCCACAGGGCTACACCTAGTTCTTGAAGAGTCTGTTGAATGAACACATACATGGTTTATCTGTTTTTCTGTCTGCTCTGACCTCTGGCAGCTT

TAGCCTGCCCCACTCTTAGATAAACGAACCTTAGTGACTTCTGCTATACCAAAGTCTCCACGCCCCTCCGTAAACCTCTAACATGATGTCAGCAAATATTAAAAATGA

97%


?

• Begin transcription• End transcription• Splice transcript• Begin translation


Natural filters/transformations

• Selective transcription

• Selective processing

• Translation

• Folding

DNA Functional protein



DNA Functional protein

Simulation of Nature Surrogate Processes

From Sequence to OrganismHow can WE do it?


Simulation of Nature

Utterance of W Shakespeare

Utterance of George W Bush

“Whether ‘tis nobler in the mind to suffer the slings and arrows

of outrageous fortune...”

“We must give our military every tool and weapon it needs to prevail...”

???


Surrogate Processes






Word frequency


Surrogate Processes






Word frequency, words/sentence…





• Translation

• Folding/function

Surrogate filters

TCTACTTATA TTCAATCCAC AGGGCTACAC CTAGTTCTTG AAGAGTCTGT TGAATGAACA CATACATGGT TTATCTGTTT TTCTGTCTGC TCTGACCTCT GGCAGCTTTC CACTAGTTTC TGGATTTCGG AACTCTAGCC TGCCCCACTC

Characteristics of coding sequences/introns

• Gene finders

Predicted coding regionsMy sequence





• Translation


Surrogate filters• Gene finders

Met-Thr-Tyr-Asp-Gln-Arg-Thr-Gly-Leu...

Function?





• Translation


Surrogate filters• Gene finders

• Similarity finders

My predicted geneSequence/motif

databases

globin

globin?

Similar genes

Surrogate FiltersGene finders

Start/Stop codon search

CTCCACGCCCCTCCGTACACCTCTAACATGATGTCAGCAAATATTAAAAATGAATAAACTTTGTGACATGTACAAATGGAAATATGCAA

CT CCA CGC CCC TCC GTA CAC CTC TAA CAT GAT CTC AGC AAA TAT TAA AAA TGA ATA AAC TTT GTG ACA TGT ACA AAT GGA AAT ATG CAA

CTC CAC GCC CCT CCG TAC ACC TCT AAC ATG ATC TCA GCA AAT ATT AAA AAT GAA TAA ACT TTG TGA CAT GTA CAA ATG GAA ATA TGC AAC TCC ACG CCC CTC CGT ACA CCT CTA ACA TGA TCT CAG CAA ATA TTA AAA ATG AAT AAA CTT TGT GAC ATG TAC AAA TGG AAA TAT GCA A

Look for start codons (ATG) (GTG,TTG)

Look for stop codons (TAA,TAG,TGA)

CTCCACGCCCCTCCGTACACCTCTAACATGATGTCAGCAAATATTAAAAATGAATAAACTTTGTGACATGTACAAATGGAAATATGCAA

TTGCATATTTCCATTTGTACATGTCACAAAGTTTATTCATTTTTAATATTTGCTGAGATCATGTTAGAGGTGTACGGAGGGGCGTGGAG


Start/Stop codon search

Look for start codons (ATG) (GTG,TTG)

Look for stop codons (TAA,TAG,TGA)

Highly inaccurate


Hidden Markov Model (HMM)-based recognition

Step 1: Create model through extensive training set

AAAAACAAGAATACA . . .TTGTTT

TrainingSet

AAGCTTGACCAAAAAGTTAAAACACTGACGGCAAATAATCAATGACTATCAGACAGAGAATCATCGTGCTGTCAGTAAAACCTCTGATTTCGATCTTTACCATAATTGTTATGTTGTAATGACTAACCAGACTATCTTTTACAGAGCTTCTGGTTAACACTTGTCTAATTAGACATTGATAATGTTTGTGGGGGTTGGTCATCAGGAATGGTAAATAGCAATTACCCTTCAGACTTTCCTATGAGACGCTCCGCCAACGAGCAGTGTCTCTTAAAGAACGTTATGAGCGCTCAGTTAACTTCAGAAATTCACGGCGGAAATCCATAGTTATTATTACTTATGACTAAAACAAAATTACTATGGCGGCTTGTTTAATATAGATTCTGTGTTCTGAGAAATGACTTTTAAAGTCCCACTAACTTTTTTCTCATCTATTGCTATATTTCGACTTTAAAACTTATAGTAGATGGCTTAATTCTCAAATAACAAACTCATTTTTAGTAGATATTTCATGCAAACTGAGGTTTTTAGTGATATTTTCCCCTTATTGAGTACAGCCACTCCACAAACCTTAGAATGGCTACTCAATATTGCAATTGATCATGAATATCCCACTGGTAGAGCAGTTTTAATGGAAGATGCCTGGGGTAATGCAGTTTATTTCGTTGTATCTGGATGGGTAAAAGTTCGGCGCACCTGTGGAGATGATTCGGTAGCTTT


