www.nature.com/nature Vol 438 | Issue no. 7068 | 1 December 2005 Let data speak to data Web tools now allow data sharing and informal debate to take place alongside published papers . But to take full advantage , scientists must embrace a culture of sharing and rethink their vision of databases . pload and share your raw data , and have a high impact factor for your blog -- or perish ? That day has not yet come , but web technologies , from personal publishing tools such as blogs to electronic laboratory notebooks , are pushing the character of the web from that of a large library towards providing a user-driven collaborative workspace -LRB- see page 547 -RRB- . This will in turn expose many fields of research to changes that are already sweeping disciplines such as bioinformatics and high-energy physics . A decade ago , for example , astronomy was still largely about groups keeping observational data proprietary and publishing individual results . Now it is organized around large data sets , with data being shared , coded and made accessible to the whole community . Organized sharing of data within and among smaller and more diverse research communities is more challenging , owing to the plethora of data types and formats . A key technological shift that could change this is a move away from centralized databases to what are known as ` web services ' . These are published interfaces that serve to simplify access to data and software -LRB- for an example of such services in action , see www.ebi.ac.uk/xembl/index.html -RRB- . Until recently the preserve of expert programmers , such interfaces now mean that anyone with even a basic knowledge of programming can automate data processing and analysis . Various sorts of data are increasingly being stored in formats that computers can understand and manipulate , allowing databases to talk to one another . This enables their users quickly to adapt technologies to extract and interpret data from different sources , and to create entirely new data products and services . In biodiversity research , for example , rather than creating centralized monolithic databases , scientists could tap into existing databases wherever the data are held , weaving together all the relevant data on a species , from its taxonomy and genetic sequence to its geographical distribution . Such decentralization also helps to solve the problem that databases are often the fruits of individual or U lab research projects that are vulnerable to the vagaries of funding , and to people and labs moving on to pastures new . Although discipline-specific databases have an indisputable role , science also needs to capitalize on large common repositories for data , whose preservation is guaranteed , and where the data can easily be used by anyone . If that sounds utopian , consider OurMedia , a service created by the Internet Archive and the Creative Commons , which allows anyone to store and share permanently and free of charge any digital work -- even their videos and holiday photos . And last month Google launched Google Base , which also allows anyone to upload anything to its massive platform . Such services will also require `` By making data available new thinking on open data . under a Creative Commons Web services are dependent on licence , scientists can computers being able to freely access data in real time . stipulate rights and credits Although GenBank and many for the reuse of data . '' large databases allow unhindered access to their data , many research organizations still cling to obsolete manual data permission policies , which prevent their data being used by web services . Scientists may be justified in retaining privileged access to data that they have invested heavily in collecting , pending publication -- but there are also huge amounts of data that do not need to be kept behind walls . And few organizations seem to be aware that by making their data available under a Creative Commons licence -LRB- see http://creativecommons.org/license -RRB- , they can stipulate both rights and credits for the reuse of data , while allowing its uninterrupted access by machines . As web services empower researchers , the biggest obstacle to fulfilling such visions will be cultural . Scientific competitiveness will always be with us . But developing meaningful credit for those who share their data is essential , to encourage the diversity of means by which researchers can now contribute to the global academy . Life at the edge Successes in structural studies of membrane proteins deserve to be celebrated . S ealed membrane systems are a defining feature of cellular life . Membranes provide a barrier between the cell and its external environment and , in many organisms , divide the interior of the cell into functionally distinct compartments . The barrier , comprising lipids that are impenetrable to electrically polarized molecules , has proteins inserted within it that allow the selective transport of ions and molecules . These proteins enable cells to ingest nutrients , excrete metabolic waste , sample the environment for the sake of the immune system , and store energy by means of ion electrochemical gradients . They mediate molecular signalling across the barrier . And they are the very devil to study . Genome sequencing projects have highlighted the central role of membrane-linked processes in cells . They have revealed that membrane proteins represent about a third of the gene products in most organisms . Unfortunately , our molecular knowledge of these membrane proteins lags far behind that of proteins found in the cell cytoplasm and in external environments . This is primarily due to the difficulty in obtaining high-resolution structural information on 531 2005 Nature Publishing Group

O O O O O O O O O O O O B O O B 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 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 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 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 B 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 B O O O O O O O B 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 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 B 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 B 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 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 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 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 B 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 O B 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 B O O B O O O O O O B O O O O O O B O O O B 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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


The

Transcriptional

Landscape

of

the

Mammalian

Genome

The

FANTOM

Consortium

et

al.

