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BIONF/BENG 203: Functional Genomics

Lecture TI 1,2

Trey Ideker

UCSD Departments of Medicine & Bioengineering

Sources of Functional Data Lectures 1 and 2

Instructors

Trey Ideker

Vineet Bafna

Anand Patel (TA)

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3

Grading

40% Problem Sets (best 4 of 5)

30% Midterm

30% Final Project

Topics Covered By This Course

① Signal detection in bioinformatics

② Large-scale data generation platforms

③ Understanding next-gen sequencing data

④ Understanding mass spectrometry data

⑤ Clustering and Classification

⑥ Genotype-phenotype association

⑦ Understanding physical & genetic networks

⑧ Gene network inference and evolution 4

Ideker, Dutkowski, Hood. Cell 2011

Bioinformatics as Signal Detection

Ideker, Dutkowski, Hood. Cell 2011 Test Statistic t

Power, FDR, and all that...

Test Statistic t

Power, FDR, and all that...

An Example:

Pathway-Level Integration of

Genome-wide Association Studies

Segrè et al., 2010 A.V. Segrè, L. Groop, V.K. Mootha, M.J. Daly and D.

Altshuler, PLoS Genet. 6 (2010), p. e1001058.

2) Molecular Networks 1) Molecular States

3) Phenotypic traits

Classes of biological measurements

Protein-protein interactions:

Two-hybrid system, coIP, protein

antibody array

Protein-DNA interactions:

Chromatin IP (chip) sequencing

Protein-compound

DNA sequence / genotype: Next-gen sequencing, SNP & CNV arrays

Gene expression:

DNA microarrays, mRNA sequencing

Protein levels, locations, mods:

Mass spectrometry, fluorescence

microscopy, protein arrays

Physiological or disease state, binary or quantitative

Growth rate, response to stimulus or stress

Behaviors

Sequencing By Synthesis

(Illumina GenomeAnalyzer or HiSeq)

Bridge Amplification

Pyrosequencing

Note: No actual houses

are burned down in

pyrosequencing

Pyrosequencing (Life Sciences / Roche 454)

A luciferase is an enzyme which emits light in

the presence of ATP.

Several organisms, such as the American firefly and the

poisonous Jack-o-lantern mushroom, produce luciferases.

Detecting polymerase activity

Recall: Pyrophosphate is also known as PPi,

also known as “two phosphate groups stuck

together”. During replication, each addition

of a dNTP releases pyrophosphate

In the reaction mixture, PPi allows adenosine

phosphosulfate (APS) to be converted to

ATP; this ATP allows luciferase to luciferate

(emit light).

Measures strand extension as it happens

Pyrosequencing cycle

Add dATP. If light is emitted, your sequence

starts with A. If not, the dATP is degraded

(or elutes past immobilized primer).

Add dGTP. If light is emitted, the next base

must be a G.

Then add T, then C. You now know at least

one (maybe more) base of the sequence.

Repeat!

Pyrosequencing output

Runs of bases produce higher peaks – for instance, the sequence for (a)

is GGCCCTTG. Sample (c) comes from a heterozygous individual (hence

the heights in multiples of ½)

The X Prize Foundation

In October 2006, the X Prize Foundation

established an initiative to promote the

development of full genome sequencing

technologies, called the Archon X Prize,

intending to award $10 million to "the first

Team that can build a device and use it to

sequence 100 human genomes within 10 days

or less, with an accuracy of no more than one

error in every 100,000 bases sequenced, with

sequences accurately covering at least 98% of

the genome, and at a recurring cost of no more

than $10,000 (US) per genome.”

http://genomics.xprize.org/

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Gene and Protein Expression

The transcriptome is the full complement of RNA molecules produced by a genome

The proteome is the full complement of proteins enabled by the transcriptome

DNA RNA protein

Genome transcriptome proteome

30,000 genes ??? RNAs ??? proteins?

For example, the drosophila gene Dscam can generate 40,000 distinct transcripts through alternative splicing.

What is the minimum number of exons that would be required?

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mRNA Expression: Two dominant approaches

RNA sequencing

DNA Microarrays

Others / older approaches:

EST sequencing

RT-PCR

Differential display

SAGE

Massively parallel signature sequencing (MPSS)

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Microarrays

Monitors the level of each gene:

Is it turned on or off in a particular biological condition?

Is this on/off state different between two biological conditions?

Microarray is a rectangular grid of spots printed on a glass microscope slide, where each spot contains DNA for a different gene

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Two-color DNA microarray design

Reverse Transcription

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Types of microarrays

Spotted (cDNA)

– Robotic transfer of cDNA clones or PCR products

– Spotting on nylon membranes or glass slides coated with poly-lysine

Synthetic (oligo)

– Direct oligo synthesis on solid microarray substrate

– Uses photolithography (Affymetrix) or ink-jet printing (Agilent)

– 100,000 features per cm2

All configurations assume the DNA on the array is in excess of the hybridized sample—thus the kinetics are linear and the spot intensity reflects that amount of hybridized sample.

Labeling can be radioactive, fluorescent (one-color), or two-color

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Microarray Spotter

Affymetrix High Density Arrays

Microarray confocal scanner

Collects sharply defined optical sections from which 3D renderings can be created

The key is spatial filtering to eliminate out-of-focus light or glare in specimens whose thickness exceeds the immediate plane of focus.

