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Evolutionarily

conserved

elements

in

vertebrate

insect

worm

and

yeast

genomes

Adam

Siepel

Gill

Bejerano

Jakob

S.

Pedersen

Angie

S.

Hinrichs

Minmei

Hou

Kate

Rosenbloom

Hiram

Clawson

John

Spieth

LaDeana

W.

Hillier

Stephen

Richards

George

M.

Weinstock

Richard

K.

Wilson

Richard

A.

Gibbs

W.

James

Kent

Webb

Miller

and

David

Haussler

Genome

Res

originally

published

online

Jul

Access

the

most

recent

version

at

doi

gr

Supplementary

data

References

Supplemental

Research

Data

This

article

cites

articles

of

which

can

be

accessed

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Cold

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Press

Article

Evolutionarily

conserved

elements

in

vertebrate

insect

worm

and

yeast

genomes

Adam

Siepel

Gill

Bejerano

Jakob

S.

Pedersen

Angie

S.

Hinrichs

Minmei

Hou

Kate

Rosenbloom

Hiram

Clawson

John

Spieth

LaDeana

W.

Hillier

Stephen

Richards

George

M.

Weinstock

Richard

K.

Wilson

Richard

A.

Gibbs

W.

James

Kent

Webb

Miller

and

David

Center

for

Biomolecular

Science

and

Engineering

Hughes

Medical

Institute

University

of

California

Santa

Cruz

Santa

Cruz

California

USA

for

Comparative

Genomics

and

Bioinformatics

Pennsylvania

State

University

University

Park

Pennsylvania

USA

Sequencing

Center

Washington

University

School

of

Medicine

St.

Louis

Missouri

USA

Genome

Sequencing

Center

Department

of

Molecular

and

Human

Genetics

Baylor

College

of

Medicine

Houston

Texas

USA

We

have

conducted

a

comprehensive

search

for

conserved

elements

in

vertebrate

genomes

using

genome-wide

multiple

alignments

of

five

vertebrate

species

-LRB-

human

mouse

rat

chicken

and

Fugu

rubripes

-RRB-

Parallel

searches

have

been

performed

with

multiple

alignments

of

four

insect

species

-LRB-

three

species

of

Drosophila

and

Anopheles

gambiae

-RRB-

two

species

of

Caenorhabditis

and

seven

species

of

Saccharomyces

Conserved

elements

were

identified

with

a

computer

program

called

phastCons

which

is

based

on

a

two-state

phylogenetic

hidden

Markov

model

-LRB-

phylo-HMM

-RRB-

PhastCons

works

by

fitting

a

phylo-HMM

to

the

data

by

maximum

likelihood

subject

to

constraints

designed

to

calibrate

the

model

across

species

groups

and

then

predicting

conserved

elements

based

on

this

model

The

predicted

elements

cover

roughly

of

the

human

genome

-LRB-

depending

on

the

details

of

the

calibration

procedure

-RRB-

and

substantially

higher

fractions

of

the

more

compact

Drosophila

melanogaster

-LRB-

-RRB-

Caenorhabditis

elegans

-LRB-

-RRB-

and

Saccharaomyces

cerevisiae

-LRB-

-RRB-

genomes

From

yeasts

to

vertebrates

in

order

of

increasing

genome

size

and

general

biological

complexity

increasing

fractions

of

conserved

bases

are

found

to

lie

outside

of

the

exons

of

known

protein-coding

genes

In

all

groups

the

most

highly

conserved

elements

-LRB-

HCEs

-RRB-

by

log-odds

score

are

hundreds

or

thousands

of

bases

long

These

elements

share

certain

properties

with

ultraconserved

elements

but

they

tend

to

be

longer

and

less

perfectly

conserved

and

they

overlap

genes

of

somewhat

different

functional

categories

In

vertebrates

HCEs

are

associated

with

the

UTRs

of

regulatory

genes

stable

gene

deserts

and

megabase-sized

regions

rich

in

moderately

conserved

noncoding

sequences

Noncoding

HCEs

also

show

strong

statistical

evidence

of

an

enrichment

for

RNA

secondary

structure

-LSB-

Supplemental

material

is

available

online

at

The

multiple

alignments

predicted

conserved

elements

and

base-by-base

conservation

scores

presented

here

can

be

downloaded

from

edu/acs/conservation

Up-to-date

versions

of

these

data

sets

are

displayed

in

the

Conservation

and

Most

Conserved

tracks

in

the

UCSC

Genome

Browser

-LRB-

-RRB-

The

phastCons

program

is

part

of

a

software

package

called

PHAST

-LRB-

PHylogenetic

Analysis

with

Space/Time

models

-RRB-

which

is

available

by

request

from

acs@soe.ucsc.edu

-RSB-

Despite

tremendous

progress

in

vertebrate

genomics

it

is

still

not

clear

how

much

of

the

human

and

other

vertebrate

genomes

are

directly

functional

in

the

sense

of

encoding

proteins

or

RNAs

helping

to

regulate

transcription

and

translation

enabling

replication

altering

chromatin

structure

or

performing

other

important

cellular

tasks

It

is

even

less

clear

exactly

which

regions

are

functional

More

is

known

about

the

functional

roles

of

sequences

in

the

genomes

of

model

eukaryotes

such

as

Drosophila

melanogaster

Caenorhabditis

elegans

and

Saccharomyces

cerevisiae

but

much

remains

to

be

learned

in

these

genomes

as

well

Especially

in

larger

genomes

where

functional

elements

are

believed

to

account

for

only

a

small

fraction

of

all

bases

effective

Corresponding

author

E-mail

acs@soe.ucsc.edu

fax

-LRB-831-RRB- 459-1809

Article

and

publication

are

at

gr

Article

published

online

before

print

in

July

purpose

methods

for

identifying

sequences

likely

to

be

functional

are

of

critical

importance

One

of

the

best

strategies

known

for

finding

functional

sequences

is

to

look

for

sequences

that

are

conserved

across

species

-LRB-

e.g.

Hardison

et

al.

Loots

et

al.

Boffelli

et

al.

Kellis

et

al.

Margulies

et

al.

Woolfe

et

al.

-RRB-

While

orthologous

sequences

from

related

species

might

appear

conserved

-LRB-

i.e.

unusually

similar

-RRB-

because

of

reduced

mutation

rates

-LRB-

Wolfe

et

al.

Clark

Ellegren

et

al.

Hardison

et

al.

-RRB-

the

primary

reason

for

cross-species

sequence

conservation

is

believed

to

be

negative

-LRB-

purifying

-RRB-

selection

Thus

orthologous

sequences

that

are

significantly

more

similar

than

would

be

expected

if

they

were

evolving

under

some

reasonable

model

of

neutral

evolution

are

likely

to

have

critical

functional

roles

Thanks

to

a

recent

explosion

in

the

number

of

sequenced

genomes

and

to

the

development

of

tools

that

allow

whole

ge

Genome

Research

by

Cold

Spring

Harbor

Laboratory

Press

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from

on

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Published

by

Cold

Spring

Harbor

Laboratory

Press

Evolutionarily

conserved

elements

nomes

to

be

aligned

-LRB-

Brudno

et

al.

Blanchette

et

al.

Bray

and

Pachter

-RRB-

cross-species

conservation

is

emerging

as

a

primary

research

tool

in

genomics

It

is

now

possible

to

conduct

large-scale

searches

for

conserved

sequences

and

to

use

the

results

of

such

searches

to

help

stimulate

new

hypotheses

and

drive

experimentation

-LRB-

Nobrega

et

al.

Frazer

et

al.

Woolfe

et

al.

-RRB-

Comparative

studies

suggest

that

mammalian

genomes

contain

large

numbers

of

functional

elements

that

have

yet

to

be

identified

and

characterized

Analyses

of

human

and

rodent

genomes

-LRB-

Mouse

Genome

Sequencing

Consortium

Chiaromonte

et

al.

Roskin

et

al.

Cooper

et

al.

Rat

Genome

Sequencing

Project

Consortium

-RRB-

indicate

that

about

or

more

of

bases

in

mammalian

genomes

are

under

purifying

selection

while

protein-coding

genes

are

believed

to

account

for

only

about

of

bases

leaving

at

least

that

are

thought

to

be

functional

but

not

to

code

for

proteins

-LRB-

A

high

rate

of

turnover

of

constrained

bases

might

put

this

fraction

considerably

higher

see

Smith

et

al.

-RRB-

This

conserved

noncoding

sequence

the

dark

matter

of

the

genome

has

been

the

subject

of

intense

recent

interest

-LRB-

e.g.

Frazer

et

al.

Shabalina

et

al.

Dermitzakis

et

al.

Bejerano

et

al.

b

Nobrega

et

al.

Woolfe

et

al.

-RRB-

but

remains

for

the

most

part

poorly

understood

While

there

is

less

dark

matter

in

the

genomes

of

insects

worms

and

yeasts

these

genomes

also

contain

many

conserved

sequences

whose

functions

are

not

yet

known

-LRB-

Bergman

et

al.

Kellis

et

al.

Stein

et

al.

-RRB-

Most

groups

have

used

pairwise

alignments

and

simple

percent

identity-based

methods

for

identifying

conserved

elements

For

example

Dermitzakis

et

al.

-LRB-

-RRB-

and

Nobrega

et

al.

-LRB-

-RRB-

have

defined

conserved

elements

as

intervals

of

at

least

bp

with

identity

Tools

such

as

VISTA

-LRB-

Mayor

et

al.

-RRB-

PipMaker

-LRB-

Schwartz

et

al.

-RRB-

and

zPicture

-LRB-

Ovcharenko

et

al.

-RRB-

can

be

used

to

construct

alignments

visualize

annotations

and

percent

identity

levels

and/or

define

conserved

elements

according

to

length

and

identity

thresholds

As

more

genomes

have

become

available

however

it

has

become

essential

to

make

use

of

multiple

-LRB-

n-way

-RRB-

rather

than

just

pairwise

-LRB-

-RRB-

alignments

and

to

consider

the

phylogeny

of

the

species

that

are

represented

A

few

methods

for

detecting

conserved

elements

in

multiple

alignments

have

been

described

some

using

a

phylogeny

-LRB-

e.g.

Stojanovic

et

al.

Boffelli

et

al.

Margulies

et

al.

Chapman

et

al.

Cooper

et

al.

Ovcharenko

et

al.

-RRB-

Of

the

methods

described

so

far

however

only

the

phylogenetic

shadowing

method

-LRB-

Boffelli

et

al.

