MW 11:00-12:15 in Beckman B302 Prof: Gill Bejerano TAs: Jim Notwell & Harendra Guturu

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http://cs173.stanford.edu [BejeranoWinter12/13] 1

MW 11:00-12:15 in Beckman B302Prof: Gill BejeranoTAs: Jim Notwell & Harendra Guturu

Welcome back!

What will we study?

The most amazing “tape” in existence, your genome.

http://cs273a.stanford.edu [Bejerano Fall11/12] 4

TTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCAAAGAAGTTTAATAATCATATTACATGGCATTACCACCATATACATATCCATATCTAATCTTACTTATATGTTGTGGAAATGTAAAGAGCCCCATTATCTTAGCCTAAAAAAACCTTCTCTTTGGAACTTTCAGTAATACGCTTAACTGCTCATTGCTATATTGAAGTACGGATTAGAAGCCGCCGAGCGGGCGACAGCCCTCCGACGGAAGACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCGCGCCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGTTATGAAGAGGAAAAATTGGCAGTAACCTGGCCCCACAAACCTTCAAATTAACGAATCAAATTAACAACCATAGGATGATAATGCGATTAGTTTTTTAGCCTTATTTCTGGGGTAATTAATCAGCGAAGCGATGATTTTTGATCTATTAACAGATATATAAATGGAAAAGCTGCATAACCACTTTAACTAATACTTTCAACATTTTCAGTTTGTATTACTTCTTATTCAAATGTCATAAAAGTATCAACAAAAAATTGTTAATATACCTCTATACTTTAACGTCAAGGAGAAAAAACTATAATGACTAAATCTCATTCAGAAGAAGTGATTGTACCTGAGTTCAATTCTAGCGCAAAGGAATTACCAAGACCATTGGCCGAAAAGTGCCCGAGCATAATTAAGAAATTTATAAGCGCTTATGATGCTAAACCGGATTTTGTTGCTAGATCGCCTGGTAGAGTCAATCTAATTGGTGAACATATTGATTATTGTGACTTCTCGGTTTTACCTTTAGCTATTGATTTTGATATGCTTTGCGCCGTCAAAGTTTTGAACGATGAGATTTCAAGTCTTAAAGCTATATCAGAGGGCTAAGCATGTGTATTCTGAATCTTTAAGAGTCTTGAAGGCTGTGAAATTAATGACTACAGCGAGCTTTACTGCCGACGAAGACTTTTTCAAGCAATTTGGTGCCTTGATGAACGAGTCTCAAGCTTCTTGCGATAAACTTTACGAATGTTCTTGTCCAGAGATTGACAAAATTTGTTCCATTGCTTTGTCAAATGGATCATATGGTTCCCGTTTGACCGGAGCTGGCTGGGGTGGTTGTACTGTTCACTTGGTTCCAGGGGGCCCAAATGGCAACATAGAAAAGGTAAAAGAAGCCCTTGCCAATGAGTTCTACAAGGTCAAGTACCCTAAGATCACTGATGCTGAGCTAGAAAATGCTATCATCGTCTCTAAACCAGCATTGGGCAGCTGTCTATATGAATTAGTCAAGTATACTTCTTTTTTTTACTTTGTTCAGAACAACTTCTCATTTTTTTCTACTCATAACTTTAGCATCACAAAATACGCAATAATAACGAGTAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAG...TTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAGTCATTTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTTTCCTACGCATAATAAGAATAGGAGGGAATATCAAGCCAGACAATCTATCATTACATTTAAGCGGCTCTTCAAAAAGATTGAACTCTCGCCAACTTATGGAATCTTCCAATGAGACCTTTGCGCCAAATAATGTGGATTTGGAAAAAGAGTATAAGTCATCTCAGAGTAATATAACTACCGAAGTTTATGAGGCATCGAGCTTTGAAGAAAAAGTAAGCTCAGAAAAACCTCAATACAGCTCATTCTGGAAGAAAATCTATTATGAATATGTGGTCGTTGACAAATCAATCTTGGGTGTTTCTATTCTGGATTCATTTATGTACAACCAGGACTTGAAGCCCGTCGAAAAAGAAAGGCGGGTTTGGTCCTGGTACAATTATTGTTACTTCTGGCTTGCTGAATGTTTCAATATCAACACTTGGCAAATTGCAGCTACAGGTCTACAACTGGGTCTAAATTGGTGGCAGTGTTGGATAACAATTTGGATTGGGTACGGTTTCGTTGGTGCTTTTGTTGTTTTGGCCTCTAGAGTTGGATCTGCTTATCATTTGTCATTCCCTATATCATCTAGAGCATCATTCGGTATTTTCTTCTCTTTATGGCCCGTTATTAACAGAGTCGTCATGGCCATCGTTTGGTATAGTGTCCAAGCTTATATTGCGGCAACTCCCGTATCATTAATGCTGAAATCTATCTTTGGAAAAGATTTACAATGATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAGTCATTTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAAT

