do not reproduce without permission 1 gerstein.info/talks (c) 2007 1 (c) mark gerstein, 2002, yale,...

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Research @ GersteinLab.org

• Human Genome Annotation (pseudogenes) Characterizing the function of non-coding regions, focusing on

protein fossils and novel transcriptionally active regions(Pseudogene.org + Tiling.GersteinLab.org)

• Molecular Networks Using molecular networks to integrate & mine functional

genomics information and describe protein function on a large-scale (Networks.GersteinLab.org)

• Macromolecular motions Analyzing select populations of 3D-structures in detail, trying to

understand their flexibility in terms of packing (MolMovDB.org)

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[IHGSC, Nature 409, 2001][Venter et al. Science 29, 2001]

2001: Most of the genome is not coding (only ~1.2% exon). It consists of elements such as repeats, regulatory regions, non-coding RNAs, origins of replication, pseudogenes, segmental duplications....What do these elements do? How should they be annotated?

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[IHGSC, Nature 409, 2001][ENCODE Consortium, Nature 447, 2007]

2007 : Pilot results from ENCODE Consortium on decoding what the bases do - 1% of Genome (30 Mb in 44 regions)- Tiling Arrays to assay Transcription & Binding- Multi-organism sequencing and alignment- Careful Annotation- Variation Data

SnyderWeissman

Miller

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Identifiable Features of a Pseudogene (RPL21)

Gerstein & Zheng. Sci Am 295: 48 (2006).

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Very Different Distribution of Genes and Pseudogenes in

Different Organisms

E. coli, K-12

E. coli, O157

Yeast

Worm

Fly

Mouse

Human

Cress

Rickettsia

Leprosy

Plague

110

241

101

95

160

1,116

2411.1

3.3

4.6

4.6

5.5

12.2

100.3

131

125

2,932

3,272

-25000 -15000 -5000 5000 15000 25000 35000

-25000 -15000 -5000 5000 15000 25000 35000

No. of Genes

No. of Pseudogenes

Genome Size

Number of Genes / Pseudogenes

0 5000 15000 25000 35000Genome Size [log Mb]

E. coli, K-12

E. coli, O157

Yeast

Worm

Fly

Mouse

Human

Cress

Rickettsia

Leprosy

Plague

110

241

101

95

160

1,116

2411.1

3.3

4.6

4.6

5.5

12.2

100.3

131

125

2,932

3,272

-25000 -15000 -5000 5000 15000 25000 35000

-25000 -15000 -5000 5000 15000 25000 35000

No. of Genes

No. of Pseudogenes

Genome Size

Number of Genes / Pseudogenes

0 5000 15000 25000 35000Genome Size [log Mb]

Zhang & Gerstein (2004) Curr Opin Genet Dev 14: 328 + Harrison & Gerstein (2002) J Mol Biol 318: 1155

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Historyof

Pseudogene

Preservation

Absent

Present with Disablement

Present without Disablement

Zheng et al. (2007) Gen. Res.

Based on alignment from ENCODE MSA

group

representative pseudogenes drawn from 201 totalA B C D E F

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Using phastOdd value to examine neutral evolution of pseudogenes

most goodcandidates

for studying

mutational processes

a few non-proc. G under constraint


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Ex. Pseudogene

Intersecting Transcript-

ional Evidence

Composite ChIPhit

SpecialG

tracks in browser

diTAG

CAGE

TARs

ChIP-chip


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• Human Genome Annotation (pseudogenes) Characterizing the function of non-coding regions, focusing on protein

fossils and novel transcriptionally active regions(Pseudogene.org + Tiling.GersteinLab.org)

• Molecular Networks Using molecular networks to integrate & mine functional genomics

information and describe protein function on a large-scale (Networks.GersteinLab.org)



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Toward Systematic Ontologies for Function,

using Networks

All of SCOP entries

1Oxido-

reductases

3Hydrolases

1.1Acting on CH-OH

1.1.1.1 Alcohol dehydrogenase

ENZYME

1.1.1NAD and

NADP acceptor

NON-ENZYME

3.1Acting on

ester bonds

1 Meta-bolism

1.1 Carb.

metab.

3.8 Extracel.

matrix

3.8.2 Extracel.

matrixglyco-protein

1.1.1 Polysach.

metab.