-RRB-

-LRB-

to

our

knowledge

-RRB-

makes

use

of

the

branch

lengths

of

the

phylogeny

allows

for

multiple

substitutions

per

site

on

single

branches

of

the

tree

and

considers

the

pattern

of

substitution

-LRB-

e.g.

the

tendency

for

transitions

to

occur

more

frequently

than

transversions

-RRB-

In

addition

most

methods

-LRB-

including

phylogenetic

shadowing

-RRB-

use

a

sliding

window

of

fixed

size

which

can

be

a

limitation

For

example

if

the

window

size

is

small

it

may

be

difficult

to

discriminate

effectively

between

conserved

and

nonconserved

regions

but

if

it

is

large

small

conserved

elements

may

be

missed

even

if

highly

conserved

In

this

study

we

describe

a

new

program

called

phastCons

that

is

designed

to

identify

conserved

elements

in

multiply

aligned

sequences

PhastCons

is

based

on

a

phylogenetic

hidden

Markov

model

-LRB-

phylo-HMM

-RRB-

a

type

of

statistical

model

that

considers

both

the

process

by

which

nucleotide

substitutions

occur

at

each

site

in

a

genome

and

how

this

process

changes

from

one

site

to

the

next

-LRB-

Yang

Felsenstein

and

Churchill

Siepel

and

Haussler

-RRB-

Phylo-HMMs

provide

a

principled

mathematically

rigorous

framework

in

which

to

address

problems

of

segmentation

using

comparative

sequence

data

i.e.

problems

in

which

aligned

sequences

are

to

be

parsed

into

segments

of

different

classes

-LRB-

e.g.

conserved

and

nonconserved

or

coding

and

noncoding

-RRB-

For

several

reasons

they

are

attractive

tools

for

the

problem

of

identifying

conserved

elements

they

can

be

used

with

a

general

phylogeny

and

the

best

available

continuous-time

Markov

models

of

nucleotide

substitution

they

do

not

require

a

sliding

window

of

fixed

size

they

allow

nearly

all

parameters

to

be

estimated

from

the

data

by

maximum

likelihood

and

they

permit

all

necessary

computations

to

be

carried

out

efficiently

on

large-scale

data

sets

Using

phastCons

we

have

conducted

comprehensive

searches

for

conserved

elements

in

four

separate

genome-wide

multiple

alignments

consisting

of

five

vertebrate

genomes

four

insect

genomes

two

Caenorhabditis

genomes

and

seven

Saccharomyces

genomes

This

study

contains

a

detailed

discussion

of

our

results

Some

highlights

are

as

follows

Roughly

of

the

human

genome

consists

of

sequences

conserved

in

vertebrates

and/or

other

eutherian

mammals

Much

higher

fractions

of

the

more

compact

D.

melanogaster

-LRB-

-RRB-

C.

elegans

-LRB-

-RRB-

and

S.

cerevisiae

-LRB-

-RRB-

genomes

are

conserved

across

closely

related

species

From

yeasts

to

vertebrates

in

order

of

increasing

genome

size

and

general

biological

complexity

increasing

fractions

of

conserved

bases

are

found

to

lie

outside

of

known

or

suspected

exons

of

protein-coding

genes

apparently

reflecting

the

importance

of

regulatory

and

other

noncoding

sequences

in

complex

eukaryotes

In

all

species

groups

the

most

highly

conserved

elements

-LRB-

HCEs

-RRB-

by

log-odds

score

are

hundreds

or

thousands

of

bases

long

and

show

extreme

levels

of

conservation

but

not

the

perfect

identity

seen

in

ultraconserved

elements

Less

than

half

-LRB-

-RRB-

of

the

vertebrate

HCEs

overlap

exons

of

known

proteincoding

genes

in

contrast

to

insects

worms

and

yeasts

where

nearly

all

-LRB-

-RRB-

HCEs

overlap

such

exons

Some

of

the

most

extreme

conservation

in

vertebrates

is

seen

in

UTRs

particularly

of

genes

that

regulate

other

genes

possibly

reflecting

widespread

post-transcriptional

regulation

This

trend

is

less

pronounced

in

insects

and

was

not

observed

in

worms

-LRB-

Data

for

yeasts

was

not

available

-RRB-

HCEs

in

vertebrate

UTRs

and

to

a

lesser

extent

HCEs

in

UTRs

show

strong

statistical

evidence

of

an

enrichment

for

local

RNA

secondary

structure

consistent

with

the

hypothesis

of

a

role

in

post-transcriptional

regulation

HCEs

in

introns

and

intergenic

regions

also

appear

to

be

enriched

for

local

RNA

secondary

structure

indicating

that

many

may

encode

functional

RNAs

In

vertebrates

intergenic

HCEs

are

strongly

enriched

-LRB-

nearly

fivefold

-RRB-

in

stable

gene

deserts

suggesting

that

many

of

them

may

act

as

distal

cis-regulatory

elements

for

precisely

regulated

genes

-LRB-

Ovcharenko

et

al.

-RRB-

Results

Predicted

conserved

elements

Four

separate

genome-wide

multiple

alignments

were

prepared

for

the

four

species

groups

with

the

human

D.

melanogaster

C.

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Siepel

et

al.

elegans

and

S.

cerevisiae

genomes

serving

as

reference

genomes

-LRB-

see

Methods

and

Table

in

the

Supplemental

material

-RRB-

Using

the

phastCons

program

a

two-state

phylogenetic

hidden

Markov

model

-LRB-

phylo-HMM

-RRB-

-LRB-

see

Fig.

-RRB-

was

then

fitted

separately

to

each

alignment

by

maximum

likelihood

subject

to

certain

constraints

-LRB-

see

Methods

-RRB-

The

estimated

parameters

included

branch

lengths

for

all

branches

of

the

phylogeny

and

a

parameter

representing

the

average

rate

of

substitution

in

conserved

regions

as

a

fraction

of

the

average

rate

in

nonconserved

regions

-LRB-

Fig.

-RRB-

The

tree

topologies

were

assumed

to

be

known

-LRB-

see

Supplemental

material

-RRB-

The

estimated

nonconserved

branch

lengths

for

vertebrates

were

fairly

consistent

with

recent

results

based

on

-LRB-

apparently

-RRB-

neutrally

evolving

DNA

in

mammals

-LRB-

Cooper

et

al.

-RRB-

but

were

not

accurate

representations

of

the

neutral

substitution

process

in

all

respects

In

particular

the

branches

to

the

more

distant

species

-LRB-

chicken

and

Fugu

-RRB-

were

significantly

underestimated

because

the

genomes

of

these

species

are

in

general

alignable

to

the

human

mouse

and

rat

genomes

only

in

regions

that

are

under

at

least

partial

constraint

Similar

effects

were

observed

with

the

insect

worm

and

yeast

phylogenies

Nevertheless

inaccuracies

in

the

estimates

of

some

-LRB-

particularly

longer

-RRB-

nonconserved

branch

lengths

do

not

appear

to

have

strongly

influenced

our

results

-LRB-

see

Supplemental

material

-RRB-

Moreover

our

method

has

certain

advantages

over

more

traditional

methods

for

estimating

neutral

substitution

rates

such

as

by

using

fourfold

degenerate

-LRB-

-RRB-

sites

in

coding

regions

e.g.

it

does

not

depend

on

sites

being

free

from

selection

or

being

suitable

proxies

for

neutrally

evolving

sites

in

general

and

as

an

unsupervised

learning

method

-LRB-

see

Methods

-RRB-

it

is

not

dependent

on

possibly

incomplete

and/or

erroneous

annotations

As

an

approximate

way

of

calibrating

our

methods

across

species

groups

we

constrained

the

model

parameters

such

that

the

coverage

of

known

coding

regions

by

predicted

conserved

elements

-LRB-

i.e.

the

fraction

of

coding

bases

falling

in

conserved

elements

-RRB-

was

equivalent

in

all

groups

We

chose

a

target

coverage

of

-LRB-

-RRB-

as

estimated

from

human/mouse

comparisons

-LRB-

Chiaromonte

et

al.

-RRB-

This

number

was

adjusted

for

alignment

coverage

in

coding

regions

yielding

for

the

worm

data

set

and

for

the

insects

and

yeasts

The

degree

of

smoothing

of

the

phylo-HMM

was

also

constrained

by

forcing

the

expected

amount

of

phylogenetic

information

-LRB-

in

an

information

theoretic

sense

-RRB-

required

to

predict

a

conserved

element

to

be

equal

for

all

data

sets

-LRB-

see

Methods

-RRB-

Our

results

are

in

general

not

highly

sensitive

to

the

precise

level

of

target

coverage

used

in

this

calibration

procedure

-LRB-

see

Supplemental

material

-RRB-

Based

on

the

estimated

parameters

conserved

elements

were

then

identified

in

each

set

of

multiple

alignments

using

the

phastCons

program

-LRB-

see

Methods

-RRB-

About

million

conserved

elements

were

predicted

for

the

vertebrate

data

set

about

for

the

insects

about

for

the

worms

and

about

for

the

yeasts

Each

predicted

element

was

assigned

a

log-odds

score

indicating

how

much

more

likely

it

was

under

the

conserved

state

of

the

phylo-HMM

than

under

the

nonconserved

state

-LRB-

see

Supplemental

material

-RRB-

A

synteny

filter

designed

to

eliminate

predictions

that

were

based

on

alignments

of

nonorthologous

sequence

-LRB-

especially

transposons

or

processed

pseudogenes

-RRB-

reduced

the

numbers

of

predictions

for

vertebrates

and

insects

to

about

million

and

respectively

alignments

of

nonorthologous

sequence

were

less

prevalent

in

the

worm

and

yeast

data

sets

so

the

filter

was

omitted

in

these

cases

The

remaining

predicted

elements

cover

of

the

human

genome

of

D.

melanogaster

of

C.

elegans

and

of

S.

cerevisiae

These

numbers

are

somewhat

sensitive

to

the

methods

used

for

parameter

estimation

Various

different

methods

produced

coverage

estimates

of

for

the

vertebrates

for

the

insects

for

the

worms

and

for

the

yeasts

-LRB-

see

Supplemental

material

-RRB-

Note

that

the

vertebrate

coverage

is

similar

to

recent

estimates

of

for

the

share

of

the

human

genome

that

is

under

purifying

selection

-LRB-

Chiaromonte

et

al.

Roskin

et

al.

Cooper

et

al.

-RRB-

despite

the

use

of

quite

different

methods

and

data

sets

-LRB-

In

the

discussion

that

follows

specific

estimates

of

quantities

of

interest

will

be

given

rather

than

ranges

of

estimates

The

reader

should

bear

in

mind

that

while

these

estimates

are

generally

not

highly

sensitive

to

the

method

used

for

parameter

estimation

they

do

change

somewhat

from

one

method

to

another

Further

details

are

given

in

the

Supplemental

material

-RRB-

The

million

vertebrate

elements

in

addition

to

covering

of

the

bases

in

known

coding

regions

-LRB-

approximately

the

target

level

-RRB-

cover

of

the

bases

in

known

UTRs

and

of

the

bases

in

known

UTRs

and

enrichments

respectively

compared

with

the

expected

coverage

if

the

predicted

conserved

elements

were

distributed

randomly

across

of

the

genome

-LRB-

Fig.

-RRB-

Almost

nine

of

-LRB-

-RRB-

known

protein-coding

exons

are

overlapped

by

predicted

elements

as

well

as

almost

two

of

three

known

UTR

exons

-LRB-

of

UTR

exons

and

of

UTR

exons

when

an

exon

contains

both

UTR

and

coding

sequence

the

UTR

portion

is

considered

to

be

a

separate

UTR

exon

-RRB-

Regions

not

in

known

genes

but

matching

publicly

available

mRNA

or

spliced

EST

sequences

-LRB-

other

mRNA

in

Fig.