Why Genomics?

• This century is owned by Genomics.

• Growing impact on everybody’s life.

• Rewriting the book on our understanding of life.

• Genomics is an information/computational science.

• “There is gold in them thar hills”

• That gold can be yours.

Why Genomics?

• Make tantalizing discoveries with CS107 proficiency.• Knowing more CS does make you more dangerous.

Genomics is different

Theoretical CS studies the hardness of questions.A question is as hard as its easiest solution.A lot of focus on how to answer.

• Order of importance in genomics:• What to ask?• Why ask it?• How to answer?• What does my answer mean?

Genomics is drowning in data.Much to discover. Some fascinating, lots quite boring.Focus on what & why to ask, and can we answer?

Why Genomics?

• Make tantalizing discoveries with CS107 proficiency.• Knowing more CS does make you more dangerous.

• Reject the “us” (CS) and “them” (BIO) dichotomy.• Read what you need.• Develop your own taste for questions and answers.

Field Goals

Class Goals

• Meet your genome (learn to surf, learn the surf)• Understand genomic tools (theory, applications)• DIY (pose questions, use tools, write code, get answers)

MaterialsHow many people need the BIO primer?We’ll have three primers on:Biology; Text Processing; and the UCSC Genome Browser.Programming background recommended (CS107 level)

Homework (schedule on website):Two individual homework assignments,

plus a group project.Instead of an exam we’ll have a project milestone

and a final poster session.

Attendance is mandatory (for grade). You may skip 2 lectures without affecting your grade.

Get on the mailing list!

Reading Material: mostly journal papers

Topics(0) Genome context:

cells, DNA, central dogma(1) Genome content / genome function:

coding and non-coding genes, gene regulation, repeats, epigenetics, signaling

(2) Genome sequencing: technologies, assembly/analysis, technology dependence

(3) Genome evolution: evolution = mutation + selection, modes of evolution, comparative genomics, ultraconservation, exaptation

(4) Genomics & disease:disease susceptibility, cancer genomics, treatment response, personal genomics, gene therapy

(5) Genome and “genome output” (organism) evolutionEvo devo, the great divide, bridges across the great divide

Important in Genomics

• Understand deep dependence on technology.• The only truth in genomics is…• Technology dictates what can be asked.• Technology dictates how it can be answered.• Recent data deluge – the beauty, and the risks.

• Hypothesize, code, analyze, repeat until you find gold, or your sieve is empty.

• Analyze ensembles, learn from outliers.

• When you make an exciting discovery, first try hard to refute it.• If it’s too good to be true, it is most likely not true.• Seek the exciting invisible but plausible.

Further Reading

These principles and tips will be revisited at course’s end.At which point we will ask ourselves:

Are we any wiser?

