Relative

Impact

of

Nucleotide

and

Copy

Number

Variation

on

Gene

Expression

Phenotypes

Barbara

E.

Stranger

et

al.

Science

-LRB-

-RRB-

DOI

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REPORTS

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Single-letter

abbreviations

for

the

amino

acid

residues

are

as

follows

A

Ala

C

Cys

D

Asp

E

Glu

F

Phe

G

Gly

H

His

I

Ile

K

Lys

L

Leu

M

Met

N

Asn

P

Pro

Q

Gln

R

Arg

S

Ser

T

Thr

V

Val

W

Trp

and

Y

Tyr

F.

Forster

O.

Medalia

N.

Zauberman

W.

Baumeister

D.

Fass

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

P.

Zhu

et

al.

Nature

-LRB-

-RRB-

H.

S.

Yin

X.

Wen

R.

G.

Paterson

R.

A.

Lamb

T.

S.

Jardetzky

Nature

-LRB-

-RRB-

Y.

Gaudin

H.

Raux

A.

Flamand

R.

W.

Ruigrok

J.

Virol

-LRB-

-RRB-

E.

Krissinel

K.

Henrick

in

CompLife

M.

R.

Berthold

R.

Glen

K.

Diederichs

O.

Kohlbacher

I.

Fischer

Eds.

Lecture

Notes

in

Bioinformatics

vol

-LRB-

Springer-Verlag

Berlin

-RRB-

pp.

F.

Lafay

A.

Benmansour

K.

Chebli

A.

Flamand

J.

Gen.

Virol

-LRB-

-RRB-

Y.

Gaudin

J.

Virol

-LRB-

-RRB-

C.

Tuffereau

J.

Benejean

D.

Blondel

B.

Kieffer

A.

Flamand

EMBO

J.

-LRB-

-RRB-

L.

V.

Chernomordik

M.

M.

Kozlov

Cell

-LRB-

-RRB-

C.

M.

Carr

C.

Chaudhry

P.

S.

Kim

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

W.

L.

Delano

The

PyMOL

Molecular

Graphics

System

-LRB-

DeLano

Scientific

San

Carlos

CA

-RRB-

available

at

We

thank

A.

Flamand

for

constant

support

on

this

project

J.

Lepault

R.

Ruigrok

M.

Knossow

A.

Benmansour

C.

Tuffereau

and

D.

Blondel

for

helpful

discussions

at

different

stages

of

this

work

and

C.

Maheu

for

virus

purification

Data

collections

were

performed

at

the

Swiss

Light

Source

-LRB-

SLS

-RRB-

Paul

Scherrer

Institut

Villigen

Switzerland

and

at

the

European

Synchrotron

Radiation

Facility

-LRB-

ESRF

-RRB-

Grenoble

France

We

acknowledge

the

help

of

T.

Tomizaki

-LRB-

beamline

SLS

-RRB-

G.

Leonard

and

D.

Bourgeois

-LRB-

beamlines

and

ESRF

-RRB-

and

S.

Duquerroy

and

G.

Squires

in

data

collection

We

acknowledge

support

from

the

CNRS

and

INRA

the

CNRS

program

Physique

et

Chimie

du

Vivant

the

INRA

Animal

health

department

program

Les

virus

des

animaux

et

leurs

interactions

avec

la

cellule

the

Minist

re

de

l'

ducation

nationale

de

la

recherche

et

de

la

technologie

program

Action

Concert

e

Incitative

blanche

and

the

Agence

Nationale

de

la

Recherche

program

S.R.

was

the

recipient

of

an

Agence

Nationale

de

Recherche

sur

le

Sida

fellowship

during

part

of

this

project

Coordinates

and

structure

factors

have

been

deposited

with

the

Protein

Data

Bank

under

accession

code

Supporting

Online

Material

Materials

and

Methods

Figs

to

Table

References

Movie

September

accepted

January

science

Relative

Impact

of

Nucleotide

and

Copy

Number

Variation

on

Gene

Expression

Phenotypes

Barbara

E.

Stranger

Matthew

S.

Forrest

Mark

Dunning

Catherine

E.

Ingle

Claude

Beazley

Natalie

Thorne

Richard

Redon

Christine

P.

Bird

Anna

de

Grassi

Charles

Lee

Chris

Tyler-Smith

Nigel

Carter

Stephen

W.

Scherer

Simon

Tavar

Panagiotis

Deloukas

Matthew

E.

Hurles

Emmanouil

T.

Extensive

studies

are

currently

being

performed

to

associate

disease

susceptibility

with

one

form

of

genetic

variation

namely

single-nucleotide

polymorphisms

-LRB-

SNPs

-RRB-

In

recent

years

another

type

of

common

genetic

variation

has

been

characterized

namely

structural

variation

including

copy

number

variants

-LRB-

CNVs

-RRB-

To

determine

the

overall

contribution

of

CNVs

to

complex

phenotypes

we

have

performed

association

analyses

of

expression

levels

of

transcripts

with

SNPs

and

CNVs

in

individuals

who

are

part

of

the

International

HapMap

project

SNPs

and

CNVs

captured

and

of

the

total

detected

genetic

variation

in

gene

expression

respectively

but

the

signals

from

the

two

types

of

variation

had

little

overlap

Interrogation

of

the

genome

for

both

types

of

variants

may

be

an

effective

way

to

elucidate

the

causes

of

complex

phenotypes

and

disease

in

humans

to

be

associated

with

phenotypic

variation

either

through

direct

causal

effects

or

by

serving

as

proxies

for

other

causal

variants

with

which

they

are

highly

correlated

-LRB-

i.e.