-RRB-

show

coverage

by

conserved

elements

-LRB-

a

enrichment

-RRB-

and

regions

not

in

known

genes

or

other

mRNAs

but

transcribed

according

to

data

from

the

Affymetrix/NCI

Human

Transcriptome

project

-LRB-

other

trans

see

Methods

-RRB-

which

presumably

include

a

mixture

of

undocumented

coding

regions

UTRs

noncoding

RNAs

and

other

Figure

State-transition

diagram

for

the

phylo-HMM

used

by

phastCons

which

consists

of

a

state

for

conserved

regions

-LRB-

c

-RRB-

and

a

state

for

nonconserved

regions

-LRB-

n

-RRB-

Each

state

is

associated

with

a

phylogenetic

model

-LRB-

c

and

n

-RRB-

these

models

are

identical

except

for

a

scaling

parameter

-LRB-

-RRB-

which

is

applied

to

the

branch

lengths

of

c

and

represents

the

average

rate

of

substitution

in

conserved

regions

as

a

fraction

of

the

average

rate

in

nonconserved

regions

-LRB-

see

Methods

-RRB-

Two

parameters

and

-LRB-

-RRB-

define

all

state-transition

probabilities

as

illustrated

The

probability

of

visiting

each

state

first

-LRB-

indicated

by

arcs

from

the

node

labeled

begin

-RRB-

is

simply

set

equal

to

the

probability

of

that

state

at

equilibrium

-LRB-

stationarity

-RRB-

The

model

can

be

thought

of

as

a

probabilistic

machine

that

generates

a

multiple

alignment

consisting

of

alternating

sequences

of

conserved

-LRB-

dark

gray

-RRB-

and

nonconserved

-LRB-

light

gray

-RRB-

alignment

columns

-LRB-

see

example

at

bottom

-RRB-

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Evolutionarily

conserved

elements

conserved

elements

in

all

three

species

groups

but

still

appear

to

contain

substantial

numbers

of

conserved

bases

The

fractions

of

introns

and

intergenic

regions

in

conserved

elements

are

similar

with

introns

showing

slightly

higher

fractions

in

all

groups

but

yeast

-LRB-

where

they

are

few

in

number

-RRB-

In

worms

our

estimates

of

the

fractions

of

coding

regions

introns

and

intergenic

regions

that

are

conserved

are

fairly

similar

to

estimates

based

on

an

early

comparative

study

of

C.

elegans

and

C.

briggsae

-LRB-

Shabalina

and

Kondrashov

-RRB-

while

in

insects

our

estimates

of

these

fractions

for

intronic

and

intergenic

regions

are

roughly

higher

than

estimates

based

on

D.

melanogaster/D

virilis

comparisons

-LRB-

Bergman

and

Kreitman

-RRB-

Note

that

the

results

for

worm

may

be

influenced

by

the

difficulty

of

aligning

noncoding

regions

in

C.

elegans

and

C.

briggsae

and

by

the

limited

phylogenetic

information

in

pairwise

alignments

-LRB-

see

Discussion

and

Supplemental

material

-RRB-

Conversely

looking

at

how

the

predicted

conserved

elements

are

comFigure

The

assumed

tree

topologies

for

the

vertebrate

insect

worm

and

yeast

data

sets

-LRB-

top

to

posed

we

find

that

only

about

of

bottom

-RRB-

and

the

branch

lengths

estimated

for

the

conserved

-LRB-

left

-RRB-

and

nonconserved

-LRB-

right

-RRB-

states

of

the

bases

predicted

to

be

conserved

in

the

phylo-HMM

The

conserved

and

nonconserved

phylogenies

are

identical

except

for

the

scaling

constant

which

was

estimated

at

and

-LRB-

top

to

bottom

-RRB-

Horizontal

lines

indicate

vertebrates

fall

in

known

or

likely

exons

branch

lengths

and

are

drawn

to

scale

both

within

and

between

species

groups

The

estimated

trees

including

UTRs

-LRB-

Fig.

-RRB-

In

vertebrates

were

unrooted

arbitrary

roots

were

chosen

for

display

purposes

Note

that

some

distortions

in

the

of

conserved

bases

fall

in

known

branch

lengths

occur

due

to

alignment-related

ascertainment

biases

-LRB-

see

text

and

Supplemental

coding

regions

-LRB-

CDSs

-RRB-

and

material

-RRB-

fall

in

known

and

UTRs

respectively

and

another

fall

in

other

-LSB-

poly

-LRB-

A

-RRB-

-RSB-

transcripts

show

coverage

by

conserved

elemRNAs

Another

fall

in

other

transcribed

regions

leaving

ments

-LRB-

a

enrichment

-RRB-

Introns

of

known

genes

and

unabout

unannotated

-LRB-

The

percentage

in

RNA

genes

and

annotated

-LRB-

putative

intergenic

-RRB-

regions

contain

significant

fracother

known

noncoding

functional

elements

is

negligible

-RRB-

These

tions

of

conserved

bases

-LRB-

coverage

for

introns

and

numbers

are

in

good

agreement

both

with

bulk

statistical

esticoverage

for

unannotated

regions

-RRB-

but

smaller

fractions

than

mates

based

on

genome-wide

human/mouse

and

human

would

be

expected

by

chance

The

predicted

elements

also

inmouse/rat

alignments

of

the

share

of

the

human

genome

that

is

clude

of

the

bases

in

a

set

of

putative

RNA

genes

-LRB-

see

under

selection

-LRB-

Chiaromonte

et

al.

Roskin

et

al.

Methods

-RRB-

and

of

these

genes

are

overlapped

by

predicted

Cooper

et

al.

-RRB-

and

with

an

analysis

of

conserved

elements

elements

indicating

that

our

methods

are

reasonably

sensitive

in

the

region

of

the

CFTR

gene

-LRB-

Margulies

et

al.

Thomas

for

detecting

functional

noncoding

as

well

as

protein-coding

seet

al.

-RRB-

Broadly

speaking

if

of

the

human

genome

is

quences

-LRB-

If

only

RNA

genes

that

align

syntenically

across

species

conserved

and

if

codes

for

proteins

-LRB-

and

these

are

mostly

are

considered

the

base-level

coverage

increases

to

about

conserved

-RRB-

then

noncoding

regions

must

account

for

about

the

same

as

in

protein-coding

genes

-RRB-

The

predicted

elements

of

conserved

elements

Margulies

et

al.

-LRB-

-RRB-

include

of

the

bases

in

mammalian

ancestral

repeats

-LRB-

ARs

-RRB-

using

two

different

methods

found

that

of

bases

in

pre

-LRB-

see

Methods

-RRB-

which

are

believed

for

the

most

part

to

be

neudicted

conserved

elements

in

the

CFTR

region

were

not

in

exons

trally

evolving

suggesting

that

the

false-positive

rate

for

predicCooper

et

al.

-LRB-

-RRB-

reported

similar

results

based

on

wholetions

is

quite

low

-LRB-

Simulation

experiments

indicate

a

falsegenome

human/mouse/rat

alignments

positive

rate

of

in

all

species

groups

see

Supplemental

Interestingly

a

non-negligible

fraction

-LRB-

-RRB-

of

the

prematerial

-RRB-

dicted

conserved

elements

are

found

in

ARs

Simulation

experiIn

the

more

compact

insect

worm

and

yeast

genomes

less

ments

-LRB-

see

Supplemental

material

-RRB-

and

inspection

of

individual

dramatic

differences

are

observed

across

annotation

classes

in

the

cases

suggest

that

most

of

these

conserved

ARs

are

not

likely

to

be

coverage

by

conserved

elements

-LRB-

Fig.

-RRB-

In

all

three

cases

coding

false-positive

predictions

While

most

bases

in

ARs

have

evolved

regions

show

substantially

higher

coverage

than

would

be

exneutrally

-LRB-

ARs

are

underrepresented

fivefold

in

conserved

elepected

if

conserved

elements

were

distributed

randomly

as

do

ments

-RRB-

some

have

apparently

taken

on

critical

functions

that

UTRs

and

other

mRNAs

in

worms

-LRB-

but

not

in

insects

-RRB-

Introns

may

help

to

differentiate

mammals

from

ancestral

vertebrates

and

unannotated

regions

show

lower

than

expected

coverage

by

-LRB-

Britten

Jordan

et

al.

van

de

Lagemaat

et

al.

-RRB-

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Siepel

et

al.

pected

consequence

of

increasing

gene

density

-LRB-

the

more

genedense

genomes

have

smaller

fractions

of

noncoding

bases

-RRB-

but

it

nevertheless

underscores

the

importance

of

noncoding

regions

in

the

genomes

of

complex

eukaryotes

whose

complexity

apparently

derives

not

so

much

from

increased

numbers

of

proteincoding

genes

as

from

more

elaborate

mechanisms

for

gene

regulation

Note

that

the

fraction

of

conserved

elements

in

introns

and

intergenic

regions

may

be

underestimated

for

the

twospecies

worm

data

set

-LRB-

see

Discussion

and

Supplemental

material

-RRB-

The

lengths

of

the

predicted

elements

for

all

four

species

groups

are

approximately

geometrically

distributed

averaging

about

bp

for

the

vertebrate

insect

and

yeast

groups

and

about

bp

for

the

less

phylogenetically

informative

worm

group

In

all

groups

elements

range

in

length

from

bp

to

thousands

of

basepairs

A

more

detailed

analysis

in

vertebrates

revealed

noticeable

differences

in

the

length

distributions

of

the

elements

associated

with

different

types

of

annotations

elements

in

ARs

are

shortest

on

average

those

in

introns

and

intergenic

regions

are

slightly

longer

those

in

UTRs

are

longer

still

and

those

in

CDSs

are

longest

-LRB-

Supplemental

Fig

-RRB-

Accordingly

the

composition

of

conserved

elements

is

strongly

dependent

on

the

length-dependent

element

scores

-LRB-

Supplemental

Fig

-RRB-

In

particular

the

fractions

of

elements

in

coding

regions

UTRs

and

other

mRNAs

tend

to

increase

with

score

while

the

fraction

in

introns

tend

to

decrease

The

fraction

in

UTRs

is

particularly

large

among

the

highest

scoring

elements

suggesting

some

special

role

for

highly

conserved

UTRs

in

vertebrates

-LRB-

see

below

-RRB-

The

percentage

of

bases

in

ARs

also

decreases

sharply

with

element

score

Additional

details

are

given

in

the

Supplemental

material

Figure

Fractions

of

bases

of

various

annotation

types

covered

by

predicted

conserved

elements

-LRB-

left

-RRB-

and

fractions

of

bases

in

conserved

elements

belonging

to

various

annotation

types

-LRB-

right

-RRB-

Annotation

types

include

coding

regions

of

known

genes

-LRB-

CDS

-RRB-

and

UTRs

of

known

genes

other

regions

aligned

to

mRNAs

or

spliced

ESTs

from

GenBank

-LRB-

other

mRNA

-RRB-

other

transcribed

regions

according

to

data

from

Phase

of

the

Affymetrix/NCI

Human

Transcriptome

project

-LRB-

other

trans

see

Methods

-RRB-

introns

of

known

genes

and

other

regions

-LRB-

unannotated

-RRB-

All

annotations

were

for

the

reference

genome

of

each

species

group

and

all

fractions

were

computed

with

respect

to

these

genomes

-LRB-

see

Methods

-RRB-

Dashed

lines

in

column

graphs

indicate

expected

coverage

if

conserved

elements

were

distributed

uniformly

Transcriptome

data

was

available

for

the

vertebrates

only

and

UTRs

and

other

mRNAs

were

omitted

for

yeast

because

of

sparse

data

Note

that

these

graphs

change

somewhat

-LRB-

but

not

dramatically

-RRB-

under

alternative

calibration

methods

-LRB-

see

Supplemental

material

-RRB-

Base-by-base

conservation

scores

In

addition

to

predictions

of

discrete

conserved

elements

phastCons

produces

a

continuous-valued

conservation

score

for

each

base

of

the

reference

genome

These

scores

are

plotted

along

the

genome

and

displayed

as

part

of

a

conservation

track

in

the

version

of

the

UCSC

Genome

Browser

-LRB-

Karolchik

et

al.

-RRB-

dedicated

to

the

reference

genome

Beneath

the

plot

of

conservation

scores

the

conservation

track

also

has

an

alignment

display

which

shows

either

a

graphical

summary

of

the

pairwise

alignments

between

each

genome

and

the

reference

genome

or

-LRB-

at

appropriate

zoom

levels

-RRB-

the

actual

bases

of

the

multiple

alignment

Conservation

tracks

have

been

produced

for

all

four

data

sets

discussed

in

this

study

and

are

displayed

in

the

UCSC

Genome

Browsers

for

the

human

D.

melanogaster

C.

elegans

and

S.

cerevisiae

genomes

-LRB-

Fig.