AAAA: 33%

AAAC: 25%

AAAG: 12%

AAAT: 30%


Class 3: Hidden Markov Model (HMM)-based recognition


TrainingSet



AACA: 30%

AACC: 20%

AACG: 15%

AACT: 35%




TrainingSet


Step 2: Assess candidate genes

0.12

A C G TAAA 0.33 0.25 0.12 0.30AAC 0.30 0.20 0.15 0.35AAG 0.35 0.15 0.20 0.30 AAT 0.30 0.15 0.20 0.25 ACA 0.25 0.20 0.15 0.35 . . .TTG 0.25 0.30 0.15 0.30TTT 0.30 0.25 0.10 0.35

Candidategene

AAAGCAA…

3rd order Markov model




AAAGCAA…

0.12 x 0.15





Candidategene


AAAGCTA…

0.12 x 0.15 . . .

So far, not a good candidate!





Candidategene





Candidate genes Predicted genes

Predicted genes





Candidate genes Predicted genes

Conform to standard modelChallenge

accepted beliefs

Computers are powerful

globin

Highly filtered output • Easy to grasp• High-level insights

Unfiltered output• Confusing• Basic insights

Computers are tempting

Globin

Computers are tempting

Crisis in Bioinformatics

1. Need high-level filters

2. Need access to raw phenomena

3. Need new tools for new phenomena

4. Need intuitive representation of results

Need a new generation

5. Need ability to build new tools

View of the Future

View of the Future Integration of information


Cell interaction

Metabolism,Architecture


Active site

Prochlorococcus MED4

Prochlorococcus MIT9313

• Gene present in Prochlorococcus MED4 MED4 is naturally adapted to grow in high light.

How do cells control response to light?

• Ortholog absent in Prochlorococcus MIT9313 MIT9313 is naturally adapted to grow in low light

• Ortholog present in Synechocystis PCC 6803 Reason will become apparent in a moment

• Synechocystis PCC 6803 ortholog responds to high light Gene turns on by factor > 2 in response to high light

What genes are related to the adaptation to high light?

Look for:

Build set Display set

Click on Build Set to begin finding orfs with

the desired specifications

HELPSet operation

All items in All open reading frames of

All amino acid sequences of

All intergenic regions of

Human-annotated orfs of

Private set

Public set

All open reading frames of


Choose set type

Goal is to find all open reading frames within Prochlorococcus MED4 that

meet certain specifications, so click on All open reading frames in

CancelHELPSet operation

All items in All open reading frames of Arthrobacter platensisGloeobacter violaceusMicrocystis aeruginosa

Nostoc punctiformeNostoc PCC 7120

Prochlorococcus MED4Prochlorococcus MIT9313

Prochlorococcus S120Synechococcus PCC6301Synechococcus PCC7942

Synechococcus WHSynechocystis PCC 6803Thermosynechococcus

TrichodesmiumUnicellulularFilamentous

All



Choose set type Choose database

Click on Prochlorococcus MED4


All items in All open reading frames of Prochlorococcus MED4

Display set

such that:

Variable Data Operation Function Done


Build set

You will ask that an ortholog of each desired MED4 genes exists in Synechocystis PCC 6803. It is

convenient to define the ortholog now. Click the Variable button



Display set

such that:

Variable Data

ItemNew variable

Variable


New variable

Build set

Item refers to the MED4 orf under consideration. You want to define its ortholog

in Synechocystis, so click on New variable

Operation Function Done



Display set

such that:

Variable Data

6803 ortholog

Type variable name

=


Build set

You can name the variable representing the ortholog anything you

like. For this simulation, a name is provided. Press the Enter key




Display set

such that:

Variable Data

6803 ortholog

Type variable name

= Closest ortholog of

Protein product of

Upstream region of

Downstream region of

Ortholog of (item


Choose function

Build set

One variable can be defined with respect to another in several ways.