in

linkage

disequilibrium

-RRB-

-LRB-

-RRB-

An

understanding

of

this

association

has

been

facilitated

by

the

validation

of

millions

of

SNPs

by

the

International

HapMap

project

-LRB-

-RRB-

However

during

the

last

few

years

structural

variants

such

as

copy

number

variants

-LRB-

CNVs

-RRB-

defined

as

DNA

segments

that

are

kb

or

larger

in

size

present

at

variable

copy

number

in

comparison

with

a

reference

genome

-LRB-

-RRB-

have

attracted

much

attention

-LRB-

-RRB-

It

has

become

apparent

that

they

are

quite

common

in

the

human

genome

-LRB-

-RRB-

and

can

have

dramatic

phenotypic

consequences

as

a

result

of

altering

gene

dosage

disrupting

coding

Wellcome

Trust

Sanger

Institute

Wellcome

Trust

Genome

Campus

Hinxton

Cambridge

UK

of

Oncology

University

of

Cambridge

Cancer

Research

UK

Cambridge

Research

Institute

Li

Ka

Shing

Centre

Robinson

Way

Cambridge

UK

di

Tecnologie

Biomediche-Sezione

di

Bari

Consiglio

Nazionale

della

Ricerche

-LRB-

CNR

-RRB-

Bari

Italy

of

Pathology

Brigham

and

Women

's

Hospital

and

Harvard

Medical

School

Boston

MA

USA

Institute

of

Harvard

and

Massachusetts

Institute

of

Technology

Cambridge

MA

USA

Centre

for

Applied

Genomics

and

Program

in

Genetics

and

Genomic

Biology

The

Hospital

for

Sick

Children

MaRS

Centre

Toronto

Ontario

Canada

of

Molecular

and

Medical

Genetics

University

of

Toronto

Toronto

Ontario

Canada

in

Molecular

and

Computational

Biology

University

of

Southern

California

Los

Angeles

CA

USA

U

nderstanding

the

genetic

basis

of

phenotypic

variation

in

human

populations

is

currently

one

of

the

major

goals

in

human

genetics

Gene

expression

-LRB-

the

transcription

of

DNA

into

mRNA

-RRB-

has

been

interrogated

in

a

variety

of

species

and

experimental

scenarios

in

order

to

investigate

the

genetic

basis

of

variation

in

gene

regulation

-LRB-

-RRB-

as

well

as

to

tease

apart

regulatory

networks

-LRB-

-RRB-

In

some

respects

a

comprehensive

survey

of

gene

expression

phenotypes

-LRB-

steady-state

levels

of

mRNA

-RRB-

serves

as

a

proxy

for

the

breadth

and

nature

of

phenotypic

variation

in

human

populations

-LRB-

-RRB-

Much

of

the

observed

variation

in

mRNA

transcript

levels

may

be

compensated

at

higher

stages

of

regulatory

networks

but

an

understanding

of

the

nature

of

genetic

variants

that

affect

gene

expression

will

provide

an

essential

framework

and

model

for

elucidating

the

causes

of

other

types

of

phenotypic

variation

Single-nucleotide

polymorphisms

-LRB-

SNPs

-RRB-

have

long

been

known

VOL

SCIENCE

To

whom

correspondence

should

be

addressed

E-mail

-LRB-

E.T.D.

-RRB-

meh@sanger.ac.uk

-LRB-

M.E.H.

-RRB-

FEBRUARY

Downloaded

from

on

May

REPORTS

quences

or

perturbing

long-range

gene

regulation

-LRB-

-RRB-

Evidence

has

been

presented

that

increased

copy

number

can

be

positively

-LRB-

-RRB-

or

negatively

-LRB-

-RRB-

correlated

with

gene

expression

levels

-LRB-

for

example

deletion

of

a

transcriptional

repressor

could

serve

to

elevate

gene

expression

-RRB-

but

the

relative

contribution

of

such

large

genetic

variants

-LRB-

i.e.

CNVs

-RRB-

and

smaller

variants

-LRB-

i.e.