-RRB-

Like

the

predicted

elements

the

base-by-base

conservation

scores

are

derived

from

the

two-state

phylo-HMM

The

conservation

score

at

each

base

in

the

reference

genome

is

defined

as

the

posterior

probability

that

the

corresponding

alignment

column

was

generated

by

the

conserved

state

-LRB-

rather

than

the

nonconserved

state

-RRB-

of

the

phylo-HMM

given

the

model

parameters

and

the

multiple

alignment

-LRB-

Thus

the

scores

range

between

and

-RRB-

The

conservation

scores

can

be

interpreted

as

probabilities

that

each

base

is

in

a

conserved

element

given

the

assumptions

of

the

model

and

the

maximum-likelihood

parameter

estimates

The

scores

are

also

influenced

by

the

values

of

two

userdefined

tuning

parameters

-LRB-

see

Methods

-RRB-

The

same

parameter

estimates

and

user-defined

parameters

are

used

for

both

the

conservation

scores

and

the

predicted

elements

Many

conserved

ARs

show

relatively

weak

conservation

but

some

are

more

strongly

conserved

For

example

one

highly

conserved

element

of

more

than

bp

in

a

gene

desert

between

the

zinc

finger

genes

and

contains

a

repeat

Three

conserved

elements

in

introns

of

the

RNAprocessing

gene

ranging

from

to

bp

in

length

contain

or

repeats

Moving

from

vertebrates

to

insects

and

then

to

worms

and

to

yeasts

in

decreasing

order

of

genome

size

and

general

biological

complexity

a

progressively

larger

fraction

of

conserved

elements

can

be

seen

to

fall

in

coding

regions

and

UTRs

and

a

progressively

smaller

fraction

in

introns

and

unannotated

regions

-LRB-

Fig.

-RRB-

In

particular

the

fraction

of

bases

in

predicted

conserved

elements

that

fall

in

known

or

likely

protein-coding

exons

increases

from

in

vertebrates

to

in

insects

in

worms

and

in

yeasts

so

that

while

most

conserved

bases

in

vertebrates

and

insects

apparently

do

not

code

for

proteins

most

in

worms

and

yeasts

do

This

trend

can

be

seen

as

an

ex

Genome

Research

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from

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by

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Spring

Harbor

Laboratory

Press

Figure

Screen

shots

of

the

conservation

tracks

in

the

-LRB-

A

-RRB-

human

and

-LRB-

B

-RRB-

S.

cerevisiae

UCSC

Genome

Browsers

Each

conservation

track

has

two

parts

a

plot

of

conservation

scores

and

beneath

it

a

display

showing

where

each

of

the

other

genomes

aligns

to

the

reference

genome

-LRB-

Darker

shading

indicates

higher

BLASTZ

scores

white

indicates

no

alignment

-RRB-

A

separate

track

labeled

PhastCons

Conserved

Elements

shows

predicted

conserved

elements

and

log-odds

scores

In

A

exons

of

the

RNA-edited

human

gene

are

shown

Peaks

in

the

conservation

plot

generally

correspond

to

exons

and

valleys

to

noncoding

regions

but

a

conserved

noncoding

element

can

be

seen

near

the

end

of

exon

This

conserved

element

includes

the

editing

complementary

sequence

-LRB-

ECS

-RRB-

of

the

RNA

editing

site

in

exon

The

displays

seen

when

zooming

in

to

the

base

level

at

a

typical

exon

-LRB-

left

-RRB-

and

in

the

region

of

the

RNA

editing

site

-LRB-

right

see

arrow

-RRB-

are

shown

as

insets

On

the

left

several

synonymous

substitutions

are

visible

-LRB-

highlighted

bases

-RRB-

and

the

elevated

conservation

abruptly

ends

after

the

splice

site

while

on

the

right

there

are

fewer

synonymous

substitutions

and

the

elevated

conservation

extends

into

the

intron

In

the

base-level

display

the

vertical

orange

bars

and

numbers

above

them

indicate

hidden

indels

and

their

lengths

i.e.

deletions

in

the

human

genome

or

insertions

in

other

genomes

In

B

the

S.

cerevisiae

gene

and

flanking

region

are

shown

Strong

cross-species

conservation

can

be

seen

in

the

regulatory

region

upstream

of

the

promoter

as

well

as

in

the

protein-coding

portion

of

the

gene

The

conserved

element

shown

at

bottom

overlaps

three

sites

-LRB-

highlighted

in

base-level

view

-RRB-

A

fourth

site

also

is

reflected

by

a

small

bump

in

the

conservation

scores

-LRB-

left

arrow

-RRB-

as

is

the

promoter

itself

-LRB-

right

arrow

-RRB-

Downloaded

from

on

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by

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Spring

Harbor

Laboratory

Press

Siepel

et

al.

The

conservation

tracks

are

useful

devices

for

visualizing

cross-species

conservation

along

a

genome

and

are

complementary

to

tracks

in

the

browser

describing

known

protein-coding

and

RNA

genes

known

regulatory

regions

aligned

mRNA

and

EST

sequences

gene

predictions

and

so

on

With

appropriate

parameter

settings

many

functional

elements

stand

out

clearly

as

mesas

of

cross-species

conservation

against

a

plain

of

neutral

or

nearly

neutral

evolution

-LRB-

Fig.

-RRB-

Sometimes

the

conservation

track

lends

support

to

independent

annotations

such

as

gene

predictions

in

other

cases

it

highlights

conserved

sequences

that

are

not

supported

by

any

existing

annotations

and

helps

to

stimulate

further

investigation

into

possible

functions

of

these

sequences

Using

the

UCSC

Table

Browser

-LRB-

-RRB-

it

is

possible

to

define

regions

of

the

genome

having

scores

that

exceed

-LRB-

or

fall

below

-RRB-

some

threshold

and

to

conduct

searches

that

intersect

the

conservation

scores

with

other

annotations

-LRB-

e.g.

find

all

intervals

with

conservation

scores

above

that

do

not

overlap

known

genes

-RRB-

The

conservation

track

has

been

popular

with

users

of

the

UCSC

Genome

Browser

and

the

phastCons

conservation

scores

are

already

in

use

in

several

other

research

projects

-LRB-

e.g.

ENCODE

Project

Consortium

Elnitski

et

al.

Ovachrenko

et

al.

King

et

al.

-RRB-

dency

of

the

log-odds

scores

and

the

tolerance

for

a

small

number

of

substitutions

The

HCEs

identified

for

the

other

three

sets

of

genomes

cover

a

higher

percentage

of

each

reference

genome

-LRB-

in

insect

in

worm

and

in

yeast

-RRB-

and

are

much

more

likely

to

overlap

coding

regions

-LRB-

of

HCEs

in

insect

in

worm

and

in

yeast

overlapped

CDSs

-RRB-

As

with

the

vertebrates

the

HCEs

for

the

other

three

species

groups

are

quite

long

with

lengths

ranging

from

to

bp

-LRB-

mean

bp

-RRB-

for

the

insects

to

bp

-LRB-

mean

bp

-RRB-

for

the

worms

and

to

bp

-LRB-

mean

bp

-RRB-

for

the

yeasts

The

fractions

of

HCEs

in

insects

overlapping

UTRs

are

similar

to

those

in

vertebrates

-LRB-

and

overlap

and

UTRs

respectively

-RRB-

but

in

worm

these

fractions

are

considerably

lower

-LRB-

and

-RRB-

-LRB-

Sparse

data

on

UTRs

in

yeasts

did

not

allow

for

a

comparison

with

this

group

-RRB-

In

insect

worm

and

yeast

only

about

of

highly

conserved

elements

fall

completely

in

introns

or

intergenic

regions

In

general

highly

conserved

elements

appear

to

become

more

strongly

associated

with

genes

as

genome

sizes

become

smaller

and

gene

densities

increase

consistent

with

the

trend

discussed

above

for

the

larger

set

of

conserved

elements

-LRB-

Fig.

-RRB-

HCEs

in

the

UTRs

of

vertebrate

genes

Highly

conserved

elements

The

genome-wide

sets

of

conserved

elements

predicted

for

each

of

the

four

species

groups

were

ranked

by

log-odds

score

and

the

top-scoring

elements

were

extracted

for

further

analysis

The

top

elements

were

selected

from

the

vertebrate

and

insect

sets

and

the

top

were

selected

from

the

smaller

worm

and

yeast

sets

-LRB-

The

numbers

of

elements

selected

were

essentially

arbitrary

they

were

chosen

to

be

small

enough

that

only

truly

extreme

cases

of

cross-species

conservation

would

be

included

but

large

enough

to

allow

meaningful

statistics

to

be

obtained

The

results

discussed

below

are

not

highly

sensitive

to

these

numbers

-RRB-

These

highly

conserved

elements

-LRB-

HCEs

-RRB-

are

like

ultraconserved

elements

-LRB-

UCEs

-RRB-

-LRB-

Bejerano

et

al.

-RRB-

in

that

they

show

extreme

evolutionary

conservation

-LRB-

defined

by

some

arbitrary

threshold

-RRB-

but

HCEs

tend

to

be

longer

than

UCEs

and

tend

to

have

less

extreme

sequence

conservation

due

to

the

length

dependency

of

the

log-odds

scores

In

addition

the

set

of

vertebrate

HCEs

is

about

larger

than

the

set

of

UCEs

and

is

based

on

a

different

set

of

species

-LRB-

including

chicken

and

Fugu

-RRB-

HCEs

are

different

from

-LRB-

and

in

some

ways

complementary

to

-RRB-

UCEs

nevertheless

the

vertebrate

HCEs

do

include

about

of

the

human/rodent

UCEs

identified

by

Bejerano

et

al.

-LRB-

-RRB-

-LRB-

The

that

are

not

included

tend

to

be

short

mean

length

bp

-RRB-

The

vertebrate

HCEs

cover

of

the

human

genome

They

are

considerably

longer

on

average

than

elements

in

the

full

set

-LRB-

lengths

ranged

from

to

bp

with

mean

bp

-RRB-

and

they

have

a

larger

fraction

of

bases

in

CDS

and

UTR

regions

-LRB-

Supplemental

Fig

-RRB-

At

the

base

level

coding

regions

are

enriched

for

HCEs

while

UTRs

and

UTRs

are

enriched

and

eightfold

respectively

Nevertheless

only

of

HCEs

overlap

known

exons

-LRB-

overlap

CDS

exons

overlap

UTR

exons

and

overlap

UTR

exons

-RRB-

with

falling

completely

in

known

introns

and

another

completely

in

unannotated

regions

The

fraction

of

HCEs

overlapping

known

exons

is

somewhat

higher

than

the

observed

for

UCEs

-LRB-

Bejerano

et

al.

-RRB-

presumably

because

of

the

length

depenAs

noted

above

UTRs

account

for

an

unexpectedly

large

fraction

of

bases

in

vertebrate

HCEs

and

this

trend

becomes

more

pronounced

as

higher

scoring

subsets

of

all

conserved

elements

are

considered

UTRs

account

for

of

bases

in

the

top

elements

in

the

top

and

in

the

top

compared

with

in

all

conserved

elements

-LRB-

Supplemental

Fig

-RRB-

In

contrast

UTRs

are

only

slightly

overrepresented

in

HCEs

-LRB-

of

bases

compared

with

in

all

conserved

elements

-RRB-

and

they

are

almost

absent

in

the

top

elements

Some

of

the

most

extreme

conservation

in

vertebrate

genomes

is

seen

in

the

UTRs

of

DNA

and

RNA-binding

genes

such

as

and

SYNCRIP

which

in

turn

are

regulators

of

other

genes

-LRB-

Supplemental

Table

Fig.