The relationship you want is Ortholog of




Choose set type


Choose database

Display set

such that:

Variable Data

= Ortholog of (item in Arthrobacter platensisGloeobacter violaceusMicrocystis aeruginosa





Trichodesmium

Choose database

Synechocystis PCC6803

)Choose function

Build set

Clicking on Synechocystis PCC6803 defines the variable 6803 ortholog as

the ortholog in Synechocystis to a given orf of MED4.

6803 ortholog

Type variable name




Choose set type


Choose database

Display set

such that:

Variable Data

Synechocystis PCC 6803

Build set

)

The first limitation on the MED4 orf is that no ortholog of it exists in MIT9313. To evoke the concept of ortholog, press the

Function button

= Ortholog of (item inChoose databaseChoose function

6803 ortholog

Type variable name




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

Click on Ortholog of

Closest ortholog of

Protein product of

Upstream region of

Downstream region of

Ortholog of

Choose function

Synechocystis PCC 6803 )= Ortholog of (item inChoose databaseChoose function

6803 ortholog

Type variable name




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

As always, Item refers to the orf of MED4 that is being defined. You want to specify that an ortholog of it in MIT9313 doesn’t

exist, so click on Item.

Item6803 ortholog

Variable

Item( in


6803 ortholog

Type variable name

Ortholog of

Choose function




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

Clicking on Prochlorococcus MIT9313 defines an ortholog of a MED4 gene in MIT9313 (if such an ortholog exists)

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function

Arthrobacter platensisGloeobacter violaceusMicrocystis aeruginosa





Trichodesmium

Choose database

)





Choose set type


Choose database

Display set

such that:

Variable Data

Build set

You want to keep only those MED4 genes where an ortholog in MIT9313 does NOT

exist, so click on doesn’t exist.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) =

existsdoesn’t existdoesn’t exist

Op




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

That completes one specification, but there are more. Click on the Operation button to

connect one specification to the next.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

You want both the first specification AND the second to be true, so click on AND.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

ANDOR

AND

Op




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

The second specification is that microarray data for the 6803 ortholog meets a certain criterion. To get at that

data, press the Data button

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

The data you want is for the 6803 ortholog. Click on 6803

ortholog.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for ( Item6803 ortholog

New variable

Variable

6803 orthologin




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

Choose the Hihara experiment, which measured expression changes upon shift from low light to high light. If you didn’t

know which experiment was appropriate, you could have clicked on Choose data set for a description of the choices

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for ( 6803 ortholog

Variable

in Microarray:Hihara1(6803)Microarray:Suzuki1(6803)

Microarray:Yoshimura1(6803)Microarray:Meeks(Npun)Microarray:Golden(7120)

Choose data set

Microarray:Hihara1(6803) )



High light vs low light experiment


Choose set type


Choose database

Display set

such that:

Variable Data

Build set

You want the ratio of experimental condition to control to exceed a

specified value. Click on >.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for (

Variable

in Microarray:Hihara1(6803)

Choose data set

) << or =

=> or =

>>

Op

6803 ortholog




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

You can type in the value you want. For this simulation a number is supplied. Press the Enter key.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for (

Variable


Choose data set

) >

Op Value

]+26803 ortholog




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

No more specifications. Press the Done button.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for (

Variable


Choose data set

) >

Op Value

]+26803 ortholog




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

This was a complicated search. If you wanted to do it again, you could save the

search description. In this case, just save the results by clicking on Save only results.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for (

Variable


Choose data set

) >

Op Value

]+26803 ortholog

Save results and scriptSave only resultsSave only results




Choose set type


Choose database

Display set

such that:

Variable Data

Build set

All MED4 genes meeting the given specifications will be collected into a set. You can name the set anything you want. For this

simulation, a name is provided. Press the Enter key.