SNPs

-RRB-

to

phenotypic

variation

has

not

been

evaluated

It

is

also

still

unknown

whether

SNPs

can

serve

as

proxies

to

CNVs

-LRB-

-RRB-

and

whether

the

complex

nature

of

some

CNVs

requires

that

they

be

surveyed

directly

-LRB-

-RRB-

We

have

used

the

phase

I

HapMap

SNPs

-LRB-

-RRB-

and

the

recently

described

CNV

data

ascertained

in

the

same

HapMap

populations

-LRB-

-RRB-

for

correlation

with

genomewide

gene

expression

variation

in

the

same

individuals

Gene

expression

was

interrogated

in

lymphoblastoid

cell

lines

of

all

unrelated

HapMap

individuals

-LRB-

-RRB-

from

four

populations

-LRB-

CEU

Utah

residents

with

ancestry

from

northern

and

western

Europe

CHB

Han

Chinese

in

Beijing

JPT

Japanese

in

Tokyo

YRI

Yoruba

in

Ibadan

Nigeria

-RRB-

in

four

technical

replicates

-LRB-

see

Methods

-RRB-

Out

of

the

transcripts

that

were

interrogated

the

normalized

values

for

transcripts

-LRB-

genes

-RRB-

were

included

in

the

analysis

-LSB-

see

Methods

and

-LRB-

-RRB-

-RSB-

The

SNP

genotypes

from

phase

I

HapMap

-LRB-

-RRB-

were

used

in

the

analysis

-LRB-

see

Methods

-RRB-

CNV

data

were

represented

by

ratios

from

comparative

genomic

hybridization

-LRB-

CGH

-RRB-

of

each

HapMap

individual

against

a

common

reference

individual

on

an

array

comprising

largeinsert

clones

covering

of

the

euchromatic

portion

of

the

genome

-LRB-

-RRB-

ratios

from

two

sets

of

clones

were

analyzed

the

whole

set

of

autosomal

clones

-LRB-

CGH

clones

-RRB-

and

the

autosomal

clones

corresponding

to

CNVs

present

in

at

least

two

HapMap

individuals

-LRB-

CNV

clones

-RRB-

-LRB-

-RRB-

We

excluded

genes

on

sex

chromosomes

because

of

their

imbalance

in

males

and

females

We

performed

linear

regression

-LRB-

on

each

of

the

four

populations

separately

-RRB-

between

normalized

quantitative

gene

expression

values

and

SNP

genotypes

or

clone

ratios

that

were

near

the

gene

-LRB-

SNP

position

or

clone

midpoint

within

Mb

and

Mb

respectively

of

the

probe

midpoint

position

-RRB-

We

used

different

window

sizes

for

SNPs

and

clones

because

clones

are

large

-LRB-

median

size

of

kb

-RRB-

and

structural

variants

can

exert

long-range

effects

-LRB-

-RRB-

so

a

window

is

more

appropriate

Statistical

significance

was

evaluated

through

the

use

of

permutations

-LRB-

-RRB-

as

previously

described

-LRB-

-RRB-

and

a

corrected

P

value

threshold

of

was

applied

-LRB-

see

Methods

-RRB-

Repeated

permutation

exercises

showed

that

our

permutation

thresholds

were

very

stable

-LRB-

see

table

-RRB-

We

tested

a

large

number

of

genes

so

an

additional

correction

was

required

This

could

be

done

either

by

adjusting

the

threshold

to

a

new

corrected

threshold

above

which

all

genes

are

expected

to

be

significant

-LRB-

e.g.

Bonferroni

correction

-RRB-

or

by

setting

the

threshold

to

a

value

that

generates

a

satisfactory

false-discovery

rate

-LRB-

FDR

-RRB-

We

have

used

the

second

and

we

have

estimated

the

FDR

on

the

basis

of

the

number

of

genes

tested

and

have

required

that

in

all

cases

at

least

of

the

genes

called

significant

are

estimated

to

be

truly

significant

Given

that

there

are

genes

that

lie

within

Mb

of

SNPs

and

within

Mb

of

the

full

set

of

CGH

clones

and

genes

that

lie

within

Mb

from

the

CNV

clones

-LRB-

from

to

depending

on

the

population

owing

to

missing

data

-RRB-

we

expect

this

analysis

to

generate

false-positive

association

signals

for

approximately

and

genes

respectively

in

each

population

Of

the

genes

tested

we

detected

significant

associations

with

at

least

one

SNP

for

and

genes

for

CEU

CHB

JPT

and

YRI

respectively

-LRB-

e.g.

Table

and

table

-RRB-

These

comprise

a

total

of

nonredundant

genes

of

which

-LRB-

-RRB-

were

replicated

at

the

same

significance

level

in

at

least

one

other

population

and

of

those

-LRB-

-RRB-

were

significant

in

all

four

populations

-LRB-

Table

and

table

-RRB-

As

expected

we

have

limited

power

to

detect

weak

effects

because

of

the

small

sample

sizes

The

minimum

detected

squared

regression

coefficient

-LRB-

-RRB-

which

reflects

the

proportion

of

expression

variance

accounted

for

by

the

linear

association

with

allele

counts

was

However

some

very

strong

effects

were

detected

that

in

some

cases

had

an

close

to

-LRB-

Fig.

and

fig

-RRB-

We

detected

a

strong

preference

for

associated

SNPs

to

be

close

to

their

respective

genes

most

of

which

were

within

kb

of

the

interrogated

expression

probe

-LRB-

Fig.

A

and

C

-RRB-

In

summary

we

detected

a

large

number

of

regions

that

appear

to

carry

genetic

variation

affecting

gene

expression

To

evaluate

the

effect

of

experimental

variation

and

hence

the

robustness

of

our

associations

we

compared

the

list

of

gene

expression

associations

from

our

previous

study

-LRB-

-RRB-

in

which

we

detected

expression

associations

significant

at

the

permutation

threshold

in

the

CEU

population

Of

those

expression

phenotypes

went

into

the

current

analysis

of

which

-LRB-

-RRB-

were

called

significant

at

the

same

permutation

threshold

-LRB-

-RRB-

in

the

same

population

The

previous

study

was

performed

with

different

batches

of

cells

by

using

RNA

extracted

in

a

different

laboratory

with

RNA

levels

quantified

on

a

different

type

of

array

-LRB-

custom

versus

genomewide

array

-RRB-

so

the

high

degree

of

experimental

and

statistical

replication

strongly

suggests

that

the

signals

we

detected

are

robust

and

stable

to

experimental

variation

in

expression

measurements

Of

the

genes

tested

we

detected

significant

associations

with

at

least

one

of

the

autosomal

CGH

clones

in

and

genes

in

CEU

CHB

JPT

and

YRI

respectively

-LRB-

nonredundant

genes

-RRB-

of

which

-LRB-

-RRB-

were

replicated

at

the

same

significance

level

in

at

least

one

other

population

and

of

those

-LRB-

-RRB-

were

significant

in

all

four

populations

-LRB-

Fig.