Check out the Bejerano lab “resources” page:• Popular science books• Core Stanford classes• Core technical books/skills

What if I get hooked?Classes, rotations, CURIS, honors theses, etc.

Organism – Cell - Genome

1013 different cells in an adult human.The cell is the basic unit of life.DNA = linear molecule inside the cell that carries instructions needed throughout the cell’s life ~ long string(s) over a small alphabet

Alphabet of four (nucleotides/bases) {A,C,G,T} Strings of length 104-1011

...ACGTACGACTGACTAGCATCGACTACGACTAGCAC...

“instruction”Genome:

One Cell, One Genome, One Replication

•Every cell holds a copy of all its DNA = its genome.•The human body is made of ~1013 cells.•All originate from a single cell through repeated cell divisions.

genome =all DNA

chicken ≈ 1013 copies(DNA) of egg (DNA)

chicken

egg egg

celldivision

DNA strings =Chromosomes

Genomes, Genes & Proteins

The most visible instructions in our genome are Genes.Genes explain exactly HOW to synthesize any protein.Proteins are the work horses of every living cell.

geneGenome:

cellprotein

Genes & Gene Regulation

• Human genome encodes 20-25,000 genes (2% genome),>1,000,000 genomic switches that control genes (>10%).

• Gene = genomic substring that encodes HOW to make a protein.

• Genomic switch = genomic substring that encodes WHEN, WHERE & HOW MUCH of a protein to make.

[1,0,0,1] [1,1,0,0]

[0,1,1,1]

Epigenomics: transient writing “on” the genome

Repeats / obile Elements ("selfish/junk DNA")

HumanGenome:

3*109 letters2%

knownfunction >50%

Genome: conceptual part list

A copy (actually two) in every cell.Contains:

1. Genes2. Gene regulation sequences3. Repetitive DNA4. Transient marks

on genome packing material

“instruction”Genome:

DNA sequencingGenomes are awesome.Let’s get’em.

…ACGTGACTGAGGACCGTGCGACTGAGACTGACTGGGTCTAGCTAGACTACGTTTTATATATATATACGTCGTCGTACTGATGACTAGATTACAGACTGATTTAGATACCTGACTGATTTTAAAAAAATATT…

Genomic Drama

HGC Celera

Getting the “blueprint of life”

DNA sequencing costs

1st gen

2nd gen

3rd gen

1st Genome Assembly

1. Find overlapping reads

4. Derive consensus sequence ..ACGATTACAATAGGTT..

2. Merge some “good” pairs of reads into longer contigs

3. Link contigs to form supercontigs

Some Terminology

read a 500-900 long word that comes out of sequencer

mate pair a pair of reads from two endsof the same insert fragment

contig a contiguous sequence formed by several overlapping readswith no gaps

supercontig an ordered and oriented set(scaffold) of contigs, usually by mate

consensus sequence derived from thesequene multiple alignment of reads

in a contig

2nd Gen: Next Generation (re)Sequencing

Output = massive amounts of short, lower quality reads.New Technologies + New Algorithms = New Opportunities

3rd Gen: cost effective, long reads

http://www.mcb.harvard.edu/branton/index.htm

Just one example:

Output: very long reads of 10,000-100,000 basepairs each.Sequence “anything” you like. In a lab. Trivial assembly.

30http://cs173.stanford.edu [BejeranoWinter12/13]

100 million species

7 billion individuals

1013 cells in a human

Genomes, sequences everywhere

or sequence just an active portion

31http://cs173.stanford.edu [BejeranoWinter12/13]