Item

Variable

( in


6803 ortholog

Type variable name

Ortholog of

Choose function


Choose database

) doesn’t exist

Op

AND

Op

[

data for (

Variable


Choose data set

) >

Op Value

]+2

Light-specific genes

Type name of set

6803 ortholog




:all0687 hupL [NiFe] uptake hydrogenase large subunit, C terminus

:all0687 hupL [NiFe] uptake hydrogenase large subunit, N terminus

:all0688 hupS [NiFe] uptake hydrogenase small subunit

:alr0692 similar to nifU

:alr0874 nifH2 dinitrogenase reductase

:asr1309 similar to nifU

:alr1407 nifV1 homocitrate synthase

:asr1408 nifZ iron-sulfur cofactor synthesis

:asr1408 nifT

Set: Light-specific genes

ProcMed4:all0687 hupL [NiFe] uptake hydrogenase large subunit, C terminus

ProcMed4:all0687 hupL [NiFe] uptake hydrogenase large subunit, N terminus

ProcMed4:all0688 hupS [NiFe] uptake hydrogenase small subunit

ProcMed4:alr0692 similar to nifU

ProcMed4:alr0874 psbBX dinitrogenase reductase

ProcMed4:asr1309 similar to nifU

ProcMed4:alr1407 psbY1 homocitrate synthase

ProcMed4:asr1408 psbX iron-sulfur cofactor synthesis

ProcMed4:asr1408 nifT

• The results are displayed as a list of orfs (Of course, the search capabilities do not now exist, and the results of the described search are unknown)• Clicking on the name of any orf brings you to its page (see Scenarios 1 and 2).• Clicking on circles next to the orf names allows you to modify the set.• The genetic neighborhood of each orf is shown to the right.

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Prochlorococcus MED4: pll1290

Replicon: Chromosome

Coordinates: 1533026 (stop) <- 1533931 (start-TTG) Human Length = 301 amino acids

Strand: Complementary

Gene name(s): proXM

Function: Putative type II DNA cytosine methyltransferase (CAGCTG-specific) Human Classification: Type II beta (N4) Human

Activity: Protects against: PvuII Experiment In vivo activity: exists Experiment

Cyanobacterial orthologs: none

ProcMED4

Proteus vulgaris

Salmonella paratyphi

Streptomyces spectabilis

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]+26803 ortholog

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Equivalent script that bypasses interface

FOR orf IN (orfs:ProcMED4) { 6803ortholog = Ortholog(orf,orfs:Syny6803); WHEN (NOT Exists(Ortholog(orf,orfs:Proc9313)) AND Data(6803ortholog,microarray:Hihara1) > +2){ COLLECT orf INTO light_specific_genes; }}DISPLAY (light_specific_genes, “BNC”);

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MAIL (light_specific_genes,[email protected],“BNC”);

The same search could have been conducted through the script shown above. The script interface makes possible complex

searches beyond the scope of the graphical interface.


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How does a biologist maintain a grip on sanity?reality?

View of the Future Interplay of low- & high-level perception

ProcMED4

Proteus vulgaris



View of the Future Interplay of low- & high-level perception

Anab7120

Proteus vulgaris



TCTACTTATATTCAATCCACAGGGCTACACCTAGTTCTTGAAGAGTCTGTTGAATGAACACATACATGGTTTATCTGTTTTTCTGTCTGCTCTGACCTCTGGCAGCTT

TAGCCTGCCCCACTCTTAGATAAACGAACCTTAGTGACTTCTGCTATACCAAAGTCTCCACGCCCCTCCGTAAACCTCTAACATGATGTCAGCAAATATTAAAAATGA

97%


Anabaena Chromosome (6413771 bp): 4001 to 5000

cgcccaacaataacaaatgtgtaatctagaccttctgccttgagttccttggcgcggttttcggcacgacggatgacgttggtattgtaaccgccgcacaaaccacgatcgccagaaataactagcaagcctactgatttaacttcccgttttttcagtagaggtaagtctacatcttcaaaccgtagacgagtttgcaaaccgtataatacttgtgccaaacggtcagcaaaaggacgagtagcgattacttgttcttgggcgcgacgtacacgcgccgccgctaccagccgcatggcttctgtgattttcttggtgtttttgaccgactgaatgcgatcgcgtattgatttgagattaggcataatatttgttgattgtcagttgtcagttgtcagttgtcagttgtcagtgtctattgctactgaccactgaccaatgactaatgactaattacgctgtagctttgaaggtctttttgtagtcttctaaagctgccttcaatgctttttcttcatcatcacccagtgctttcttcgattgtacgtcttggaagtaggggttaacgccggacttcaagtaatctctcaagcctttggtgaaggtggtgactttatcaacagggatatcatctaagtaaccgttgatacctgcgtacagaatggctacttgttcagctacggatagaggctgattttgggactgtttgaggagttcccgcaggcgttgacctcttgccaattggtcttgggtggctttatctaggtcggaagcaaattgcgcgaaggcttggaggtcgtcaaactgtgctagttcgagcttaatcttaccagcaacttttttcatcgctttggtttgtgccgcagaacccacacgggatacagagataccagggtttacagccggacgaataccagcgttaaataagtcagaagataagaatatctgaccgtctgtaatagaaattacgttggtaggaatgtaggcagaaacgtcacca