Science

-LRB-

-RRB-

DOI

science

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weekly

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American

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title

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AAAS

Downloaded

from

on

May

CORRECTED

MARCH

SEE

LAST

PAGE

REPORTS

only

LKS

stations

in

NH

-RRB-

are

fully

consistent

with

this

assumption

particularly

for

the

tropical

stations

In

the

extratropics

there

are

only

four

daytime-only

stations

so

the

MSU

test

is

less

meaningful

but

the

two

independent

estimates

do

agree

within

per

decade

To

illustrate

the

importance

of

the

heating

bias

we

have

computed

its

impact

dsol

on

the

trends

at

LKS

stations

The

LKS

f

factors

unhomogenized

trends

and

trends

adjusted

only

for

solar

heating

are

given

for

the

middle

troposphere

and

lower

stratosphere

in

Table

In

the

stratosphere

our

dsol

is

similar

to

the

total

adjustments

by

LKS

and

others

with

trends

moving

closer

to

those

from

MSU

-LRB-

-RRB-

At

the

tropical

tropopause

-LRB-

of

relevance

to

stratospheric

water

vapor

-RRB-

dsol

is

somewhat

smaller

than

In

the

troposphere

however

dsol

is

much

larger

than

previous

adjustments

Indeed

the

tropical

trend

with

this

adjustment

-LRB-

per

decade

over

to

-RRB-

would

be

consistent

with

model

simulations

driven

by

observed

surface

warming

which

was

not

true

previously

-LRB-

-RRB-

One

independent

indication

that

the

solar-adjusted

trends

should

be

more

accurate

is

their

consistency

across

latitude

belts

for

the

period

to

the

spread

of

values

fell

by

in

the

lower

stratosphere

and

in

the

troposphere

Though

this

is

encouraging

our

confidence

in

these

nighttime

trends

is

still

limited

given

that

other

radiosonde

errors

have

not

been

addressed

SH

trends

from

to

seem

unrealistically

high

in

the

troposphere

especially

with

the

dsol

adjustment

although

this

belt

has

by

far

the

worst

sampling

Previous

homogenization

efforts

typically

produced

small

changes

to

mean

tropospheric

trends

which

could

mean

that

other

error

trends

cancel

out

dsol

in

the

troposphere

In

our

judgment

however

such

fortuitous

cancellation

of

independent

errors

is

unlikely

compared

to

the

possibility

that

most

solar

artifacts

were

previously

either

missed

or

their

removal

negated

by

other

inaccurate

adjustments

To

be

detected

easily

a

shift

must

be

large

and

abrupt

but

dsol

was

spread

out

over

so

many

stations

-LRB-

of

stations

during

to

and

during

to

experienced

DT

trends

significant

at

level

-RRB-

at

such

modest

levels

and

of

sufficient

frequency

at

many

stations

that

many

may

have

been

undetectable

Most

important

jumps

in

the

difference

between

daytime

and

nighttime

monthly

means

would

be

detectable

at

only

a

few

tropical

stations

because

most

lack

sufficient

nighttime

data

In

any

case

we

conclude

that

carefully

extracted

diurnal

temperature

variations

can

be

a

valuable

troubleshooting

diagnostic

for

climate

records

and

that

the

uncertainty

in

late

century

radiosonde

trends

is

large

enough

to

accommodate

the

reported

surface

warming

References

and

Notes

B.

D.

Santer

et

al.

Science

-LRB-

-RRB-

published

online

August

-LRB-

science

-RRB-

J.

K.

Angell

J.

Clim

-LRB-

-RRB-

J.

R.

Lanzante

S.

A.

Klein

D.

J.

Seidel

J.

Clim

-LRB-

-RRB-

D.

E.

Parker

et

al.

Geophys

Res

Lett

-LRB-

-RRB-

P.

W.

Thorne

et

al.

J.

Geophys

Res.

in

press

D.

H.

Douglass

B.

D.

Pearson

S.

F.

Singer

P.

C.

Knappenberger

P.

J.

Michaels

Geophys

Res

Lett

-LRB-

-RRB-

D.

J.

Gaffen

et

al.

Science

-LRB-

-RRB-

D.

E.

Parker

D.

I.

Cox

Int

J.

Climatol

-LRB-

-RRB-

M.

Free

D.

J.

Seidel

J.

Geophys

Res

-LRB-

-RRB-

J.

K.

Luers

R.

E.

Eskridge

J.

Appl

Meteorol

-LRB-

-RRB-

I.

Durre

T.

C.

Peterson

R.

S.

Vose

J.

Clim

-LRB-

-RRB-

L.

Haimberger

Homogenization

of

radiosonde

temperature

time

series

using

analysis

feedback

information

Tech

Rep.

European

Center

for

Medium

Range

Weather

Forecasting

-LRB-

-RRB-

Project

Report

Series

D.

J.

Seidel

et

al.

J.

Clim

-LRB-

-RRB-

P.

R.

Krishnaiah

B.

Q.

Miao

Handbook

of

Statistics

P.

R.

Krishnaiah

C.

R.

Rao

Eds

-LRB-

Elsevier

New

York

-RRB-

vol

M.

Free

et

al.

Bull

Am

Meteorol

Soc

-LRB-

-RRB-

W.

J.

Randel

F.

Wu

in

preparation

D.

J.

Seidel

M.

Free

J.

Wang

J.

Geophys

Res

-LRB-

-RRB-

A.

Dai

K.

E.

Trenberth

T.

R.

Karl

J.

Clim

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Tides

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et

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Science

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J.

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R.

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Clim

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et

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E.

Eskridge

et

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Am

Meteorol

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Riehl

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Meteorology

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McGraw

Hill

New

York

-RRB-

S.

C.

Sherwood

Geophys

Res

Lett

-LRB-

-RRB-

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R.

W.

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W.

B.

Norris

W.

D.

Braswell

D.

E.

Parker

J.

Atmos

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Technol

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Data

files

and

further

information

on

methods

uncertainty

and

interpretation

of

our

results

are

available

as

supporting

material

on

Science

Online

S.C.S.

thanks

J.

Risbey

and

K.