Table

and

table

and

figs

and

-RRB-

Not

all

associated

clones

were

within

CNVs

defined

using

the

stringent

criteria

of

-LRB-

-RRB-

-LSB-

out

of

-LRB-

-RRB-

associated

clones

were

previously

defined

as

CNVs

-RSB-

and

it

is

likely

that

some

of

these

clones

encompass

smaller

CNVs

that

are

detectable

though

asso

Table

Numbers

of

genes

with

significant

associations

to

SNPs

-LRB-

SNP-probe

distance

Mb

-RRB-

all

CGH

clones

-LRB-

clone-probe

distance

Mb

-RRB-

or

CNV

clones

-LRB-

clone-probe

distance

Mb

-RRB-

as

assessed

by

permutations

together

with

the

numbers

of

overlaps

between

SNP-associated

genes

and

CGH

or

CNV

clone-associated

genes

-LRB-

probe-variant

distance

Mb

for

both

SNPs

and

clones

-RRB-

-LRB-

see

table

-RRB-

CNV

-LRB-

Mb

-RRB-

CGH

clones

CEU

CHB

JPT

YRI

Nonredundant

CEU

CHB

JPT

YRI

Nonredundant

CEU

CHB

JPT

YRI

Nonredundant

362 221 319 481

CNV

clones

CNV

-LRB-

Mb

-RRB-

SNP

overlap

CGH

clones

CNV

clones

Gene

population

SNP

Permutation

threshold

643 14 110 673

10 134 752

13 166 815

14 451 1886

Permutation

threshold

Permutation

threshold

SCIENCE

VOL

FEBRUARY

Downloaded

from

on

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REPORTS

ciations

of

ratios

across

a

population

but

can

not

be

detected

as

extreme

outliers

in

their

ratios

in

any

one

individual

-LSB-

as

is

required

for

classification

as

a

CNV

in

-LRB-

-RRB-

-RSB-

-LRB-

see

example

below

-RRB-

For

common

-LRB-

minor

allele

frequency

-RRB-

CNVs

-LRB-

encompassing

CGH

clones

-RRB-

accurate

CNV

genotypes

were

available

We

used

these

genotypes

to

validate

the

statistical

power

of

performing

association

analysis

using

ratios

directly

rather

than

genotypes

There

was

strong

correlation

between

values

or

P

values

generated

using

the

ratio

signals

or

the

CNV

genotypes

-LRB-

Pearson

correlation

coefficients

-RRB-

indicating

that

ratios

can

be

used

directly

Little

prior

data

exists

on

CNV-expression

associations

against

which

to

compare

and

demonstrate

the

robustness

of

our

associations

One

recent

study

-LRB-

-RRB-

demonstrated

three

associations

between

common

deletions

and

gene

expression

in

a

subset

of

the

CEU

Two

of

these

deletions

are

covered

by

our

CGH

data

The

reported

expression

association

caused

by

the

largest

of

these

two

deletions

is

also

captured

in

our

analysis

-LRB-

influencing

-RRB-

and

we

extend

this

observation

to

show

that

this

deletion

also

affects

the

expression

of

three

other

nearby

genes

-LRB-

and

-RRB-

and

that

these

associations

replicate

across

all

four

populations

The

smaller

deletion

of

only

kb

reported

previously

-LRB-

-RRB-

as

affecting

expression

of

is

below

the

expected

resolution

of

the

CGH

data

Nonetheless

we

observe

an

association

that

although

it

does

not

pass

our

stringent

permutation

threshold

-LRB-

-RRB-

has

significant

nominal

P

values

in

all

four

populations

-LRB-

PCEU

PYRI

PJPT

PCHB

-RRB-

This

suggests

that

effects

of

CNVs

far

smaller

than

genomic

regions

that

met

our

criteria

to

be

called

a

CNV

within

the

CGH

platform

can

be

detected

and

replicated

in

multiple

populations

with

our

analysis

Having

investigated

the

potential

contribution

of

CNV

to

variation

in

gene

expression

by

using

data

from

all

CGH

clones

we

interrogated

the

nature

of

CNV

effects

on

gene

expression

in

finer

detail

by

performing

association

tests

of

clones

within

high

confidence

CNVs

-LRB-

see

above

-RRB-

with

expression

of

the

genes

in

order

to

generate

a

set

of

high

stringency

associations

for

which

the

presence

of

an

underlying

CNV

has

already

been

validated

Significant

associations

with

at

least

one

of

the

CNV

clones

were

detected

for

and

genes

in

CEU

CHB

JPT

and

YRI

respectively

-LRB-

nonredundant

genes

-RRB-

-LRB-

table

-RRB-

Thirty-four

of

the

genes

-LRB-

-RRB-

associated

with

CNV

clones

have

a

significant

signal

in

at

least

two

populations

-LRB-

Table

-RRB-

of

which

-LRB-

-RRB-

were

associated

in

all

populations

Some

CNV

clones

were

associated

with

more

than

one

gene

in

the

same

population

a

notable

example

was

a

single

CNV

clone

associated

with

expression

of

four

genes

in

all

populations

-LRB-

genes

see

above

-RRB-

CNVs

detected

by

CGH

can

be

classified

into

five

classes

deletion

duplication

deletion

and

duplication

at

the

same

locus

multiallelic

and

complex

-LRB-

-RRB-

we

find

all

classes

of

CNV

represented

among

the

significant

associations

Despite

the

clear

preference

for

genes

to

lie

close

to

their

associated

CNVs

-LRB-

Fig.