Typical output of current programs

Future: Sequence plus genetic context

Noncoding region

Future: Both filtered and raw data

Filters: Information reducersBuild filter to find repeated sequences


TGGTCTCCGACCGACCGTAGGTCATCGTGGTCTCCGACCGACCGTAGGTCATCG

CTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGTAGCCGAAGTAGTTCGACTGAGCGTAGTCGAAGTC

...

Repeat filter

Entire genome Repeated sequences

Filters: Information reducersBuild repeats filter


TGGTCTCCGACCGACCGTAGGTCATCGTGGTCTCCGACCGACCGTAGGTCATCG

CTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGTAGCCGAAGTAGTTCGACTGAGCGTAGTCGAAGTC

...

Repeat filter

Entire genome Repeated sequences

NIS-1: repeat family

Alignment of NIS-1

(…271 more)

Filters: Information reducersBuild secondary repeats filter

A: CTTGTACTGAGCGAAGTCGAAGTAB: CTTGTACTGAGCGTAGCCGAAGTA

Distance = 2

CTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGAAGTCGAAGTACTTGTACTGAGCGAAGTCGAAGTA ...CTTGTACTGAGCGAAGTCGAAGTA

Copy number = 10

Subfamily A

CTTGTACTGAGCGTAGCCGAAGTACTTGTACTGAGCGTAGCCGAAGTA

Copy number = 2

Subfamily B

GTTCGACTGAGCGTAGTCGAAGTC

Copy number = 1

Subfamily C


Distance = 2

A: CTTGTACTGAGCGAAGTCGAAGTAC: GTTCGACTGAGCGTAGTCGAAGTC

Distance = 5


Copy number = 10

Subfamily A


Copy number = 2

Subfamily B


Copy number = 1

Subfamily C


B: CTTGTACTGAGCGTAGCCGAAGTAC: GTTCGACTGAGCGTAGTCGAAGTC

Distance = 5Distance = 5Do for all pairs of subfamilies


Copy number = 10

Subfamily A


Copy number = 2

Subfamily B


Copy number = 1

Subfamily C

Distance = 2

Diameter Copies of exact repeats

Distance Number of mismatches

Relationship between related repeats in genome(sequences within NIS-1 repeat family)


1. Need high-level filters2. Need access to raw phenomena

Integrated knowledge base



3. Need new tools for new phenomena4. Need intuitive representation of results


Tools that bridge levels of perception



3. Need new tools for new phenomena4. Need intuitive representation of results

Long term: Need a new generation

5. Need ability to build new tools


Tools that bridge levels of perception

Short term: Graphical programming Human help


How does a biologist maintain a grip on reality?

Filtering reality Raw reality

Real questions with real answers

Pre-genomic Molecular Biology


How do we figure out how cars are made?

Genetic approach Biochemical approach

Pre-genomic Molecular BiologyGeneticist’s Approach

Isolation of Defective Gene

Pre-genomic Molecular BiologyGeneticist’s Approach

Pre-genomic Molecular BiologyBiochemist’s Approach

• One component at a time

• Highly filtered perception

• Many local viewpoints

Pre-genomic Molecular BiologyHow we viewed the world

Post-genomic Molecular Biology

Post-genomic Molecular BiologyBioinformaticist’s Approach

(long term)

Assemble the whole

Post-genomic Molecular BiologyBioinformaticist’s Approach

(short term)

Identify critical parts

Globin

Current Biology

AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT

Future Biology

Globin


Current BiologyCurrent Life

“Axis of Evil...”

Current Life

“No war for oil...”Globin

Current Life

Contact Information

Jeff ElhaiDepartment of BiologyVirginia Commonwealth UniversityRichmond, VA

E-Mail: [email protected]: 804-828-0794Web: www.people.vcu.edu/~elhaij/

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