Braganza

for

useful

discussions

This

work

was

supported

by

the

National

Oceanic

and

Atmospheric

Administration

Climate

and

Global

Change

Program

award

and

by

NSF

Supporting

Online

Material

Methods

SOM

Text

Data

files

References

and

Notes

June

accepted

July

Published

online

August

science

Include

this

information

when

citing

this

paper

The

Transcriptional

Landscape

of

the

Mammalian

Genome

The

FANTOM

Consortium

and

RIKEN

Genome

Exploration

Research

Group

and

Genome

Science

Group

-LRB-

Genome

Network

Project

Core

Group

-RRB-

This

study

describes

comprehensive

polling

of

transcription

start

and

termination

sites

and

analysis

of

previously

unidentified

full-length

complementary

DNAs

derived

from

the

mouse

genome

We

identify

the

and

boundaries

of

transcripts

with

extensive

variation

in

transcripts

arising

from

alternative

promoter

usage

splicing

and

polyadenylation

There

are

new

mouse

protein-coding

transcripts

including

encoding

previously

unidentified

proteins

Genomic

mapping

of

the

transcriptome

reveals

transcriptional

forests

with

overlapping

transcription

on

both

strands

separated

by

deserts

in

which

few

transcripts

are

observed

The

data

provide

a

comprehensive

platform

for

the

comparative

analysis

of

mammalian

transcriptional

regulation

in

differentiation

and

development

The

production

of

RNA

from

genomic

DNA

is

directed

by

sequences

that

determine

the

start

and

end

of

transcripts

and

splicing

into

mature

RNAs

We

refer

to

the

pattern

of

transcription

control

signals

and

the

transcripts

they

generate

as

the

transcriptional

landscape

To

describe

the

transcriptional

landscape

of

the

mammalian

genome

we

combined

fulllength

cDNA

isolation

-LRB-

-RRB-

and

and

end

sequencing

of

cloned

cDNAs

with

new

capanalysis

gene

expression

-LRB-

CAGE

-RRB-

and

gene

identification

signature

-LRB-

GIS

-RRB-

and

gene

signature

cloning

-LRB-

GSC

-RRB-

ditag

technologies

for

the

identification

of

RNA

and

mRNA

sequences

corresponding

to

transcription

initiSCIENCE

VOL

ation

and

termination

sites

-LRB-

-RRB-

A

detailed

description

of

the

data

sets

generated

mapping

strategies

and

depth

of

coverage

of

the

mouse

transcriptome

is

provided

in

supporting

online

material

-LRB-

SOM

-RRB-

text

-LRB-

Tables

and

-RRB-

We

have

identified

paired

initiation

and

termination

sites

the

boundaries

of

independent

transcripts

for

independent

transcripts

in

the

transcriptome

-LRB-

Table

-RRB-

In

total

we

found

start

sites

for

each

end

and

ends

for

each

end

-LRB-

table

-RRB-

Based

on

these

data

the

number

of

transcripts

is

at

least

one

order

of

magnitude

larger

than

the

estimated

Bgenes

-LSB-

in

the

mouse

genome

-LRB-

-RRB-

-LRB-

SOM

text

-RRB-

and

the

SEPTEMBER

Downloaded

from

on

May

REPORTS

large

majority

of

transcriptional

units

have

alternative

promoters

and

polyadenylation

sites

The

use

of

genome

tiling

arrays

-LRB-

-RRB-

in

humans

has

also

implied

that

the

number

of

transcripts

encoded

by

the

genome

is

at

least

times

as

great

as

the

number

of

Bgenes

-LSB-

To

extend

the

mouse

data

two

CAGE

libraries

one

constructed

with

random

primers

and

the

other

with

oligo-dT

primers

were

combined

to

produce

CAGE

tags

Mapping

of

these

tags

to

the

human

genome

identified

the

likely

promoters

and

transcriptional

starting

site

-LRB-

TSS

-RRB-

of

many

of

the

gene

models

identified

by

tiling

array

also

called

transfrags

-LRB-

-RRB-

and

clearly

indicates

that

the

same

level

of

transcriptional

diversity

occurs

in

humans

as

in

mice

-LRB-

table

-RRB-

The

FANTOM

Consortium

P.

Carninci

T.

Kasukawa

S.

Katayama

J.

Gough

M.

C.

Frith

N.

Maeda

R.

Oyama

T.

Ravasi

B.

Lenhard

C.

Wells

R.

Kodzius

K.

Shimokawa

V.

B.

Bajic

S.

E.

Brenner

S.

Batalov

A.

R.

R.

Forrest

M.

Zavolan

M.

J.

Davis

L.

G.

Wilming

V.

Aidinis

J.

E.

Allen

A.

Ambesi-Impiombato

R.

Apweiler

R.

N.

Aturaliya

T.

L.

Bailey

M.

Bansal

L.

Baxter

K.

W.

Beisel

T.

Bersano

H.

Bono

A.

M.

Chalk

K.

P.

Chiu

V.

Choudhary

A.

Christoffels

D.

R.

Clutterbuck

M.

L.

Crowe

E.

Dalla

B.

P.

Dalrymple

B.

de

Bono

G.

Della

Gatta

D.

di

Bernardo

T.

Down

P.

Engstrom

M.

Fagiolini

G.

Faulkner

C.

F.

Fletcher

T.

Fukushima

M.

Furuno

S.

Futaki

M.

Gariboldi

P.

Georgii-Hemming

T.

R.

Gingeras

T.

Gojobori

R.

E.

Green

S.

Gustincich

M.

Harbers

Y.

Hayashi

T.

K.

Hensch

N.

Hirokawa

D.

Hill

L.

Huminiecki

M.

Iacono

K.

Ikeo

A.

Iwama

T.

Ishikawa

M.

Jakt

A.

Kanapin

M.

Katoh

Y.

Kawasawa

J.