3.8.2.1 Fibro-nectin

General similarity Functional class similarityPrecise functional similarity

3 Cell

structure

1.5Acting on

CH-NH

3.4Acting on

peptide bonds

1.1.1.3Homoserine

dehydrogenase

1.2Nucleotide

metab.

3.1 Nucleus

3.8.2.2Tenascin

1.1.1.1 Glycogenmetab.

1.1.1.2 Starchmetab.

3.1.1.1 Carboxylesterase

3.1.1Carboxylic

ester hydro-lases

3.1.1.8 Cholineesterase

General Networks[Eisenberg et al.]

Hierarchies & DAGs[Enzyme, Bairoch; GO, Ashburner;

MIPS, Mewes, Frishman]

Interaction Vectors [Lan et al, IEEE 90:1848]

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Networks occupy a midway point in terms of level of understanding

1D: Complete Genetic Partslist

~2D: Bio-molecularNetwork

Wiring Diagram

3D: Detailed structural

understanding of cellular machinery

[Jeong et al. Nature, 41:411][Fleischmann et al., Science, 269 :496]

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Networks as a universal language

Disease Spread

[Krebs]

ProteinInteractions

[Barabasi] Social Network

Food Web

Neural Network[Cajal]

ElectronicCircuit

Internet[Burch & Cheswick]

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TopNet – an automated web tool

[Yu et al., NAR (2004); Yip et al. Bioinfo. (2006); Similar tools include Cytoscape.org, Idekar, Sander et al]

(vers. 2 :"TopNet-like

Yale Network Analyzer")

Normal website + Downloaded code (JAVA)+ Web service (SOAP) with Cytoscape plugin

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Target Genes

Transcription Factors

142 transcription factors

3,420 target genes

7,074 regulatory interactions

From integrating data from Snyder et al... TRANSFAC

Yeast Regulatory Network: a platform for integration

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Yeast Regulatory Hierarchy: the Middle-managers Rule

[Yu et al., PNAS (2006)]

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Yeast Network Similar in Structure to Government Hierarchy

with Respect to Middle-managers

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Characteristics of Regulatory Hierarchy: Middle Managers are Information Flow

Bottlenecks

[Yu et al., PNAS (2006)]

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Do not reproduce without permission

Surveying structural flexibility on a proteomic scale

• Questions How do we describe a wide-range of

structural variability in standard terms? Can we develop simple models to

explain constraints on protein flexibility? What information about flexible hinge

location is encoded in sequence?

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MolMovDB.org

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Example "Morph": MBP

2 Known Crystal Structures (endpoints, not necessarily same seq.)

Std. Geometric Stats. (from structure comparison)

Pathway Interpolation

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Interdigitating structure of protein interfaces constrains motion

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Packing Tools - Voronoi software to calculate packing volumes (geometry.molmovdb.org)

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Small Shearing Domain Motions: Molybdenum-binding protein & GAPDH

[Lawson] [Wonacott]

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Proteins With Shear Motions are Often Divided into Layers

GAPDH Hexokinase [Steitz]

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Transferrin: Interdomain Hinges

[Baker]

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Transferrin hinge involves absence of steric constraints (continuously

maintained interfaces), esp. at hinge

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Proteomics Research @ GersteinLab.org

• Macromolecular motions Analyzing select populations of 3D-structures in detail, trying to understand their

flexibility in terms of packing (MolMovDB.org)

• Molecular Networks Using molecular networks to integrate & mine functional genomics information

and describe protein function on a large-scale (Networks.GersteinLab.org)

• Human Genome Annotation (protein fossils) Characterizing the function of non-coding regions, focusing on protein fossils and

novel transcriptionally active regions(Pseudogene.org + Tiling.GersteinLab.org)

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RNAi:Birth of a Field in

the Literature Culmin-ating in the 2006

Nobel

Source:Gerstein & Douglas.

PLoS Comp. Bio. 3:e80 (2007)

PubNet.GersteinLab.org

do not reproduce without permission 1 gerstein.info/talks (c) 2007 1 (c) mark gerstein, 2002, yale,...

Documents

c mark gerstein

infotalks c

harrison gerstein

total ab c def slide

function of noncoding

protein function

active regions

molecular networks