-RRB-

suggesting

that

regulation

in

UTRs

plays

a

key

role

in

critical

regulatory

networks

These

findings

are

consistent

with

earlier

reports

of

widespread

conservation

in

UTRs

-LRB-

Duret

et

al.

Lipman

-RRB-

some

of

which

have

noted

an

enrichment

for

genes

for

DNA-binding

proteins

-LRB-

Duret

et

al.

-RRB-

It

is

likely

that

many

conserved

UTR

sequences

are

involved

in

posttranscriptional

regulatory

mechanisms

e.g.

by

influencing

subcellular

localization

transcript

stability

or

translatability

-LRB-

Duret

et

al.

Grzybowska

et

al.

Mignone

et

al.

-RRB-

Post-transcriptional

regulation

by

microRNA

-LRB-

miRNA

-RRB-

binding

in

UTRs

is

of

particular

interest

as

it

is

believed

that

miRNAs

may

regulate

the

translation

of

a

large

fraction

of

eukaryotic

genes

-LRB-

e.g.

John

et

al.

Krek

et

al.

Lewis

et

al.

Xie

et

al.

-RRB-

Most

genes

known

and

predicted

to

be

targeted

by

miRNAs

in

D.

melanogaster

and

C.

elegans

as

well

as

human

and

mouse

show

only

moderate

conservation

in

their

UTRs

with

short

conserved

elements

alternating

with

nonconserved

regions

There

are

exceptions

however

such

as

which

is

targeted

by

in

mouse

and

has

a

HCE

in

its

UTR

is

unusual

among

known

animal

miRNAs

for

its

near-perfect

complementarity

to

its

target

site

and

for

inducing

cleavage

of

the

mRNA

rather

than

inhibiting

translation

-LRB-

Yekta

et

al.

-RRB-

Human

genes

with

predicted

miRNA

targets

appear

to

be

somewhat

enriched

for

UTR

HCEs

Genome

Research

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from

on

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by

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Harbor

Laboratory

Press

Evolutionarily

conserved

elements

Figure

Extreme

conservation

at

the

end

of

the

-LRB-

HuD

-RRB-

gene

an

RNA-binding

gene

associated

with

paraneoplastic

encephalomyelitis

sensory

neuropathy

and

homologous

to

Drosophila

genes

with

established

roles

in

neurogenesis

and

sex

determination

-LRB-

entrez/query

fcgi?db

OMIM

-RRB-

The

conserved

element

that

overlaps

the

UTR

of

this

gene

-LRB-

arrow

-RRB-

is

the

fifth

highest

scoring

conserved

element

in

the

human

genome

-LRB-

log

odds

score

-RRB-

Several

conserved

elements

in

introns

are

also

visible

examples

include

the

genes

for

the

eukaryotic

translation

initiation

factor

the

methyl

CpG-binding

protein

MECP

the

DNA-binding

proteins

-LRB-

and

oncoproteins

-RRB-

MYC

and

MYCN

the

homeobox

protein

NBPHOX

and

the

ubiquitin

protein

ligase

which

is

mutated

in

Angelman

syndrome

-LRB-

John

et

al.

-RRB-

We

also

found

several

examples

of

D.

melanogaster

genes

with

predicted

miRNA

target

sites

and

HCEs

in

their

UTRs

such

as

the

Hox

cluster

genes

Abd-B

Antp

Scr

and

Ubx

-LRB-

Enright

et

al.

-RRB-

Correlations

between

HCEs

and

predicted

miRNA

target

sites

must

be

treated

cautiously

because

they

may

be

artifacts

of

considering

conservation

in

target-site

prediction

Still

miRNA

binding

may

provide

at

least

a

partial

explanation

for

extreme

conservation

in

some

UTRs

e.g.

because

of

multiple

possibly

overlapping

target

sites

and/or

requirements

for

nearperfect

complementarity

Three

groups

of

known

RNA-binding

proteins

and

the

mRNAs

they

bind

provide

further

circumstantial

evidence

for

a

connection

between

HCEs

in

UTRs

and

post-transcriptional

regulation

and

moreover

-LRB-

if

predictions

of

target

sites

are

accurate

-RRB-

for

a

connection

with

miRNAs

John

et

al.

-LRB-

-RRB-

found

a

substantial

enrichment

for

predicted

miRNA

targets

among

the

genes

for

the

fragile

X

mental

retardation

protein

the

ELAV-like

proteins

and

the

polyadenylation-binding

proteins

-LRB-

CPEBs

-RRB-

and

among

the

genes

whose

mRNAs

are

known

to

be

bound

by

these

proteins

suggesting

that

miRNAs

play

a

critical

role

in

the

regulatory

networks

in

which

these

genes

participate

Interestingly

the

same

genes

are

also

highly

enriched

for

HCEs

in

UTRs

-LRB-

Fig.

-RRB-

The

gene

and

its

mRNA

cargoes

CIC

and

all

contain

both

predicted

miRNA

target

sites

and

HCEs

in

their

UTRs

as

do

the

genes

and

the

genes

FOS

and

MYC

whose

mRNAs

are

bound

by

ELAV-like

proteins

and

all

four

known

human

CPEB

genes

The

PURA

and

PURB

genes

which

interact

with

at

the

protein

level

also

have

HCEs

in

their

UTRs

Another

possible

reason

for

highly

conserved

sequences

in

UTRs

might

be

gene

regulation

via

antisense

transcription

-LRB-

Here

we

mean

cis-acting

rather

than

trans-acting

antisense

transcription

i.e.

transcription

of

both

DNA

strands

at

the

same

locus

-RRB-

For

example

if

long

perfect

RNA

duplexes

were

essential

for

regulation

then

sequence

conservation

might

result

from

selection

against

allelic

divergence

-LRB-

Lipman

-RRB-

This

possibility

is

of

particular

interest

in

light

of

the

recent

identification

of

a

large

number

of

apparent

sense/antisense

transcriptional

units

in

eukaryotic

genomes

many

of

which

overlap

in

their

UTRs

-LRB-

Shendure

and

Church

Yelin

et

al.

-RRB-

and

in

light

of

accumulating

evidence

for

the

importance

of

antisense

transcription

in

various

kinds

of

transcriptional

and

post-transcriptional

regulation

-LRB-

Lavorgna

et

al.

Dahary

et

al.

-RRB-

However

we

have

not

observed

a

strong

correlation

between

antisense

transcription

and

extreme

conservation

-LRB-

HCEs

-RRB-

in

UTRs

or

for

that

matter

extreme

conservation

in

UTRs

or

coding

regions

Only

a

few

of

the

known

sense/antisense

pairs

reviewed

by

Shendure

and

Church

-LRB-

-RRB-

contain

HCEs

coinciding

with

regions

of

sense/antisense

overlap

-LRB-

A

striking

example

is

the

nuclear

receptor

whose

UTR

overlaps

the

most

exon

of

the

thyroid

hormone

receptor

THRA

as

well

as

a

HCE

and

an

ultraconserved

element

-RRB-

Most

sense/antisense

pairs

show

only

moderate

conservation

Secondary

structure

in

noncoding

HCEs

Because

several

known

mechanisms

for

post-transcriptional

regulation

involve

stem-loop

-LRB-

and

other

-RRB-

structures

in

UTRs

-LRB-

Ross

Mignone

et

al.

-RRB-

strong

conservation

in

UTRs

may

occur

partly

as

a

result

of

structural

constraints

We

tested

HCEs

in

UTRs

for

statistical

evidence

of

secondary

structure

using

a

model

analogous

to

a

phylo-HMM

but

with

a

stochastic

contextfree

grammar

-LRB-

SCFG

-RRB-

in

place

of

a

hidden

Markov

model

SCFGs

are

richer

computational

models

than

HMMs

which

can

accommodate

the

long

distance

base

pairing

that

occurs

in

RNA

structures

-LRB-

Durbin

et

al.

-RRB-

Compared

with

an

ordinary

SCFG

a

phylo-SCFG

gains

additional

power

for

detecting

secondary

structure

by

picking

up

on

the

tendency

for

compensatory

substitutions

in

stem-pairing

sites

-LRB-

Knudsen

and

Hein

Pedersen

et

al.

-RRB-

-LRB-

see

also

Rivas

and

Eddy

-RRB-

We

evaluated

the

HCEs

in

UTRs

using

a

folding

potential

score

-LRB-

FPS

-RRB-

a

log-odds

score

derived

from

two

phylo-SCFGs

one

allowing

for

both

Genome

Research

Downloaded

from

on

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by

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Harbor

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Press

Siepel

et

al.

stem-pairing

and

nonpairing

sites

and

one

allowing

only

for

nonpairing

sites

-LRB-

see

Methods

-RRB-

The

FPS

reflects

possible

-LRB-

local

-RRB-

stem-pairings

within

each

sequence

in

a

multiple

alignment

and

compensatory

substitutions

along

the

branches

of

the

phylogeny

but

is

designed

to

avoid

biases

related

to

base

composition

overall

conservation

level

and

sequence

length

-LRB-

see

Methods

and

Supplemental

material

-RRB-

Compared

with

a

random

sample

of

UTRs

without

HCEs

the

HCEs

in

UTRs

have

considerably

higher

FPSs

on

average

indicating

a

significant

enrichment

for

local

secondary

structure

-LRB-

Fig.

-RRB-

The

HCEs

in

UTRs

in

contrast

do

not

have

significantly

higher

FPSs

than

those

of

non-HCE

UTRs

-LRB-

P

data

not

shown

-RRB-

However

this

finding

appeared

to

be

partly

a

consequence

of

spurious

stem

pairings

in

CpG

islands

-LRB-

CG

dinucleotides

are

sometimes

erroneously

predicted

to

pair

with

one

another

-RRB-

When

elements

overlapping

CpG

islands

are

excluded

the

UTR

HCEs

do

show

a

modest

but

statistically

significant

enrichment

for

secondary

structure

-LRB-

P

-RRB-

The

UTR

HCEs

also

have

significantly

higher

FPSs

than

do

the

UTR

HCEs

-LRB-

Fig.

-RRB-

These

results

provide

bulk

statistical

support

for

widespread

secondary

structure

in

highly

conserved

UTRs

and

suggest

that

secondary

structure

is

present

although

probably

less

widespread

in

highly

conserved

UTRs

It

is

worth

noting

that

the

non-HCE

UTRs

had

significantly

higher

FPSs

than

the

nonHCE

UTRs

suggesting

that

there

is

also

widespread

secondary

structure

in

UTRs

outside

of

highly

conserved

elements

Secondary

structure

in

intronic

and

intergenic

conserved

elements

is

also

of

interest

because

it

may

indicate

the

presence

of

novel

noncoding

RNAs

We

tested

the

intronic

and

intergenic

HCEs

and

found

strong

evidence

there

as

well

for

local

secondary

structure

FPSs

in

intronic

HCEs

are

on

average

about

the

same

as

those

in

UTR

HCEs

while

FPSs

in

intergenic

HCEs

are

on

average

intermediate

between

those

in

and

UTR

HCEs

We

also

computed

FPSs

for

HCEs

in

coding

regions

which

are

not

expected

to

have

extensive

secondary

structure

The

FPSs

of

both

intronic

and

intergenic

HCEs

as

well

as

those

of

and

UTR

HCEs

are

significantly

higher

than

those

of

coding

HCEs

-LRB-

Fig.