Kelso

H.

Kitamura

H.

Kitano

G.

Kollias

S.

P.

T.

Krishnan

A.

Kruger

S.

K.

Kummerfeld

I.

V.

Kurochkin

L.

F.

Lareau

D.

Lazarevic

L.

Lipovich

J.

Liu

S.

Liuni

S.

McWilliam

M.

Madan

Babu

M.

Madera

L.

Marchionni

H.

Matsuda

S.

Matsuzawa

H.

Miki

F.

Mignone

S.

Miyake

K.

Morris

S.

Mottagui-Tabar

N.

Mulder

N.

Nakano

H.

Nakauchi

P.

Ng

R.

Nilsson

S.

Nishiguchi

S.

Nishikawa

F.

Nori

O.

Ohara

Y.

Okazaki

V.

Orlando

K.

C.

Pang

W.

J.

Pavan

G.

Pavesi

G.

Pesole

N.

Petrovsky

S.

Piazza

J.

Reed

J.

F.

Reid

B.

Z.

Ring

M.

Ringwald

B.

Rost

Y.

Ruan

S.

L.

Salzberg

A.

Sandelin

C.

Schneider

C.

Schonbach

K.

Sekiguchi

C.

A.

M.

Semple

S.

Seno

L.

Sessa

Y.

Sheng

Y.

Shibata

H.

Shimada

K.

Shimada

D.

Silva

B.

Sinclair

S.

Sperling

E.

Stupka

K.

Sugiura

R.

Sultana

Y.

Takenaka

K.

Taki

K.

Tammoja

S.

L.

Tan

S.

Tang

M.

S.

Taylor

J.

Tegner

S.

A.

Teichmann

H.

R.

Ueda

E.

van

Nimwegen

R.

Verardo

C.

L.

Wei

K.

Yagi

H.

Yamanishi

E.

Zabarovsky

S.

Zhu

A.

Zimmer

W.

Hide

C.

Bult

S.

M.

Grimmond

R.

D.

Teasdale

E.

T.

Liu

V.

Brusic

J.

Quackenbush

C.

Wahlestedt

J.

S.

Mattick

D.

A.

Hume

RIKEN

Genome

Exploration

Research

Group

and

Genome

Science

Group

-LRB-

Genome

Network

Project

Core

Group

-RRB-

C.

Kai

D.

Sasaki

Y.

Tomaru

S.

Fukuda

M.

KanamoriKatayama

M.

Suzuki

J.

Aoki

T.

Arakawa

J.

Iida

K.

Imamura

M.

Itoh

T.

Kato

H.

Kawaji

N.

Kawagashira

T.

Kawashima

M.

Kojima

S.

Kondo

H.

Konno

K.

Nakano

N.

Ninomiya

T.

Nishio

M.

Okada

C.

Plessy

K.

Shibata

T.

Shiraki

S.

Suzuki

M.

Tagami

K.

Waki

A.

Watahiki

Y.

Okamura-Oho

H.

Suzuki

J.

Kawai

General

Organizer

Y.

Hayashizaki

Affiliations

can

be

found

on

Science

Online

-LRB-

available

at

-RRB-

These

authors

are

core

authorship

members

To

whom

correspondence

should

be

addressed

E-mail

yosihide@gsc.riken.jp

The

mapping

of

ends

of

transcripts

can

be

used

to

identify

the

genomic

span

of

the

primary

transcript

Figure

shows

length

distributions

of

the

predicted

genomic

regions

spanned

by

mouse

cDNAs

showing

a

bimodal

distribution

and

compares

them

with

one

peak

for

unspliced

and

another

for

spliced

RNAs

At

the

upper

end

of

the

distribution

are

candidate

mega

transcripts

-LRB-

transcripts

originating

from

genomic

regions

in

the

order

of

millions

of

base

pairs

-RRB-

For

example

we

located

six

pairs

of

genome

signature

cloning

-LRB-

GSC

-RRB-

ditags

to

RIKEN

clone

ID

and

corresponding

RIKEN

expressed

sequence

tags

-LRB-

ESTs

-RRB-

This

clone

encodes

for

a

previously

unidentified

large

transcript

that

is

similar

to

a

protein

tyrosine

phosphatase

receptor

type

D

-LRB-

accession

no

-RRB-

the

genomic

structure

of

which

has

not

been

previously

reported

-LRB-

-RRB-

The

predicted

mRNA

is

base

pairs

in

length

but

spans

a

genomic

region

of

megabases

-LRB-

Mb

-RRB-

We

previously

coined

the

term

transcriptional

units

-LRB-

TUs

-RRB-

which

groups

mRNAs

that

share

at

least

one

nucleotide

and

have

the

same

genomic

location

and

orientation

-LRB-

-RRB-

However

TU

fusions

can

join

unrelated

and

differently

annotated

transcripts

-LRB-

SOM

text

-RRB-

Therefore

we

define

a

transcriptional

framework

-LRB-

TK

-RRB-

as

grouping

transcripts

that

share

common

expressed

regions

as

well

Fig.