Portals to the Human GenomeGGTGCCAGGGAAAGGGCAGGAGGTGAGTGCTGGGAGGCAGCTGAGGTCAACTTCTTTTGAACTTCCACGTGGTATTTACTCAGAGCAATTGGTGCCAGAGGCTCAGGGCCCTGGAGTATAAAGCAGAATGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCGAAAGACCTGTTGGAGGCTATGAATGCAATCAAGGTGACAGACAACTGGTGCAATGATGGTAGTGGAAATGGAGGAGAGGGGATTGATTCAAGATGCATTTAGGACCAAGAATCGGGAGCTTGTGAACGTGTGTATGAGTACTGTAGACGGAGTGGGTGTGTCATCAGAGAAGATCTGAGCATTTGGGCTTGCTCTCCTCAGAGGCCCTGCGAGTGGAGTTCAGCTTTTCCTCATGGGGCAAATCTCACTTTCGCTCCAGTTCCTGGGGCTCAGAGTCCCTGGCCCAGATGCCTCTTGCCATCTCATCTTCACCCTGCCTGGCTTCCCTTGCTTGTTCCAGGATTGTTTCATAAAGAGGGATGTGGTTGGTCTTTAACCCTATGAATGCTGGCTGAGGATGCCTGCGGAACCTGTAGTGAAGCTTTCAGGGGCTGCTCGGGTTCTGGCTGGTAGGTGAACACTGTCCATCTTGCCGGCTGGGACACAGTGACTCTGGGTAGTTGTGTAAGAGAGGGGCCCTTGGCAGACAAACAGGTTCTTCTCTGTTGGTGGGCCAGCCAGCAGGTCAGTGGGAAGGTTAAAGGTCATGGGGTTTGGGAGAACTGGGTGAGGAGTTCAGCCCCATCCCCCGTAAAGCTCCTGGGAAGCACTTCTCTACTGGGGCAGCCCCTGATACCAGGGCACTCATTAACCCTCTGGGTGCCAGGGAAAGGGCAGGAGGTGAGTGCTGGGAGGCAGCTGAGGTCAACTTCTTTTGAACTTCCACGTGGTATTTACTCAGAGCAATTGGTGCCAGAGGCTCAGGGCCCTGGAGTATAAAGCAGAATGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGGAAAGACCTGTTGGAGGCTATGAATGCAATCAAGGTGACAGACAACTGGTGCAATGATGGTAGTGGAAATGGAGGAGAGGGGATTGATTCAAGATGCATTTAGGACCAAGAATCGGGAGCTTGTGAACGTGTGTATGAGTACTGTAGACGGAGTGGGTGTGTCATCAGAGAAGATCTGAGCATTTGGGCTTGCTCTCCTCAGAGGCCCTGCGAGTGGAGTTCAGCTTTTCCTCATGGGGCAAATCTCACTTTCGCTCCAGTTCCTGGGGCTCAGAGTCCCTGGCCCAGATGCCTCTTGCCATCTCATCTTCACCCTGCCTGGCTTCCCTTGCTTGTTCCAGGATTGTTTCATAAAGAGGGATGTGGTTGGTCTTTAACCCTATGAATGCTGGCTGAGGATGCCTGCGGAACCTGTAGTGAAGCTTTCAGGGGCTGCTCGGGTTCTGGCTGGTAGGTGAACACTGTCCATCTTGCCGGCTGGGACACAGTGACTCTGGGTAGTTGTGTAAGAGAGGGGCCCTTGGCAGACAAACAGGTTCTTCTCTGTTGGTGGGCCAGCCAGCAGGTCAGTGGGAAGGTTAAAGGTCATGGGGTTTGGGAGAAACTGGGTGAGGAGTTCAGCCCCATCCCCCGTAAAGCTCCTGGGAAGCACTTCTCTACTGGGGCAGCCCCTGATACCAGGGCACTCATTAACCCTCTGGGTGCCAGGGAAAGGGCAGGAGGTGAGTGCTGGGAGGCAGCTGAGGTCAACTTCTTTTGAACTTCCACGTGGTATTTACTCAGAGCAATTGGTGCCAGAGGCTCAGGGCCCTGGAGTATAAAGCAGAATGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCGAAAGACCTGTTGGAGGCTATGAATGCAATCAAGGTGACAGACAACTGGTGCAATGATGGTAGTGGAAATGGAGGAGAGGGGATTGATTCAAGATGCATTTAGGACCAAGAATCGGGAGCTTGTGAACGTGTGTATGAGTACTGTAGACGGAGTGGGTGTGTCATCAGAGAAGATCTGAGCATTTGGGCTTGCTCTCCTCAGAGGCCCTGCGAGTGGAGTTCAGCTTTTCCTCATGGGGCAAATCTCACTTTCGCTCCAGTTCCTGGGGCTCAGAGTCCCTGGCCCAGATGCCTCTTGCCATCTCATCTTCACCCTGCCTGGCTTCCCTTGCTTGTTCCAGGATTGTTTCATAAAGAGGGATGTGGTTGGTCTTTAACCCTATGAATGCTGGCTGAGGATGCCTGCGGAACCTGTAGTGAAGCTTTCAGGGGCTGCTCGGGTTCTGGCTGGTAGGTGAACACTGTCCATCTTGCCGGCTGGGACACAGTGACTCTGGGTAGTTGTGTAAGAGAGGGGCCCTTGGCAGACAAACAGGTTCTTCTCTGTTGGTGGGCCAGCCAGCAGGTCAGTGGGAAGGTTAAAGGTCATGGGGTTTGGGAGAACTGGGTGAGGAGTTCAGCCCCATCCCCCGTAAAGCTCCTGGGAAGCACTTCTCTACTGGGGCAGCCCCTGATACCAGGGCACTCATTAACCCTCTGGGTGCCAGGGAAAGGGCAGGAGGTGAGTGCTGGGAGGCAGCTGAGGTCAACTTCTTTTGAACTTCCACGTGGTATTTACTCAGAGCAATTGGTGCCAGAGGCTCAGGGCCCTGGAGTATAAAGCAGAATGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAGACGTGAGCAGGTGAGCAGCTGGGGCTGTCTGCTCTCTGTGCCCAG