B

and

D

-RRB-

of

the

expression

probes

associated

with

a

CGH

clone

were

located

outside

the

CNVs

encompassing

that

clone

-LRB-

-RRB-

This

suggests

that

rather

than

altering

gene

dosage

about

half

the

CNV

effects

are

caused

by

disruption

of

the

gene

-LRB-

some

parts

of

the

gene

but

not

the

probe

are

within

in

the

CNV

-RRB-

or

affect

regulatory

regions

and

other

functional

regions

that

have

an

impact

on

gene

expression

When

we

extended

our

analysis

to

consider

associations

between

genes

and

CNVs

up

to

Mb

apart

we

detected

a

few

significant

long-distance

associations

beyond

Mb

-LRB-

table

-RRB-

These

types

of

long-range

effects

are

becoming

more

apparent

through

recent

studies

looking

in

detail

at

specific

genomic

regions

-LRB-

-RRB-

A

small

minority

-LRB-

to

-RRB-

of

the

significant

CNV-expression

associations

have

a

negative

correlation

between

copy

number

and

gene

expression

which

suggests

that

not

all

the

detected

effects

are

of

the

conventional

type

wherein

gene

expression

levels

increase

with

gene

copy

number

-LRB-

table

-RRB-

Almost

all

-LRB-

out

of

-RRB-

of

the

associations

that

are

shared

between

populations

also

exhibit

the

same

direction

of

correlation

in

all

populations

The

two

exceptions

could

result

from

the

CNVs

being

in

linkage

disequilibrium

with

different

regulatory

variants

in

different

populations

or

because

of

SNP

CNV

interactions

However

the

strong

bias

toward

positive

correlations

between

copy

number

and

expression

levels

implies

that

the

vast

majority

of

these

associations

are

attributable

to

the

CNV

itself

and

not

to

a

linked

variant

We

next

determined

whether

the

same

associations

were

also

captured

by

SNPs

-LRB-

Fig.