Genome-transcriptome

relation

-LRB-

A

-RRB-

Genome

span

covered

by

full-length

cDNA

and

GIS/GSC

ditags

shows

similar

distribution

with

two

main

peaks

Ditags

mapping

follows

the

same

distribution

profile

at

various

mapping

thresholds

with

a

minimum

around

to

Mb

Mapping

events

above

this

genomic

span

are

nonspecific

Count

displays

the

number

of

events

in

the

size

interval

-LRB-

B

-RRB-

Asymptotic

unit

collapse

Due

to

extensive

overlap

of

the

genome

transcripts

overlap

to

the

extent

that

they

collapse

to

a

few

GFs

Simulating

addition

of

ditags

shows

the

collapsing

rate

of

the

known

annotated

genes

into

elements

only

Primary

transcripts

only

GFs

identified

by

GSC

ditags

only

Ensembl

only

GFs

produced

by

the

Ensembl-only

annotated

transcripts

total

the

total

number

of

GFs

SEPTEMBER

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May

REPORTS

as

splicing

events

TSS

or

termination

events

-LRB-

SOM

text

-RRB-

TKs

can

be

clustered

together

into

transcript

forests

-LRB-

TFs

-RRB-

genomic

regions

that

are

transcribed

on

either

strand

without

gaps

TFs

encompass

of

the

genome

-LRB-

table

-RRB-

and

are

separated

by

regions

devoid

of

transcription

or

transcription

deserts

With

the

inclusion

of

GSC

tags

in

addition

to

full-length

cDNA

and

paired

EST

sequences

the

estimated

total

number

of

transcript

forests

is

which

will

collapse

further

with

increasing

depth

of

coverage

-LRB-

Fig.

-RRB-

The

approach

used

to

isolate

full-length

cDNAs

based

on

library

subtraction

and

previously

unidentified

end

selection

before

full-insert

sequencing

was

weighted

toward

identification

of

representative

transcripts

Nevertheless

different

splicing

variants

were

identified

such

that

of

TUs

contain

multiple

splice

variants

-LRB-

Table

-RRB-

an

increase

from

our

previous

estimate

-LRB-

-RRB-

-LRB-

-RRB-

This

is

still

expected

to

be

an

underestimate

and

new

approaches

will

be

necessary

for

a

full

evaluation

of

exon

diversity

-LRB-

-RRB-

Transcript

diversity

also

arises

through

alternative

termination

Little

is

known

about

sequence

motifs

that

control

alternative

polyadenylation

We

identified

motif

families

with

six

or

more

nucleotides

that

were

statistically

overrepresented

within

base

pairs

of

the

polyadenylation

site

of

individual

transcripts

in

our

data

set

These

motifs

represent

candidate

modulators

of

polyadenylation

site

for

eight

unconventional

alternative

polyadenylation

signals

-LRB-

-RRB-

-LRB-

table

-RRB-

In

addition

we

found

a

widespread

motif

family

with

sequence

TTGTTT

which

was

associated

with

both

the

canonical

-LRB-

AAUAAA

and

AUUAAA

-RRB-

and

unconventional

signals

-LRB-

-RRB-

Gene

names

of

transcripts

that

were

protein

coding

were

assigned

according

to

annotation

rules

-LRB-

-RRB-

Their

encoded

protein

sequences

were

combined

with

the

publicly

available

proteins

supported

by

cDNA

sequences

-LRB-

-RRB-

This

generated

a

nonredundant

set

of

proteins

with

experimental

evidence

Eisoform

protein

set

-LRB-

IPS

-RRB-

of

which

are

complete

-LRB-

complete

IPS

-RRB-

By

comparison

the

mammalian

gene

collection

-LRB-

http

mgc.nci.nih.gov

-RRB-

has

cloned

as

of

July

only

transcripts

-LRB-

nonredundant

-RRB-

In

the

data

set

protein

sequences

are

newly

described

Their

splice

variants

were

grouped

together

into

TKs

For

of

these

a

previously

known

sequence

maps

to

the

same

TK

-LRB-

locus

-RRB-

but

clusters

-LRB-

different

proteins

-RRB-

map

to

new

TKs

-LRB-

SOM

text

-RRB-

There

are

a

total

of

protein-coding

TKs

on

the

genome

of

which

have

only

a

single

protein

splice

form

although

of

those

do

have

an

alternative

noncoding

splice

variant

The

SUPERFAMILY

analysis

of

structural

classification

of

protein

database

-LRB-

SCOP

-RRB-

domain

architectures

-LRB-

-RRB-

was

carried

out

for

each

sequence

Of

the

TKs

that

show

variation

in

splicing

showed

variation

in

SCOP

domain

prediction

Of

the

variable

TKs

produce

proteins

with

different

observed

contents

of

InterPro

entries

More

than

two

alternatives

were

observed

in

of

the

InterPro-variable

TKs

Thus

in

the

majority

of

variable

loci

splicing

controls

some

aspect

of

domain

content

or

organization

To

seek

evidence

for

such

an

impact

in

specific

sets

of

regulatory

proteins

we

compared

a

representative

protein

set

Fig.