Human Genome = three billion (3*109) basepairs:

Genome Browser Database

Primary table: positions, names, etc.

UnderlyingDatabase(MySQL)

Auxiliary table: related data

visualize search & download

Genome Evolution

“Nothing in Biology Makes Sense Except in the Light of Evolution” Theodosius Dobzhansky

So far we’ve treated the genome as immutable.But boy is it alive.

Every Genome is Different

DNA Replication is imperfect – between individuals of the same species, even between the cells of an individual.

...ACGTACGACTGACTAGCATCGACTACGA...

chicken

egg ...ACGTACGACTGACTAGCATCGACTACGA...

functionaljunk

TT CAT

“anythinggoes”

many changesare not tolerated

chicken

This has bad implications – disease, and good implications – evolution.

Genome mutation types: anything you can do to a

stringDeletionInversionTranslocationDuplication

Modes of evolution = Mutation + Selection

Don’t care Beneficial mutationHarmful mutation

timepopulation

Cancer is a disease of the genome

that makes cell veer off plan(whatever its particular plan is)and start dividing uncontrollably.

Single Base Changes Can Be Detrimental

“Non-coding” mutations can be detrimental

[de Kok et al, 1996]

Finding Disease Loci

Gene/Cell Therapy: Curing Genomics Defects

1 Get’em2 Fix’em3 Put’em back

Evolution is not all bad!

Sampled Genomes

S SpeciationTime

mouserat

chicken

opossum

macaque

platypus

Comparative Genomics, Evo Devo

We can sample ancient genomes (tens of thousands of years old).We can reconstruct ancestral genomes (tens of millions of years).

How to learn from different genomes about different owners?

(we can get the tape, we can play the tape, we want to hear the music!)

The great genotype-phenotype divide

PhenotypeGenotype

and ways to cross it!

To Be Continued…

MW 11:00-12:15 in Beckman B302 Prof: Gill Bejerano TAs: Jim Notwell & Harendra Guturu

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