and

figs

and

-RRB-

We

only

considered

those

CGH

clones

or

CNVs

within

Mb

of

the

probe

so

that

the

analysis

is

comparable

to

that

of

the

SNPs

-LRB-

total

of

and

genes

for

CGH

clones

and

CNVs

respectively

-RRB-

We

expect

some

of

the

CNVs

to

be

correlated

with

SNPs

via

common

genealogical

history

-LRB-

linkage

disequilibrium

-RRB-

and

therefore

their

effect

on

gene

expression

would

also

be

captured

by

SNP

associations

Fewer

than

-LRB-

in

all

populations

-RRB-

of

the

detected

CGH

clone

associations

overlapped

with

SNP

associations

-LRB-

Table

-RRB-

even

when

we

included

CGH

and

SNP

associations

with

the

same

gene

but

in

different

populations

-LSB-

out

of

-LRB-

-RRB-

genes

with

significant

CGH

clone

associations

also

had

a

SNP

association

in

any

population

-RSB-

The

same

is

true

of

CNV

clone

associations

Only

of

genes

-LRB-

-RRB-

with

CNV

clone

associations

within

Mb

also

had

a

SNP

association

in

any

population

and

if

we

required

the

association

in

the

same

population

only

-LRB-

-RRB-

of

genes

had

a

SNP

association

On

the

basis

of

previous

work

characterizing

the

patterns

of

linkage

disequilibrium

around

CNVs

-LRB-

-RRB-

we

considered

that

this

low

overlap

between

CNVor

CGH

clone

associations

with

SNP

associations

might

be

due

in

part

either

to

a

low

density

of

successfully

genotyped

SNPs

around

some

CNVs

or

to

the

suppression

of

apparent

LD

by

recurrent

mutation

at

some

CNVs

Segmental

duplications

-LRB-

SDs

-RRB-

are

the

primary

cause

of

low

Table

Sharing

of

associations

between

populations

CGH

clone

-LRB-

Mb

-RRB-

CEU-CHB-JPT-YRI

CEU-CHB-JPT

CEU-CHB-YRI

CEU-JPT-YRI

CHB-JPT-YRI

CEU-CHB

CEU-JPT

CEU-YRI

CHB-JPT

CHB-YRI

JPT-YRI

CEU

only

CHB

only

JPT

only

YRI

only

Sum

Gene

associations

in

at

least

two

populations

Percentage

of

total

Gene

associations

in

single

populations

Percentage

of

total

CNV

clone

-LRB-

Mb

-RRB-

SNP

-LRB-

Mb

-RRB-

18 27 116 107

122 212 888 331

FEBRUARY

VOL

SCIENCE

Downloaded

from

on

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REPORTS

SNP

densities

in

HapMap

Phase

I

because

of

the

difficulties

in

developing

robust

SNP

genotyping

assays

within

them

-LRB-

-RRB-

We

did

not

observe

enrichment

of

segmentally

duplicated

sequences

within

the

CGH

and

CNV

clones

that

did

not

share

signals

with

SNPs

relative

to

those

CGH

and

CNV

clones

that

did

share

signals

with

SNPs

However

we

observe

a

excess

of

compound

CNVs

-LSB-

CNVs

with

more

than

one

mutation

event

on

the

basis

of

classification

of

the

CNVs

in

-LRB-

-RRB-

-RSB-

in

associations

that

are

not

shared

with

SNPs

relative

to

those

that

are

shared

-LRB-

Fisher

's

exact

test

P

-RRB-

Thus

our

analysis

suggests

that

recurrent

mutation

is

a

likely

factor

reducing

overlap

between

CNV

and

SNP

associations

CNV

associations

that

were

also

detected

with

SNPs

were

clearly

biased

toward

large

effect

sizes

-LRB-

tables

and

-RRB-

Of

the

genes

with

both

SNP

and

CNV

associations

in

the

same

population

shared

the

association

in

two

or

more

populations

-LRB-

giving

a

redundant

total

across

the

four

populations

of

shared

CNV

and

SNP

associations

-RRB-

The

ratio

of

out

of

-LRB-

-RRB-

population

shared

associations

is

larger

than

that

observed

in

all

CNV

associations

-LRB-

out

of

-RRB-

potentially

suggesting

that

associations

with

higher

frequency

older

CNVs

are

more

likely

to

be

captured

by

SNPs

For

the

associations

-LRB-

representing

genes

see

above

-RRB-

captured

both

by

CNVs

and

SNPs

in

the

same

population

we

observed

that

SNPs

and

CNVs

were

themselves

highly

correlated

for

out

of

SNP-CNV

pairs

-LRB-

Pearson

correlation

P

-RRB-

suggesting

that

for

these

cases

the

CNVand

SNP

captured

the

same

effect

and

that

only

a

small

fraction

of

the

associations

captured

both

by

SNPs

and

CNVs

occurs

by

chance

In

summary

out

of

-LRB-

-RRB-

of

genes

with

a

significant

CNV

association

are

not

associated

with

SNPs

The

large-scale

-LRB-

typically

kb

-RRB-

copy

number

variation

analyzed

here

appears

to

be

associated

with

about

to

as

many

gene

expression

phenotypes

as

captured

by

SNPs

and

the

majority

of

these

effects

can

not

be

explained

by

altered

dosage

of

the

entire

gene

but

by

gene

disruption

and

its

impact

on

the

regulatory

landscape

of

the

region

where

these

CNVs

occur

When

we

restrict

the

analysis

to

within

Mb

of

the

probe

of

the

expressed

gene

we

detected

genes

associated

with

CGH

clones

or

SNPs

of

which

are

associated

with

CGH

clones

with

SNPs

and

with

both

Of

the

genes

associated

with

CNV

clones

or

SNPs

are

associated

with

CNV

clones

with

SNPs

and

with

both

Whereas

the

phase

I

HapMap

SNPs

likely

capture

a

large

fraction

of

the

SNP

effects

in

the

genome

-LRB-

-RRB-

only

a

small

minority

of

the

CNVs

in

the

genome

were

considered

here

CNVs

kb

in

length

are

far

more

numerous

than

CNVs

kb

in

length

-LRB-

-RRB-

As

a

consequence

to

is

a

minimal

estimate

of

the

proportion

of

heritable

gene

expression

variation

that

is

explained

by

copy

number

variation

Our

study

has

attempted

to

evaluate

the

relative

impact

of

CNVs

and

SNPs

on

phenotypic

variation

in

human

populations

Within

the

limitations

of

our

samples

tissue

type

SNP

coverage

and

CNV

resolution

each

type

of

genetic

variation

captures

a

substantial

number

of

largely

mutually

exclusive

effects

on

gene

expression

We

also

demonstrate

that

both

CNV

and

A

CEU

CHB

B

slope

CEU

CHB

JPT

YRI

JPT

YRI

Distance

Distance

C

CEU

CHB

D

CEU

CHB

Frequency

JPT

YRI

Frequency

JPT

YRI

Adjusted

Adjusted

Fig.

Strength

of

association

as

a

function

of

distance

between

-LRB-

A

-RRB-

SNP

and

probe

and

-LRB-

B

-RRB-

CNV

and

probe

Positive

associations

between

mRNA

levels

and

clone

ratios

are

shown

in

red

negative

associations

in

black

Distance

equal

to

zero

corresponds

to

the

probe

residing

within

the

SCIENCE

CNV

In

each

population

panel

only

the

details

for

the

most

significant

association

per

significant

gene

are

shown

Distribution

of

r

values

for

the

most

significant

association

per

significant

gene

for

-LRB-

C

-RRB-

SNPexpression

associations

and

-LRB-

D

-RRB-

clone-expression

associations

VOL

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-RRB-

-LRB-

p-value

-RRB-

REPORTS

A

-LRB-

p-value

-RRB-

coordinate

B

Expression

Expression

-LRB-

p-value

-RRB-

CEU

CNV

CNV

Expression

SNP

Genotype

clone

SNP

coordinate

Expression

-LRB-

p-value

-RRB-

Expression

Expression

-LRB-

p-value

-RRB-

CHB

CNV

SNP

Genotype

CNV

clone

SNP

coordinate

coordinate

Expression

Expression

-LRB-

p-value

-RRB-

-LRB-

p-value

-RRB-

JPT

CNV

Expression

SNP

Genotype

clone

SNP

CNV

coordinate

-LRB-

p-value

-RRB-

coordinate

coordinate

Expression

Expression

-LRB-

p-value

-RRB-

YRI

CNV

Expression

CNV

SNP

Genotype

clone

SNP

coordinate

Fig.