Transcription

originating

in

UTRs

-LRB-

A

-RRB-

For

each

analyzed

exon

the

fraction

of

tags

mapped

to

equally

large

subsections

of

the

exon

was

calculated

-LRB-

Left

-RRB-

CAGE

tags

mapping

to

the

first

exon

are

prevalently

located

in

the

first

part

of

the

exon

-LRB-

Middle

-RRB-

CAGE

tags

mapping

to

internal

exons

are

uniformly

distributed

-LRB-

Right

-RRB-

Last

exons

show

a

distinct

overrepresentation

of

CAGE

tags

mapping

close

to

the

end

-LRB-

B

-RRB-

Distance

to

the

closest

downstream

gene

for

the

set

of

highly

expressed

TUs

that

have

extreme

tag

density

in

the

of

the

terminal

exons

Transcript

pairs

were

grouped

into

tail-to-head

-LRB-

exon

and

downstream

TU

on

same

strand

-RRB-

or

tail-to-tail

-LRB-

exon

and

downstream

TU

on

opposite

strand

-RRB-

configurations

Remaining

TUs

were

used

as

control

groups

For

TUs

with

strong

transcriptional

activity

the

distance

to

the

next

TU

is

significantly

smaller

than

expected

when

the

gene

pair

is

in

a

tail-to-tail

configuration

-LRB-

P

e

Wilcoxon

test

-RRB-

suggesting

regulatory

mechanisms

based

on

natural

antisense

influencing

the

downstream

gene

-LRB-

-RRB-

Table

Data

set

resources

Total

RIKEN

full-length

cDNAs

Public

-LRB-

non-RIKEN

-RRB-

mRNAs

CAGE

tags

-LRB-

mouse

-RRB-

CAGE

tags

-LRB-

human

-RRB-

GIS

ditags

GSC

ditags

RIKEN

ESTs

RIKEN

ESTs

EST

pairs

of

RIKEN

cDNA

Number

of

libraries

266 265 264

Safely

mapped

SCIENCE

VOL

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from

on

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REPORTS

Fig.

Noncoding

RNA

promoters

are

highly

conserved

-LRB-

A

-RRB-

Human-mouse

conservation

of

coding

and

noncoding

RNAs

compared

with

random

genome

sequence

-LRB-

B

and

C

-RRB-

Promoters

conservation

of

noncoding

and

coding

mRNA

evaluated

-LRB-

B

-RRB-

by

identity

and

-LRB-

C

-RRB-

by

alignment

-LRB-

D

-RRB-

Overlap

of

promoters

of

ncRNAs

-LRB-

E

and

F

-RRB-

Promoters

of

coding

mRNAs

contain

a

larger

fraction

of

low

complexity

and

repeats

than

noncoding

promoters

LINE

long

interspersed

nuclear

elements

LTR

long

terminal

repeats

SINEs

short

interspersed

nuclear

elements

-LRB-

RPS

-RRB-

and

a

variant

protein

set

-LRB-

VPS

-RRB-

of

phosphatases

and

kinases

that

have

been

comprehensively

annotated

-LRB-

-RRB-

by

looking

at

domain

composition

counts

-LRB-

table

-RRB-

These

phosphoregulators

could

be

functionally

modulated

through

alteration

in

their

intracellular

location

Among

the

receptor

tyrosine

phosphatase

loci

we

identified

variant

transcripts

from

loci

with

predicted

changes

to

the

subcellular

localization

and

function

of

the

encoded

peptides

Of

these

we

identified

two

noncatalytic

classes

secreted

-LRB-

-RRB-

and

tethered

-LRB-

-RRB-

Furthermore

we

identified

two

catalytic

classes

that

lack

the

extracellular

domains

catalytic

only

-LRB-

-RRB-

and

tethered

catalytic

-LRB-

-RRB-

Similarly

among

the

receptor

kinase

loci

we

identified

variant

transcripts

from

loci

which

encode

secreted

-LRB-

-RRB-

tethered

-LRB-

-RRB-

catalytic

only

-LRB-

-RRB-

or

other

tethered

catalytic

-LRB-

-RRB-

peptides

We

then

analyzed

the

membrane

organization

splicing

variants

class

within

the

full

set

of

TUs

-LRB-

table

-RRB-

which

revealed

TUs

that

exhibit

alternative

initiation

splicing

and

termination

likely

to

yield

variant

isoforms

of

membrane

proteins

that

differ

in

their

cellular

location

Of

the

cDNAs

lack

any

protein-coding

sequence

-LRB-

CDS

-RRB-

and

are

annotated

as

non

protein

coding

RNA

-LRB-

ncRNA

-RRB-

-LRB-

-RRB-

-LRB-

table

-RRB-

Many

putative

ncRNAs

were

singletons

in

the

full-length

cDNA

set

Among

the

cDNA

set

there

was

additional

support

from

ESTs

CAGE

tags

or

other

cDNA

clones

overlapping

both

the

starting

and

termination

sites

for

cDNAs

of

which

only

were

ncRNAs

This

supported

ncRNA

set

includes

many

known

ncRNAs

-LRB-

SOM

text

-RRB-

and

many

are

dynamically

expressed

-LRB-

SOM

text

-RRB-

Following

these

same

criteria

from

cDNAs

previously

annotated

as

truncated

SCIENCE

CDS

were

supported

as

genuine

transcripts

and

are

believed

to

be

ncRNA

variants

of

proteincoding

cDNAs

Many

ncRNAs

appear

to

start

from

initiation

sites

in

untranslated

regions

-LRB-

UTRs

-RRB-

of

protein-coding

loci

-LRB-

-RRB-

The

normalized

distribution

of

CAGE

tags

along

annotated

exons

of

known

transcripts

with

more

than

mapped

tags

each

is

shown

in

Fig.

As

expected

the

highest

tag

density

on

average

occurs

at

the

end

but

there

is

also

a

substantial

increase

of

tags

in

the

last

one-fifth

of

the

UTR

Strong

evidence

of

end

initiation

was

correlated

with

a

short

intergenic

distance

when

in

tail-to-tail

orientation

with

a

neighboring

gene

-LRB-

Fig.