Two lasers for excitation

Two color scan in less than 10 minutes

High resolution, 10 micron pixel size

Next-Gen Sequencing of mRNAs

cDNA = complementary or copy DNA

EST = Expressed Sequence Tag

The microarray could be described as a “closed system” because information about RNAs is limited by the targets available for hybridization. RNAs not represented on the array are not interrogated.

Direct sequencing of cDNAs overcomes this problem by large-scale random sampling of sequences from a whole-cell RNA extract

Statistical counting of distinct sequences provides a precise estimate of expression level

cDNA library can be normalized to capture rare messages

Has been dramatically enabled by large scale sequencing

mRNA Sequencing: Preparation of a cDNA library in phage vector

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Proteomics

MS / MS

1D and 2D SDS PAGE

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Mass spectrometry

Mass spectrometers consist of 3 essential parts

– Ionization source: Converts peptides into gas-phase ions

(MALDI + ESI)

– Mass analyzer:

Separates ions by mass to charge (m/z) ratio

(Ion trap, time of flight, quadrupole)

– Ion detector: Current over time indicates amount of signal at

each m/z value

MS/MS Overview

MS/MS Overview

A raw fragmentation spectrum

By calculating the molecular weight difference between ions of the same type the sequence can be determined.

Algorithms like SEQUEST use the fragmentation pattern to search through a complete protein database to identify the sequence which best fits the pattern.

43 Tandem Mass Spec (MS/MS)

Isotope Coded Affinity Tags (ICAT)

Biotin

tag

Linker (d0 or d8) Thiol specific

reactive group

ICAT Reagents: Heavy reagent: d8-ICAT (X=deuterium)

Normal reagent: d0-ICAT (X=hydrogen)

S

N N

O

N O O

O N I

O O X

X

X

X

X

X

X

X

Mass spec based method for measuring relative protein abundances between two samples

Combine and

proteolyze

(trypsin)

Affinity

separation

(avidin)

Protein identification

ICAT-

labeled

cysteines

550 560 570 580

m/z

0

100

200 400 600 800

m/z

0

100 NH2-EACDPLR-COOH

Light Heavy

Mixture 2

Mixture 1

Protein Quantification & Identification

via ICAT Strategy

Quantitation

ICAT Flash animation: http://occawlonline.pearsoned.com/bookbind/pubbooks/bc_mcampbell_genomics_1/medialib/method/ICAT/ICAT.html

ICAT continued

The heavy (blue) and light (gray) peptides are separated and quantified to produce a ratio for each peptide – here, a single peptide ratio is shown

Each peptide is subjected to CID fragmentation in the second MS stage in order to identify it

Gene replacement for yeast & other model species

Using HR-based gene replacement, genes can be replaced with drug

resistance cassette, tagged with GFP, epitope tagged, etc.

Systematic phenotyping

yfg1 yfg2 yfg3

CTAACTC TCGCGCA TCATAAT Barcode

(UPTAG):

Deletion Strain:

Growth 6hrs in minimal media

(how many doublings?)

Rich media

…

Harvest and label genomic DNA

Systematic phenotyping with a barcode array Ron Davis and friends…

These oligo barcodes are also

spotted on a DNA microarray

Growth time in minimal media:

– Red: 0 hours

– Green: 6 hours

YFP tagging for protein localization

NIC96 Nuclear Pore

YPF is green, transmitted light is red

TUB1 Tubulin cytoskeleton

HHF2 Histone Nucleus

BNI4 Bud neck

Images courtesy T. Davis lab

See also work by Weissman and O’Shea labs at UCSF

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Molecular Interactions

Among proteins,

mRNA, small

molecules, and so on…

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Protein→DNA interactions

Gene levels (on/off)

Protein—protein interactions

Protein levels (present/absent)

Biochemical reactions

Biochemical levels

▲ Chromatin IP

▼ DNA microarray

▲ Protein coIP

▼ Mass spectrometry

▲Not yet!!!

Metabolic flux ▼ measurements

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Measurements of molecular interactions

Protein-protein interactions

Yeast-two-hybrid

Kinase-substrate assays

Co-immunoprecipitation w/ mass spec

Protein-DNA interactions

ChIP-on-chip and ChIP-seq

Genetic interactions

Systematic Genetic Analysis

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Yeast two-hybrid method

Fields and Song

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Kinase-target interactions

Mike Snyder and colleagues

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Protein interactions by protein immunoprecipitation followed by mass spectrometry

Gavin / Cellzome

TEV = Tobacco Etch Virus proteolytic site

CBP = Calmodulin binding peptide

Protein A = IgG binding from Staphylococcus

ChIP measurement of protein→DNA interactions

From Figure 1 of Simon et al. Cell 2001

Genetic interactions: synthetic lethals and suppressors

Genetic Interactions:

Widespread method used by geneticists to discover pathways in yeast, fly, and worm

Implications for drug targeting and drug development for human disease

Thousands are now reported in literature and systematic studies

As with other types, the

number of known genetic interactions is exponentially increasing…

Adapted from Tong et al., Science 2001

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Most recorded genetic interactions are synthetic lethal relationships

Adapted from Hartman, Garvik, and Hartwell, Science 2001

A B A B A B A B

A

B

Parallel Effects

(Redundant or Additive)

Sequential Effects

(Additive)

Single A or B mutations typically

abolish their biochemical activities

Single A or B mutations typically

reduce their biochemical activities

Interpretation of genetic interactions (Guarente T.I.G. 1990)

A B

GOAL: Identify

downstream

physical pathways