-RRB-

suggesting

that

many

intronic

and

intergenic

HCEs

may

function

at

the

RNA

level

A

similar

analysis

was

performed

with

the

insect

HCEs

Here

the

UTR

HCEs

show

a

statistically

significant

enrichment

for

secondary

structure

-LRB-

P

-RRB-

but

the

UTR

intronic

and

intergenic

HCEs

-LRB-

for

which

the

sample

sizes

are

quite

small

-RRB-

do

not

As

with

the

vertebrates

the

UTRs

without

HCEs

have

significantly

higher

FPSs

than

do

the

UTRs

without

HCEs

-LRB-

P

-RRB-

Several

of

the

intergenic

HCEs

overlap

known

functional

RNA

structures

annotated

in

FlyBase

We

did

not

analyze

the

noncoding

HCEs

for

secondary

structure

in

worm

and

yeast

because

data

for

these

species

groups

was

too

sparse

to

allow

meaningful

statistics

to

be

obtained

Clearly

much

more

can

be

done

on

the

topic

of

secondary

structure

in

conserved

elements

in

UTRs

introns

and

intergenic

regions

specific

structures

can

be

predicted

and

analyzed

structures

can

be

correlated

with

particular

categories

of

genes

and

so

on

A

manuscript

devoted

to

this

topic

is

in

preparation

-LRB-

J.S.

Pedersen

G.

Bejerano

and

D.

Haussler

in

prep

-RRB-

Functional

enrichment

of

genes

associated

with

HCEs

Using

the

Gene

Ontology

-LRB-

GO

-RRB-

database

-LRB-

Ashburner

et

al.

-RRB-

we

examined

the

molecular

functions

and

biological

processes

of

known

genes

overlapped

by

HCEs

in

coding

regions

UTRs

UTRs

and

introns

In

vertebrates

these

genes

are

enriched

for

many

of

the

same

GO

categories

that

are

associated

with

mammalian/vertebrate

ultraconserved

elements

-LRB-

Bejerano

et

al.

International

Chicken

Genome

Sequencing

Consortium

-RRB-

regions

with

high

fractions

of

conserved

noncoding

bases

-LRB-

International

Chicken

Genome

Sequencing

Consortium

-RRB-

stable

gene

deserts

-LRB-

Ovcharenko

et

al.

-RRB-

and

human/Fugu

conserved

noncoding

elements

-LRB-

Woolfe

et

al.

-RRB-

e.g.

DNA

binding

transcription

regulator

activity

and

development

-LRB-

Table

-RRB-

These

trans-dev

-LRB-

Woolfe

et

al.

-RRB-

categories

are

significantly

enriched

in

genes

overlapped

by

HCEs

in

UTRs

and

introns

as

well

as

in

coding

regions

Other

categories

are

more

strongly

associated

with

high

conservation

in

some

parts

of

genes

than

in

other

parts

of

genes

For

example

genes

overlapped

by

HCEs

in

coding

regions

are

more

strongly

enriched

for

ion

channel

activity

glutamate

receptor

activity

and

synaptic

transmission

than

are

genes

overlapped

in

other

regions

-LRB-

Table

-RRB-

suggesting

a

possible

connection

with

RNA

editing

Figure

Histograms

of

folding

potential

scores

-LRB-

FPSs

-RRB-

for

-LRB-

A

-RRB-

highly

conserved

elements

-LRB-

HCEs

-RRB-

in

UTRs

vs.

a

random

sample

of

UTRs

without

HCEs

-LRB-

B

-RRB-

HCEs

in

UTRs

vs.

HCEs

in

UTRs

and

-LRB-

C

-RRB-

HCEs

in

introns

vs.

HCEs

in

coding

regions

-LRB-

vertebrate

data

in

all

cases

-RRB-

Scores

are

based

on

a

phylogenetic

stochastic

context-free

grammar

and

represent

the

potential

for

local

secondary

structure

in

a

sliding

window

of

bp

-LRB-

see

Methods

-RRB-

In

all

three

cases

the

difference

between

the

distributions

is

highly

statistically

significant

-LRB-

P

P

and

P

respectively

Wilcoxon

rank

sum

test

-RRB-

Genome

Research

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Press

Evolutionarily

conserved

elements

Table

Selected

gene

ontology

-LRB-

GO

-RRB-

categories

of

vertebrate

genes

overlapped

by

highly

conserved

elements

CDS

Term

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

GO

a

UTR

Pd

exp

obs

158 119 115

P

UTR

exp

obs

221 140 122

P

Intron

exp

obs

P

Description

DNA

binding

transcription

regulator

activity

development

ion

channel

activity

chromatin

assembly/disassembly

neurogenesis

organogenesis

morphogenesis

glutamate

receptor

activity

transcription

factor

binding

protein

binding

microtubule-based

movement

RNA

binding

synaptic

transmission

cell

differentiation

cell-cell

signaling

mRNA

metabolism

mRNA

processing

ubiquitin

cycle

exp.b

obs.c

378 251 266

47 82 144 169

Number

of

genes

in

background

set

assigned

to

category

Expected

number

of

genes

overlapped

under

background

distribution

Observed

number

of

genes

overlapped

d

P-value

Values

of

less

than

can

be

considered

significant

-LRB-

see

Methods

-RRB-

b

c

There

are

several

known

cases

of

RNA-edited

ion

channel

genes

involved

in

neurotransmission

and

both

editing

sites

and

complementary

sequences

are

known

to

be

highly

conserved

-LRB-

Aruscavage

and

Bass

Hoopengardner

et

al.

-RRB-

Indeed

the

RNA-editing

site

in

shown

in

Figure

corresponds

to

an

HCE

as

do

the

editing

sites

in

the

related

genes

and

A

recently

identified

RNA-editing

site

in

-LRB-

Hoopengardner

et

al.

-RRB-

also

corresponds

to

an

HCE

one

of

the

top

by

log-odds

score

Other

categories

such

as

ubiquitin

cycle

RNA

binding

mRNA

metabolism

and

mRNA

processing

are

particularly

strongly

enriched

in

genes

overlapped

by

HCEs

in

UTRs

suggesting

that

many

of

these

HCEs

may

have

functional

roles

in

post-transcriptional

regulation

The

known

human

genes

overlapped

by

HCEs

include

many

wellstudied

disease

genes

-LRB-

Supplemental

Table

-RRB-

In

insects

worms

and

yeasts

genes

overlapped

by

HCEs

in

coding

regions

are

enriched

for

some

of

the

same

GO

categories

as

in

vertebrates

but

there

are

also

substantial

differences

across

species

groups

-LRB-

Supplemental

Table

-RRB-

The

insects

show

the

greatest

similarity

to

the

vertebrates

with

enrichment

for

several

trans-dev

categories

as

well

as

for

categories

such

as

protein

binding

cell

cell

signaling

synaptic

transmission

and

voltage-gated

ion

channel

activity

The

apparent

connection

with

RNA

editing

occurs

also

in

insects

the

RNA-edited

potassium

channel

genes

shaker

ether-a-go-go

and

slowpoke

-LRB-

Hoopengardner

et

al.

-RRB-

each

overlap

four

or

more

HCEs

-LRB-

see

related

observations

by

Glazov

et

al.

-RRB-

Some

new

categories

also

appear

in

insects

such

as

metamorphosis

and

oogenesis

The

worm

and

yeast

sets

are

generally

quite

different

from

the

vertebrate

and

insect

sets

although

overlap

does

occur

in

several

categories

including

RNA

binding

ion

transport

and

chromatin

assembly

or

disassembly

Categories

unique

to

worm

and

yeast

are

among

the

most

strongly

enriched

for

each

species

group

structural

constituent

of

cuticle

in

worm

and

structural

constituent

of

ribosome

in

yeast

The

enrichment

for

cuticle

-LRB-

primarily

collagen

-RRB-

genes

is

intriguing

as

these

genes

seem

to

require

the

same

kind

of

precise

regulation

required

by

many

development

genes

the

nematode

cuticle

is

synthesized

multiple

times

in

different

forms

during

the

nematode

life

cycle

in

a

complex

process

involving

the

differential

expression

of

more

than

individual

collagen

genes

-LRB-

Johnstone

-RRB-

As

in

vertebrates

the

insect

genes

overlapped

by

HCEs

in

and

UTRs

are

enriched

for

several

trans-dev

categories

Insect

genes

overlapped

in

UTRs

however

are

not

enriched

for

the

ubiquitin

cycle

RNA

binding

mRNA

metabolism

and

mRNA

processing

categories

which

are

strongly

enriched

in

their

vertebrate

counterparts

and

are

enriched

for

new

categories

such

as

structural

constituent

of

ribosome

cell

cell

signaling

and

synaptic

transmission

We

did

see

an

association

in

insects

as

in

vertebrates

between

UTR

HCEs

and

certain

known

post-transcriptional

regulatory

networks

For

example

the

insect

orthologs

of

the

vertebrate

ELAV-like

and

CPEB

genes

all

have

HCEs

overlapping

their

UTRs

Due

to

sparse

data

a

comparison

across

all

species

groups

was

not

possible

with

the

genes

overlapped

by

HCEs

in

UTRs

and

introns

The

general

conclusions

of

this

section

remain

unchanged

if

the

number

of

conserved

elements

considered

is

altered

by

a

factor

of

two

e.g.

if

the

top-scoring

or

worm

elements

are

analyzed

instead

of

the

top-scoring

Vertebrate

HCEs

and

segments

rich

in

conserved

noncoding

sequence

Based

on

human/chicken

comparisons

the

conserved

noncoding

fraction

-LRB-

CNF

-RRB-

of

the

human

genome

-LRB-

fraction

of

nonrepetitive

noncoding

sequence

that

aligns

to

chicken

-RRB-

in

regions

on

the

order

of

a

megabase

in

size

has

been

observed

to

vary

considerably

across

the

genome

Segments

of

particularly

high

CNF

tend

to

be

gene-poor

and

G+C

poor

In

addition

these

high-CNF

segments

contain

of

human/chicken

ultraconserved

elements

Genome

Research

Downloaded

from

on

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Published

by

Cold

Spring

Harbor

Laboratory

Press

Siepel

et

al.

while

themselves

occupying

only

of

the

human

genome

and

the

genes

overlapping

them

are

significantly

enriched

for

particular

-LRB-

mostly

trans-dev

-RRB-

GO

categories

-LRB-

International

Chicken

Genome

Sequencing

Consortium

-RRB-

We

defined

an

alternative

set

of

-LRB-

vertebrate

-RRB-

high-CNF

segments

-LRB-

phastCons

high-CNF

segments

as

opposed

to

human

chicken

high-CNF

segments

-RRB-

as

maximal

intervals

of

at

least

kb

having

CNFpc

of

at

least

where

CNFpc

is

the

fraction

of

noncoding

bases

that

fall

in

the

complete

set

of

conserved

elements

predicted

by

phastCons

-LRB-

genome-wide

average

repetitive

regions

are

included

here

-RRB-

There

are

phastCons

high-CNF

segments

covering

of

the

human

genome

and

averaging

kb

in

length

and

CNFpc

Unlike

human

chicken

high-CNF

segments

these

segments

are

not

significantly

depleted

for

genes

but

like

human/chicken

high-CNF

segments

they

show

a

significant

enrichment

for

trans-dev

genes

Certain

phastCons

high-CNF

segments

with

below-average

human

chicken

noncoding

conservation

appear

to

contain

significant

mammal-specific

conservation

-LRB-

see

Supplemental

material

-RRB-

Even

if

redefined

such

that

the

HCEs

are

excluded

when

computing

the

CNFpc

the

phastCons

high-CNF

segments

overlap

of

all

HCEs

and

of

intronic/intergenic

HCEs

enrichments

of

eightfold

and

respectively

Thus

there

appears

to

be

a

strong

correlation

between

moderate

conservation

in

megabase-sized

regions

and

extreme

conservation

in

smaller

regions

of

hundreds

or

thousands

of

bases

These

independently

defined

phastCons

high-CNF

segments

also

include

of

human/rodent

ultraconserved

elements

a

enrichment

gene

deserts

and

depleted

in

variable

gene

deserts

and

most

stable

deserts

have

HCEs

while

most

variable

deserts

do

not

These

results

lend

additional

support

to

the

claim

that

stable

and

variable

gene

deserts

are

fundamentally

different

and

further

suggest

that

many

intergenic

HCEs

may

be

distal

cis-regulatory

elements

particularly

of

trans-dev

genes

See

related

findings

by

Woolfe

et

al.