-RRB-

suggesting

a

possible

role

in

an

intergenic

regulatory

interaction

The

function

of

ncRNAs

is

a

matter

of

debate

-LRB-

-RRB-

Some

ncRNAs

are

highly

conserved

even

in

distant

species

out

of

SEPTEMBER

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REPORTS

Table

Transcript

grouping

and

classification

The

extent

of

splice

variation

was

calculated

by

excluding

T-cell

receptor

and

immunoglobulin

genes

from

the

transcripts

The

remaining

transcripts

were

grouped

in

TUs

of

which

-LRB-

-RRB-

consist

of

single-exon

transcripts

-LRB-

-RRB-

contain

a

single

multiexon

transcript

and

the

remaining

TUs

-LRB-

-RRB-

contain

at

least

two

spliced

transcripts

Among

these

TUs

-LRB-

-RRB-

show

no

evidence

of

splice

variation

whereas

-LRB-

-RRB-

contain

multiple

splice

forms

Average

per

TU

cluster

Average

per

TK

cluster

shown

that

the

set

of

nonpolyadenylated

nuclear

RNAs

may

be

very

large

and

that

many

such

transcripts

arise

from

so-called

intergenic

regions

-LRB-

-RRB-

The

future

can

only

reveal

additional

complexity

in

the

mammalian

transcriptome

References

and

Notes

P.

Carninci

et

al.

Genome

Res

-LRB-

-RRB-

T.

Shiraki

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

P.

Ng

et

al.

Nat

Methods

-LRB-

-RRB-

R.

H.

Waterston

et

al.

Nature

-LRB-

-RRB-

D.

Kampa

et

al.

Genome

Res

-LRB-

-RRB-

P.

Bertone

et

al.

Science

-LRB-

-RRB-

J.

Cheng

et

al.

Science

-LRB-

-RRB-

R.

L.

Strausberg

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

Y.

Okazaki

et

al.

Nature

-LRB-

-RRB-

A.

Watahiki

et

al.

Nat

Methods

-LRB-

-RRB-

V.

Bajic

in

preparation

N.

Maeda

R.

Oyama

in

preparation

J.

Gough

in

preparation

A.

R.

Forrest

et

al.

Genome

Res

-LRB-

-RRB-

Materials

and

methods

are

available

as

supporting

material

on

Science

Online

P.

Carninci

et

al.

in

preparation

J.

Wang

et

al.

Nature

p

following

discussion

following

-LRB-

-RRB-

S.

Cawley

et

al.

Cell

-LRB-

-RRB-

T.

Ravasi

D.

A.

Hume

in

Encyclopedia

of

Genetics

Genomics

Proteomics

and

Bioinformatics

L.

B.

Jorde

P.

F.

R.

Little

M.

J.

Dunn

S.

Subramaniam

Eds

-LRB-

John

Wiley

Sons

Chichester

UK

in

press

-RRB-

part

J.

S.

Mattick

I.

V.

Makunin

Hum

Mol

Genet.

in

press

J.

Kelso

et

al.

Genome

Res

-LRB-

-RRB-

R.

A.

Baldock

et

al.

Neuroinformatics

-LRB-

-RRB-

All

sequences

-LRB-

CAGE

and

cDNA

-RRB-

are

available

through

DDBJ

to

other

public

databases

The

cDNA

clones

are

available

Y.

Okazaki

D.

A.

Hume

Genome

Res

-LRB-

-RRB-

E.

Marshall

Science

-LRB-

-RRB-

RIKEN

Genome

Exploration

Research

Group

and

Genome

Science

Group

-LRB-

Genome

Network

Project

Core

Group

-RRB-

and

the

FANTOM

Consortium

Science

-LRB-

-RRB-

We

thank

H.

Atsui

A.

Hasegawa

Y.

Hasegawa

K.

Hayashida

H.

Himei

F.

Hori

T.

Iwashita

S.

Kanagawa

C.

Kawazu

M.

Aoki

K.

Murakami

M.

Murata

H.

Nishida

M.

Nishikawa

K.

Nomura

M.

Ohno

Y.

Onodera

N.

Sakazume

H.

Sato

Y.

Shigemoto

N.

Suzuki

Y.

Takeda

Y.

Tsujimura

K.

Yoshida

for

discussion

encouragement

and

technical

assistance

We

thank

A.

Wada

T.

Ogawa

M.

Muramatsu

and

all

the

members

of

RIKEN

Yokohama

Research

Promotion

Division

for

support

and

encouragement

We

also

thank

the

Laboratory

of

Genome

Exploration

Research

Group

for

secretarial

and

technical

assistance

Yokohama

City

University

for

providing

human

samples

and

computational

resources

of

the

RIKEN

Super

Combined

Cluster

-LRB-

RSCC

-RRB-

This

work

was

mainly

supported

by

Research

Grant

for

the

Genome

Network

Project

from

MEXT

the

RIKEN

Genome

Exploration

Research

Project

from

MEXT

-LRB-

Y.H.

-RRB-

Advanced

and

Innovational

Research

Program

in

Life

Science

-LRB-

Y.H.

-RRB-

National

Project

on

Protein

Structural

and

Functional

Analysis

from

MEXT

-LRB-

Y.H.

-RRB-

Presidential

Research

Grant

for

Intersystem

Collaboration

of

RIKEN

-LRB-

P.C.

and

Y.H.

-RRB-

and

a

grant

from

the

Six

Framework

Program

from

the

European

Commission

-LRB-

P.C.