Examples

of

SNP-expression

and

clone-expression

associations

in

the

four

HapMap

populations

-LRB-

A

-RRB-

Clone-expression

association

for

chromosome

-LRB-

chr

-RRB-

Significant

associations

between

clones

and

expression

are

observed

in

CEU

CHB

and

JPT

but

not

in

YRI

-LRB-

B

-RRB-

SNPexpression

and

clone-expression

association

for

chr

Both

SNPs

and

clones

are

significantly

associated

with

expression

of

in

CEU

CHB

and

JPT

but

not

in

YRI

In

each

plot

dotted

lines

show

the

permutation

significance

threshold

For

clone-expression

associations

all

clones

in

the

window

are

shown

however

the

significance

threshold

was

determined

by

permuting

data

only

from

those

clones

in

CNVs

where

the

CNV

was

present

in

at

least

two

HapMap

individuals

All

coordinates

shown

are

from

Build

of

the

human

genome

Inset

panels

show

the

relation

between

mRNA

levels

and

SNP

genotypes

or

clone

ratios

for

the

most

significant

clone

or

SNP

in

that

population

which

may

differ

across

populations

SCIENCE

FEBRUARY

VOL

Downloaded

from

on

May

REPORTS

SNP

associations

are

replicated

across

populations

Replication

of

association

signals

is

the

sine

qua

non

of

association

studies

and

the

fact

that

we

observe

this

even

between

diverse

populations

and

with

small

sample

sizes

highlights

the

relevance

and

robustness

of

the

associations

we

detect

Gene

expression

is

the

basis

for

many

crucial

functions

in

the

cell

so

the

relative

contribution

of

these

two

types

of

variants

is

an

indication

of

the

nature

of

the

mutational

and

natural

selection

processes

that

contribute

to

phenotypic

diversity

and

divergence

It

is

therefore

essential

that

we

interrogate

both

SNPs

and

CNVs

-LRB-

of

all

types

-RRB-

to

perform

a

comprehensive

exploration

of

genetic

effects

on

phenotypic

variation

and

disease

It

is

possible

that

if

a

larger

number

of

SNPs

were

analyzed

or

a

higher

resolution

of

CNVs

was

available

we

would

observe

more

overlap

between

the

effects

attributed

to

CNVs

and

SNPs

However

the

difficulty

of

designing

robust

SNP

genotyping

assays

in

structurally

dynamic

regions

of

the

genome

-LRB-

-RRB-

suggests

that

even

with

more

comprehensive

interrogation

of

SNPs

and

CNVs

the

overlap

may

not

be

high

enough

for

one

type

of

variation

to

be

sufficient

for

exploring

the

genetic

causes

of

disease

We

have

also

demonstrated

that

it

is

not

necessary

to

perform

such

studies

with

CNV

calls

or

CNV

genotypes

but

it

is

possible

to

use

filtered

CGH

ratios

or

any

other

type

of

high-quality

quantitative

signal

that

reflects

underlying

CNV

It

has

also

become

apparent

that

there

are

many

more

structural

variants

that

contribute

to

phenotypic

variation

than

our

stringent

criteria

for

what

is

a

CNV

reveal

and

that

higherresolution

methods

are

necessary

to

elucidate

their

structure

and

function

Last

but

not

least

is

the

fact

that

we

have

only

considered

simple

models

of

association

in

small

samples

so

it

is

very

likely

that

if

we

apply

more

complex

and

realistic

models

-LRB-

e.g.

epistatic

interactions

-RRB-

and/or

larger

population

samples

a

larger

number

of

effects

would

be

revealed

The

results

presented

here

reinforce

the

idea

that

the

complexity

of

functionally

relevant

genetic

variation

ranges

from

single

nucleotides

to

megabases

and

the

full

range

of

the

effects

of

all

of

these

variants

will

be

best

captured

and

interpreted

by

complete

knowledge

of

the

sequence

of

many

human

genomes

Until

this

is

possible

we

need

to

survey

all

known

types

of

genetic

variation

to

maximize

our

understanding

of

human

evolution

diversity

and

disease

References

and

Notes

B.

E.

Stranger

et

al.

PLoS

Genet

-LRB-

-RRB-

V.

G.

Cheung

et

al.

Nature

-LRB-

-RRB-

S.

Doss

E.

E.

Schadt

T.

A.

Drake

A.

J.

Lusis

Genome

Res

-LRB-

-RRB-

R.

B.

Brem

L.

Kruglyak

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

J.

D.

Storey

J.

M.

Akey

L.

Kruglyak

PLoS

Biol

-LRB-

-RRB-

M.

F.

Oleksiak

J.

L.

Roach

D.

L.

Crawford

Nat

Genet

-LRB-

-RRB-

S.

A.

Monks

et

al.

Am

J.

Hum

Genet

-LRB-

-RRB-

E.

E.

Schadt

et

al.

Nature

-LRB-

-RRB-

E.

J.

Chesler

et

al.

Nat

Genet

-LRB-

-RRB-

L.

Bystrykh

et

al.

Nat

Genet

-LRB-

-RRB-

E.

T.

Dermitzakis

B.

E.

Stranger

Mamm

Genome

-LRB-

-RRB-

T.

Pastinen

T.

J.

Hudson

Science

-LRB-

-RRB-

International

HapMap

Consortium

Nature

-LRB-

-RRB-

L.

Feuk

C.

R.

Marshall

R.

F.

Wintle

S.

W.

Scherer

Hum

Mol

Genet

-LRB-

suppl

-RRB-

-LRB-

-RRB-

A.

J.

Iafrate

et

al.

Nat

Genet

-LRB-

-RRB-

J.

Sebat

et

al.

Science

-LRB-

-RRB-

E.

Tuzun

et

al.

Nat

Genet

-LRB-

-RRB-

S.

A.

McCarroll

et

al.

Nat

Genet

-LRB-

-RRB-

D.

F.

Conrad

T.

D.

Andrews

N.

P.

Carter

M.

E.

Hurles

J.

K.

Pritchard

Nat

Genet

-LRB-

-RRB-

P.

Stankiewicz

in

Genomic

Disorders

The

Genomic

Basis

of

Disease

J.

R.

Lupski

P.

Stankiewicz

Eds

-LRB-

Humana

Press

Totowa

NJ

-RRB-

pp.

D.

A.

Kleinjan

V.

van

Heyningen

Am

J.

Hum

Genet

-LRB-

-RRB-

M.

J.

Somerville

et

al.

N.

Engl

J.

Med

-LRB-

-RRB-

J.

A.

Lee

et

al.