-LRB-

-RRB-

The

largest

human/chicken

high-CNF

segment

a

region

of

human

chromosome

spans

the

and

genes

and

about

two-thirds

of

a

gene

desert

on

one

side

of

-LRB-

International

Chicken

Genome

Sequencing

Consortium

Hillier

et

al.

-RRB-

Both

which

encodes

a

zinc

finger/homeodomain

transcription

factor

mutated

in

Hirschsprung

disease

syndrome

-LRB-

Supplemental

Table

-RRB-

and

have

numerous

HCEs

overlapping

coding

regions

introns

and

UTRs

-LRB-

in

ranging

from

to

bp

and

in

ranging

from

to

bp

-RRB-

The

portion

of

this

high-CNF

segment

falling

in

the

gene

desert

contains

HCEs

covering

of

its

bases

more

than

nine

times

the

genome-wide

average

This

region

vividly

illustrates

the

associations

among

high-CNF

segments

gene

deserts

trans-dev

genes

and

highly

conserved

elements

The

gene

deserts

flanking

the

developmental

genes

and

all

of

which

have

been

shown

experimentally

to

harbor

distal

enhancers

-LRB-

Nobrega

et

al.

Kimura-Yoshida

et

al.

Uchikawa

et

al.

-RRB-

are

also

rich

in

HCEs

Discussion

We

have

conducted

genome-wide

searches

for

conserved

elements

in

four

groups

of

eukaryotic

species

using

a

new

method

for

identifying

conserved

elements

that

considers

the

phylogeny

of

each

species

group

makes

use

of

continuous-time

Markov

models

of

nucleotide

substitution

and

allows

key

parameters

to

be

estimated

by

maximum

likelihood

To

our

knowledge

this

is

the

first

genome-wide

survey

and

comparison

of

conserved

elements

in

different

groups

of

eukaryotic

species

-LRB-

excluding

comparisons

primarily

of

proteomes

e.g.

Rubin

et

al.

-RRB-

Our

results

generally

support

previous

estimates

of

the

fraction

of

the

human

genome

under

selection

and

the

fraction

of

conserved

human

bases

that

fall

in

noncoding

regions

and

they

allow

for

an

approximate

quantitative

comparison

of

these

fractions

across

species

groups

In

addition

we

have

identified

highly

conserved

elements

-LRB-

HCEs

-RRB-

similar

in

some

ways

to

ultraconserved

elements

but

on

average

longer

and

less

perfectly

conserved

in

all

four

species

groups

Several

interesting

properties

of

these

HCEs

have

been

noted

including

an

association

in

vertebrates

and

insects

with

UTRs

particularly

of

genes

for

DNA

and

RNAbinding

proteins

an

enrichment

in

vertebrates

and

insects

for

statistical

evidence

of

RNA

secondary

structure

and

associations

in

vertebrates

with

high-CNF

segments

and

stable

gene

deserts

As

with

ultraconserved

elements

the

reasons

for

the

extreme

conservation

observed

in

most

vertebrate

HCEs

remain

unknown

but

statistical

enrichments

and

individual

cases

suggest

that

at

least

some

of

these

sequences

function

as

cisregulatory

binding

sites

as

RNA

genes

in

mRNA

secondary

structures

important

for

RNA

editing

or

post-transcriptional

regulation

or

as

microRNA

targets

Similar

evidence

was

found

for

insect

HCEs

The

lengths

of

the

conserved

sequences

however

remain

puzzling

What

could

explain

such

sustained

conservation

spanning

hundreds

or

thousands

of

bases

This

kind

of

conservation

is

not

seen

ordinarily

with

sequences

of

any

known

HCEs

and

gene

deserts

We

also

examined

the

question

of

whether

vertebrate

HCEs

are

associated

with

unusually

large

intergenic

regions

in

the

human

genome

-LRB-

gene

deserts

-RRB-

using

such

regions

recently

analyzed

by

Ovcharenko

et

al.

-LRB-

-RRB-

These

gene

deserts

have

a

minimum

length

of

kb

and

cover

of

the

human

genome

they

tend

to

have

low

G+C

content

high

single

nucleotide

polymorphism

-LRB-

SNP

-RRB-

rates

and

decreased

fractions

of

bases

conserved

between

human

chicken

and

mouse

On

the

basis

of

human/chicken

conservation

Ovcharenko

et

al.

-LRB-

-RRB-

divided

them

into

stable

deserts

-LRB-

higher

conservation

-RRB-

and

variable

deserts

-LRB-

lower

conservation

-RRB-

and

found

several

differences

between

these

two

classes

that

are

not

direct

consequences

of

conservation

level

e.g.

flanking

genes

of

stable

deserts

were

primarily

enriched

for

trans-dev

GO

categories

while

different

categories

were

associated

with

variable

deserts

Human/chicken

synteny

breaks

are

almost

completely

absent

in

stable

deserts

suggesting

that

these

regions

may

harbor

cis-regulatory

elements

whose

order

orientation

and

position

with

respect

to

flanking

genes

are

maintained

by

purifying

selection

-LRB-

consistent

with

recent

experimental

results

Nobrega

et

al.

Kimura-Yoshida

et

al.

Uchikawa

et

al.

-RRB-

-LRB-

but

see

also

Nobrega

et

al.

-RRB-

Stable

gene

deserts

account

for

only

of

bases

in

intergenic

regions

yet

of

the

intergenic

HCEs

fall

within

or

overlap

stable

deserts

times

the

expected

number

In

contrast

variable

gene

deserts

account

for

of

bases

in

intergenic

regions

and

only

of

intergenic

HCEs

fall

within

or

overlap

variable

deserts

Conversely

of

stable

deserts

include

or

are

overlapped

by

at

least

one

HCE

while

this

is

true

for

only

of

variable

deserts

Thus

HCEs

are

substantially

enriched

in

stable

Genome

Research

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from

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by

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Spring

Harbor

Laboratory

Press

Evolutionarily

conserved

elements

functional

class

One

possible

explanation

is

that

HCEs

result

from

cases

of

multiple

overlapping

constraints

e.g.

overlapping

binding

sites

binding

sites

overlapping

with

RNA

structural

or

protein-coding

constraints

or

overlapping

protein-coding

and

RNA

structural

constraints

-LRB-

as

in

RNA

editing

sites

within

coding

regions

-RRB-

A

related

possibility

is

that

these

sequences

are

hubs

of

regulatory

networks

which

because

of

their

interactions

with

many

other

RNAs

or

proteins

-LRB-

each

interaction

possibly

involving

a

slightly

different

subset

of

bases

-RRB-

have

become

evolutionarily

frozen

The

presence

of

UTR

HCEs

in

the

CPEB

and

ELAV-like

genes

as

well

as

in

related

genes

seems

to

support

this

hypothesis

Still

it

is

possible

that

some

HCEs

have

single

as-yet-undiscovered

functions

which

are

capable

of

producing

such

extreme

conservation

individually

We

also

can

not

rule

out

the

possibility

that

their

conservation

has

a

mutational

rather

than

a

selectional

explanation

i.e.

that

somehow

these

sequences

have

been

shielded

from

mutations

and/or

subjected

to

hyperefficient

repair

-LRB-

Bejerano

et

al.

-RRB-

Space

has

not

allowed

for

a

detailed

discussion

of

another

phenomenon

known

to

be

associated

with

unusual

levels

of

cross-species

conservation

that

of

alternative

splicing

-LRB-

e.g.

Sorek

and

Ast

Bejerano

et

al.

Rahman

et

al.

Sugnet

et

al.

-RRB-

Alternative

splicing

might

-LRB-

as

noted

by

a

reviewer

of

this

work

-RRB-

provide

some

useful

clues

about

how

unusual

noncoding

conservation

arises

For

example

sequences

flanking

-LRB-

and

within

-RRB-

alternatively

spliced

exons

which

are

believed

to

mediate

splicing

by

weakly

binding

various

interacting

proteins

-LRB-

e.g.

Black

-RRB-

may

tend

to

be

conserved

because

they

have

been

fine

tuned

by

evolution

to

promote

splicing

in

certain

tissue

types

or

development

stages

but

not

in

others

In

addition

the

same

sequence

may

bind

more

than

one

factor

or

may

have

roles

both

in

protein

binding

and

in

determining

secondary

structure

and

thus

may

provide

another

example

of

conservation

due

to

multiple

overlapping

constraints

It

is

worth

noting

that

an

association

between

HCEs

and

alternative

splicing

might

explain

some

of

the

functional

enrichments

we

have

observed

since

alternative

splicing

is

known

to

affect

some

classes

of

genes

-LRB-

including

development

genes

and

ion

channel

genes

-RRB-

more

than

others

However

we

have

not

found

an

enrichment

for

HCEs

in

a

set

of

about

alternatively

retained

cassette

exons

-LRB-

Sugnet

et

al.

-RRB-

as

compared

with

a

background

set

of

exons

On

the

other

hand

the

flanking

intronic

regions

of

these

exons

do

show

a

to

twofold

enrichment

for

conserved

elements

-LRB-

including

non-HCEs

-RRB-

These

elements

tend

to

be

short

e.g.

compared

with

those

in

UTRs

and

may

fail

to

be

identified

as

HCEs

simply

for

this

reason

The

relationship

between

alternative

splicing

and

cross-species

conservation

is

explored

further

in

a

forthcoming

study

by

C.

Sugnet

K.

Srinivasan

T.A.

Clark

G.

O'Brien

M.

Cline

A.

Williams

D.

Kulp

J.

Blume

D.

Haussler

and

M.

Ares

-LRB-

in

prep

-RRB-

Clearly

our

comparison

of

conserved

elements

across

species

groups

is

dependent

on

the

procedure

used

to

calibrate

the

model

Our

approach

of

holding

fixed

the

coverage

of

coding

regions

by

predicted

conserved

elements

assumes

that

coding

regions

evolve

in

fundamentally

similar

ways

across

species

groups

-LRB-

more

similar

than

noncoding

regions

-RRB-

and

that

the

fraction

of

sites

in

coding

regions

that

are

conserved

is

not

highly

sensitive

to

the

phylogeny

This

approach

has

some

obvious

deficiencies

First

there

undoubtedly

are

differences

between

groups

in

how

coding

regions

evolve

potentially

making

a

fixed

threshold

effectively

more

or

less

stringent

in

certain

groups

than

in

others

Some

possible

reasons

for

such

differences

include

differences

in

effective

population

size

in

the

strength

and

type

of

codon

bias

in

the

fraction

of

coding

sites

subject

to

noncoding

constraints

-LRB-

e.g.

related

to

splicing

or

RNA

editing

-RRB-

and

in

neighbor

dependencies

in

substitution

rates

Second

the

sensitivity

and

specificity

of

methods

for

detecting

conserved

elements

inevitably

depend

on

the

number

of

species

considered

their

phylogeny

and

the

amount

of

missing

data

-LRB-

Margulies

et

al.

-RRB-

all

of

which

differ

across

species

groups

-LRB-

see

Supplemental

material

-RRB-

Third

what

is

actually

conserved

across

species

-LRB-

as

distinct

from

what

is

predicted

to

be

conserved

-RRB-

is

a

function

of

the

evolutionary

divergence

of

the

species

being

considered

and

the

rate

at

which

turnover

of

functional

elements

occurs

over

evolutionary

time

-LRB-

Smith

et

al.