-RRB-

Supporting

Online

Material

Materials

and

Methods

SOM

Text

Figs

to

Tables

to

References

DDBJ

Accession

Codes

March

accepted

August

science

Total

Total

number

of

transcripts

RIKEN

full-length

Public

-LRB-

non-RIKEN

-RRB-

mRNAs

GFs

Framework

clusters

TUs

With

proteins

Without

proteins

TK

With

proteins

Without

proteins

Splicing

patterns

Table

Determination

of

transcripts

start/end

accuracy

Two

pieces

of

evidence

-LRB-

cDNA

tags

ditags

EST

and

EST

pairs

-RRB-

are

required

when

TSS/terminations

lie

inside

larger

transcripts

and

one

piece

of

evidence

is

required

when

they

extend

or

identify

new

transcripts

Reliable

indicates

that

both

ends

are

associated

with

reliable

tag

clusters

Total

Total

end

pair

sequence

end

pair

cluster

Reliable

overlap

chicken

sequences

of

which

do

not

overlap

known

CDS

and

do

not

overlap

known

mRNAs

on

either

strand

whereas

out

of

have

BLAST-like

alignment

tool

-LRB-

BLAT

-RRB-

alignments

to

the

Fugu

genome

of

which

do

not

overlap

known

CDS

on

either

strand

These

ncRNAs

are

at

least

as

conserved

as

a

reference

set

of

known

ncRNAs

-LRB-

Fig.

-RRB-

contrary

to

a

previous

study

-LRB-

-RRB-

However

ncRNAs

are

slightly

less

conserved

on

average

than

or

UTRs

In

contrast

the

promoter

regions

of

ncRNAs

are

generally

more

conserved

than

the

promoters

of

the

protein-coding

mRNA

not

only

between

human

and

mouse

but

also

down

in

the

evolutionary

scale

to

chicken

-LRB-

Fig.

B

to

F

-RRB-

and

they

contain

binding

sites

for

known

transcription

factors

-LRB-

-RRB-

We

conclude

that

the

large

majority

of

ncRNAs

that

we

analyzed

display

positional

conservation

across

species

In

considering

function

one

might

conclude

that

the

act

of

transcription

from

the

particular

location

is

either

important

or

a

consequence

of

genomic

structure

or

sequence

-LRB-

for

example

enhancers

such

as

that

of

the

globin

locus

can

act

as

promoters

-RRB-

the

transcript

may

function

through

some

kind

of

sequencespecific

interaction

with

the

DNA

sequence

from

which

it

is

derived

or

many

noncoding

RNAs

have

other

targets

but

are

evolving

rapidly

-LRB-

-RRB-

New

databases

have

been

created

for

cDNA

annotation

expression

and

promoter

analysis

-LRB-

and

SOM

text

-RRB-

The

databases

integrate

common

gene

and

tissue

ontologies

like

eVOC

mouse

developmental

ontologies

-LRB-

-RRB-

cross

mapped

to

Edinburgh

Mouse

Atlas

Project

-LRB-

EMAP

-RRB-

ontology

terms

-LRB-

-RRB-

These

eVOC

terms

allow

analysis

standardization

of

RNA

samples

used

for

cDNA

and

CAGE

libraries

in

both

mouse

and

human

and

were

included

into

the

DNA

Database

of

Japan

-LRB-

DDBJ

-RRB-

data

submission

-LRB-

-RRB-

Analysis

of

the

output

of

suggested

that

there

were

many

more

transcripts

still

to

be

discovered

-LRB-

-RRB-

Here

we

have

confirmed

that

the

majority

of

the

mammalian

genome

is

transcribed

commonly

from

both

strands

Such

transcriptional

complexity

implies

caveats

in

interpretation

of

microarray

experiments

-LRB-

-RRB-

and

genome

manipulation

in

mice

because

these

will

commonly

interrupt

or

interrogate

more

than

one

TK

Although

the

current

overview

gives

us

an

indication

of

the

complexity

of

the

mammalian

transcriptional

landscape

and

a

new

set

of

tools

to

begin

to

understand

transcriptional

control

-LRB-

for

example

a

very

large

set

of

promoters

that

can

be

ascribed

to

distinct

classes

-RRB-

-LRB-

-RRB-

we

also

gain

insight

into

the

scale

of

the

task

that

remains

The

ditag

data

indicate

the

existence

of

very

long

transcripts

whose

isolation

and

sequencing

will

require

new

cloning

and

sequencing

strategies

Although

we

have

isolated

and

sequenced

many

putative

ncRNAs

the

collection

only

contains

of

those

already

known

Finally

the

focus

has

been

on

polyadenylated

mRNAs

that

are

processed

and

exported

to

the

cytoplasm

Recently

Gingeras

and

colleagues

-LRB-

-RRB-

have

SCIENCE

VOL

SEPTEMBER

Downloaded

from

on

May

CORRECTIONS

CLARIFICATIONS

ERRATUM

Post

date

March

SCIENCE

ERRATUM

POST

DATE

MARCH

Downloaded

from

on

May

Reports

The

transcriptional

landscape

of

the

mammalian

genome

by

The

FANTOM

Consortium

et

al.

-LRB-

Sept.

p.

-RRB-

On

page

column

lines

should

read

In

the

data

set

protein

sequences

are

newly

described

Their

splice

variants

were

grouped

together

into

TKs

-LRB-

transcriptional

frameworks

-RRB-

For

of

these

a

previously

known

sequence

maps

to

the

same

TK

-LRB-

locus

-RRB-

but

clusters

-LRB-

different

proteins

-RRB-

map

to

new

TKs

-LRB-

see

SOM

text

-RRB-

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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 B 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 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 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 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 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 O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 O 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 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 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 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 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 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 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