Ann

Neurol

-LRB-

-RRB-

D.

P.

Locke

et

al.

Am

J.

Hum

Genet

-LRB-

-RRB-

D.

A.

Hinds

A.

P.

Kloek

M.

Jen

X.

Chen

K.

A.

Frazer

Nat

Genet

-LRB-

-RRB-

R.

Redon

et

al.

Nature

-LRB-

-RRB-

GENEVAR

GENe

Expression

VARiation

uk/genevar

International

HapMap

Project

release

The

Copy

Number

Variation

-LRB-

CNV

-RRB-

Project

Data

Index

R.

W.

Doerge

G.

A.

Churchill

Genetics

-LRB-

-RRB-

G.

Merla

et

al.

Am

J.

Hum

Genet

-LRB-

-RRB-

We

thank

A.

Clark

and

J.

Pritchard

for

comments

on

earlier

versions

of

the

manuscript

M.

Smith

for

assistance

with

software

development

and

M.

Gibbs

J.

Orwick

and

C.

Gerringer

for

technical

support

Funding

was

provided

by

the

Wellcome

Trust

to

E.T.D.

M.E.H.

P.D.

C.T.S.

and

N.C.

NIH

to

E.T.D.

and

S.T.

Cancer

Research

U.K.

to

S.T.

and

N.T.

the

Leukemia

and

Lymphoma

Society

and

the

Brigham

and

Women

's

Hospital

Department

of

Pathology

to

C.L.

and

the

U.K.

Medical

Research

Council

-LRB-

MRC

-RRB-

to

M.D.

S.T.

is

a

Royal

Society

Wolfson

Research

Merit

Award

holder

S.W.S.

is

supported

by

grants

from

Genome

Canada/Ontario

Genomics

Institute

and

is

a

Scholar

of

the

Canadian

Institutes

of

Health

Research

and

the

Howard

Hughes

Medical

Institute

Supporting

Online

Material

Materials

and

Methods

Figs

to

Tables

to

References

and

Notes

October

accepted

January

science

Evidence

That

Focal

Adhesion

Complexes

Power

Bacterial

Gliding

Motility

T

m

Mignot

Joshua

W.

Shaevitz

Patricia

L.

Hartzell

David

R.

The

bacterium

Myxococcus

xanthus

has

two

motility

systems

S

motility

which

is

powered

by

type

IV

pilus

retraction

and

A

motility

which

is

powered

by

unknown

mechanism

-LRB-

s

-RRB-

We

found

that

A

motility

involved

transient

adhesion

complexes

that

remained

at

fixed

positions

relative

to

the

substratum

as

cells

moved

forward

Complexes

assembled

at

leading

cell

poles

and

dispersed

at

the

rear

of

the

cells

When

cells

reversed

direction

the

A-motility

clusters

relocalized

to

the

new

leading

poles

together

with

S-motility

proteins

The

Frz

chemosensory

system

coordinated

the

two

motility

systems

The

dynamics

of

protein

cluster

localization

suggest

that

intracellular

motors

and

force

transmission

by

dynamic

focal

adhesions

can

power

bacterial

motility

uring

the

exhibition

of

gliding

motility

bacteria

move

across

solid

surfaces

without

the

use

of

flagella

-LRB-

-RRB-

Gliding

motility

is

important

for

biofilm

formation

and

bacterial

virulence

Motility

in

Myxococcus

xanthus

a

Gram-negative

rod-shaped

bacterium

relies

on

associated

with

pili

or

other

obvious

structures

and

is

not

well

understood

To

investigate

the

A-motility

system

we

studied

AglZ

a

protein

that

is

essential

for

A

motility

but

dispensable

for

S

motility

-LRB-

fig

A

and

B

-RRB-

-LRB-

-RRB-

AglZ

is

similar

to

FrzS

an

S-motility

protein

that

oscillates

from

one

cell

pole

to

the

other

when

cells

reverse

direction

-LRB-

-RRB-

-LRB-

fig

-RRB-

To

track

the

localization

of

AglZ

in

moving

cells

we

constructed

an

M.

xanthus

strain

containing

a

chimeric

aglZ-yfp

gene

in

place

of

the

endogenous

aglZ

gene

-LRB-

fig

-RRB-

This

chimeric

gene

encodes

an

AglZ

yellow

fluorescent

protein

-LRB-

YFP

-RRB-

fusion

protein

that

was

stable

and

functional

-LRB-

fig

B

and

C

-RRB-

We

followed

AglZ-YFP

localization

using

time-lapse

video

microscopy

In

fully

motile

cells

AglZ-YFP

was

localized

in

Department

of

Molecular

and

Cell

Biology

University

of

California

Berkeley

CA

USA

of

Integrative

Biology

University

of

California

Berkeley

CA

USA

of

Microbiology

Molecular

Biology

and

Biochemistry

University

of

Idaho

Moscow

ID

USA

D

two

separate

but

coordinated

motility

engines

S

motility

is

powered

by

type

IV

pili

that

are

assembled

at

the

leading

cell

pole

movement

is

produced

as

the

pili

bind

to

surface

exopolysaccharides

and

are

retracted

thereby

pulling

the

cell

forward

-LRB-

-RRB-

A

motility

on

the

other

hand

is

not

SCIENCE

VOL

To

whom

correspondence

should

be

addressed

E-mail

tmignot@berkeley.edu

-LRB-

T.M.

-RRB-

zusman@berkeley.edu

-LRB-

D.R.Z.

-RRB-

FEBRUARY

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O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O B O O O O O O B O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O B B B O O O O O O O O B O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O B B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

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cnv
expression
snps
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