-RRB-

factors

which

also

may

differ

across

species

groups

It

is

difficult

to

imagine

a

calibration

procedure

that

would

address

all

of

these

problems

Indeed

there

is

probably

no

perfect

way

to

perform

a

quantitative

comparison

of

conserved

elements

across

groups

having

diverse

numbers

of

species

phylogenies

substitution

patterns

and

genome

sizes

and

the

results

of

any

such

comparison

should

be

interpreted

cautiously

Nevertheless

alternative

calibration

methods

based

on

full

maximumlikelihood

parameter

estimation

estimation

of

neutral

rates

from

fourfold

degenerate

sites

and

alternative

coverage

targets

in

coding

regions

have

led

to

generally

similar

results

-LRB-

see

Supplemental

material

-RRB-

and

certain

basic

conclusions

appear

to

be

fairly

robust

In

particular

the

fractions

of

bases

in

each

reference

genome

that

are

conserved

across

related

species

are

smallest

for

vertebrates

-LRB-

-RRB-

intermediate

for

worms

and

insects

-LRB-

and

respectively

-RRB-

and

largest

for

yeasts

-LRB-

-RRB-

In

addition

the

fractions

of

conserved

bases

that

fall

in

protein-coding

regions

are

lowest

for

vertebrates

-LRB-

-RRB-

slightly

higher

for

insects

-LRB-

-RRB-

substantially

higher

for

worms

-LRB-

-RRB-

and

highest

for

yeasts

-LRB-

-RRB-

Finally

while

the

HCEs

for

each

species

group

change

slightly

under

different

calibration

methods

the

general

properties

of

these

elements

are

quite

insensitive

to

the

calibration

method

Probably

the

weakest

part

of

our

analysis

concerns

the

worm

data

set

The

large

degree

of

divergence

between

C.

elegans

and

C.

briggsae

led

to

low-alignment

coverage

and

may

have

created

a

bias

toward

alignment

of

conserved

elements

in

coding

rather

than

noncoding

regions

-LRB-

because

conserved

noncoding

regions

tend

to

be

shorter

on

average

hence

harder

to

align

-RRB-

In

addition

having

only

two

species

considerably

reduced

the

amount

of

phylogenetic

information

per

site

forcing

the

tuning

parameter

-LRB-

expected

length

-RRB-

to

be

increased

and

in

turn

causing

short

conserved

elements

to

tend

to

be

missed

and

larger

numbers

of

nonconserved

bases

to

be

contained

within

predicted

conserved

elements

-LRB-

see

Methods

-RRB-

Together

these

factors

have

probably

resulted

in

an

overestimate

of

the

fraction

of

conserved

bases

that

fall

in

coding

regions

-LRB-

estimated

at

-RRB-

and

may

have

resulted

in

an

underestimate

of

the

total

fraction

conserved

-LRB-

estimated

at

-RRB-

With

additional

data

the

estimates

of

these

fractions

will

probably

move

toward

those

for

the

insects

although

it

seems

likely

that

they

will

fall

short

of

matching

the

insect

estimates

It

will

soon

be

possible

to

carry

out

an

improved

analysis

of

conserved

elements

in

both

worms

and

insects

with

the

sequencing

of

five

additional

nematodes

and

nine

additional

species

of

Drosophila

Several

more

vertebrate

genomes

will

also

soon

become

available

We

have

carried

out

a

preliminary

analysis

of

a

larger

set

of

insect

genomes

including

draft

assemblies

of

D.

ananassae

D.

virilis

and

D.

mojavensis

and

found

that

the

total

coverage

by

conserved

elements

and

the

fraction

of

conserved

elements

in

noncoding

regions

both

de

Genome

Research

Downloaded

from

on

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Published

by

Cold

Spring

Harbor

Laboratory

Press

Siepel

et

al.

creased

somewhat

but

did

not

change

dramatically

the

general

properties

of

conserved

elements

and

HCEs

were

essentially

unchanged

The

phylo-HMM

used

by

phastCons

is

a

fairly

rich

probabilistic

model

but

it

is

clearly

not

realistic

in

several

respects

The

assumptions

that

all

sites

evolve

at

one

of

two

evolutionary

rates

-LRB-

conserved

and

nonconserved

-RRB-

that

these

rates

are

uniform

across

the

genome

that

sites

evolve

independently

conditional

on

whether

they

are

in

conserved

or

nonconserved

regions

and

that

the

phylogenetic

models

for

conserved

and

nonconserved

regions

have

the

same

branch-length

proportions

base

compositions

and

substitution

patterns

all

represent

oversimplifications

of

the

complex

process

of

sequence

evolution

in

eukaryotic

genomes

-LRB-

e.g.

Hardison

et

al.

Hwang

and

Green

Siepel

and

Haussler

-RRB-

In

addition

treating

alignment

gaps

as

missing

data

ignores

an

important

source

of

phylogenetic

information

We

have

experimented

with

versions

of

phastCons

that

address

various

of

these

deficiencies

e.g.

by

introducing

states

for

additional

evolutionary

rates

-LRB-

Yang

Felsenstein

and

Churchill

-RRB-

allowing

the

phylogenetic

models

to

have

different

branch-length

proportions

or

substitution

patterns

or

using

substitution

models

that

consider

context

dependencies

in

substitution

rates

-LRB-

Siepel

and

Haussler

-RRB-

In

general

the

more

parameter-rich

and

complex

versions

increase

the

computational

burden

of

parameter

estimation

and

prediction

without

producing

an

appreciable

improvement

in

the

quality

of

the

program

's

output

More

complex

parameterizations

also

increase

the

danger

of

converging

on

biologically

uninteresting

local

maxima

of

the

likelihood

function

Thus

we

have

settled

on

the

relatively

simple

model

described

here

for

its

efficiency

interpretability

and

apparent

effectiveness

at

discriminating

between

conserved

and

nonconserved

sequences

Still

some

additional

complexity

in

the

model

may

turn

out

to

be

warranted

Possible

extensions

include

better

handling

of

indels

-LRB-

alignment

gaps

-RRB-

allowing

for

lineage-specific

conserved

elements

and

detecting

elements

with

other

types

of

evolutionary

signatures

such

as

those

under

positive

selection

Finally

it

is

important

to

note

that

our

entire

analysis

is

conditional

on

whole-genome

alignments

produced

by

the

MULTIZ

program

This

program

shows

good

accuracy

in

simulation

experiments

-LRB-

Blanchette

et

al.

-RRB-

and

our

synteny

filters

help

to

ensure

that

only

orthologous

conserved

elements

are

considered

but

whole-genome

alignment

is

a

difficult

problem

and

programs

that

address

it

are

still

in

their

infancy

Some

conserved

elements

are

undoubtedly

missed

because

of

alignment

failures

and

even

with

synteny

filtering

other

predicted

elements

are

probably

spurious

in

that

they

are

based

on

alignments

of

nonorthologous

sequence

Furthermore

misplacements

of

alignment

gaps

may

cause

regions

to

appear

more

or

less

conserved

than

they

really

are

It

will

be

important

to

recompute

predictions

of

conserved

elements

continually

as

multiple

aligners

improve

A

survey

of

conserved

elements

is

of

interest

in

its

own

right

by

helping

to

shed

light

on

the

evolutionary

forces

that

have

shaped

eukaryotic

genomes

but

it

is

only

a

first

step

toward

exhaustively

characterizing

the

diverse

functional

elements

in

these

genomes

Much

work

needs

to

be

done

to

establish

which

conserved

elements

are

functional

and

to

work

out

what

their

functions

are

-LRB-

ENCODE

Project

Consortium

-RRB-

We

hope

that

genome-wide

predictions

of

conserved

elements

and

visualization

devices

such

as

the

conservation

track

in

the

UCSC

Genome

Browser

will

be

helpful

resources

toward

this

end

Methods

Sequence

data

and

multiple

alignments

The

most

recent

assemblies

displayed

in

the

UCSC

Genome

Browser

as

of

Dec.

were

used

for

the

human

mouse

rat

chicken

D.

melanogaster

D.

yakuba

D.

pseudoobscura

A.

gambiae

C.

elegans

C.

briggsae

and

S.

cerevisiae

genomes

Contigs

for

S.

castelli

S.

kluyveri

and

S.

kudriavzevii

were

obtained

from

http

and

contigs

for

S.

mikatae

S.

bayanus

and

S.

paradoxus

were

obtained

from

Additional

details

are

given

in

Supplemental

Table

Multiple

alignments

for

each

species

group

were

prepared

using

version

of

the

MULTIZ

program

MULTIZ

builds

a

multiple

alignment

from

local

pairwise

alignments

of

a

designated

reference

genome

with

each

other

genome

of

interest

-LRB-

Blanchette

et

al.

-RRB-

Pairwise

alignments

were

obtained

by

using

BLASTZ

-LRB-

Schwartz

et

al.

-RRB-

then

were

passed

through

the

alignment

chaining

and

netting

pipeline

described

by

Kent

et

al.

-LRB-

-RRB-

which

ensures

that

each

base

of

the

reference

genome

is

aligned

to

at

most

one

base

in

each

other

genome

with

the

selection

procedure

being

guided

by

considerations

of

synteny

The

multiple

alignments

consisted

of

blocks

of

local

alignment

covering

of

the

human

genome

of

D.

melanogaster

of

C.

elegans

and

of

S.

cerevisiae

-LRB-

Supplemental

Table

-RRB-

The

alignment

coverage

in

known

coding

regions

was

considerably

higher

than

the

overall

coverage

-LRB-

for

human

for

D.

melanogaster

for

C.

elegans

and

for

S.

cerevisiae

-RRB-

Annotations

Annotations

for

only

the

reference

genome

of

each

species

group

were

considered

The

sets

of

known

human

coding

regions

and

UTRs

and

introns

were

based

on

the

UCSC

Known

Genes

track

as

of

and

the

set

of

other

mRNAs

was

based

on

the

human

mRNAs

and

human

spliced

ESTs

tracks

as

of

the

same

date

The

other

trans

set

was

based

on

data

from

Phase

of

the

Affymetrix/NCI

Human

Transcriptome

project

-LRB-

Cheng

et

al.

-RRB-

The

transcriptional

fragments

for

the

SK-NAS

cell

line

only

were

used

coverage

may

increase

when

additional

cell

lines

become

available

Results

were

extrapolated

from

chromosomes

X

and

Y

to

the

entire

genome

Ancestral

repeats

-LRB-

ARs

-RRB-

were

defined

as

sequences

in

the

human

genome

annotated

by

RepeatMasker

-LRB-

-RRB-

as

belonging

to

any

of

a

large

number

of

repeat

families

previously

identified

as

having

been

active

prior

to

the

eutherian

radiation

-LRB-

Mouse

Genome

Sequencing

Consortium

Hardison

et

al.

-RRB-

Putative

RNA

genes

were

identified

by

extracting

human

entries

from

the

hand-curated

seed

portion

of

Rfam

-LRB-

Griffiths-Jones

et

al.

-RRB-

and

mapping

them

to

the

genome

using

BLAT

-LRB-

Kent

-RRB-

Only

exact

matches

were

retained

but

many

of

these

genes

are

short

and

some

tend

to

match

repeats

so

some

false

matches

are

undoubtedly

included

in

this

set

-LRB-

The

sequences

mapped

perfectly

to

positions

in

the

genome

-RRB-

All

base-level

coverage

statistics

were

computed

in

the

coordinate

system

of

the

reference

genome

using

the

featureBits

program

-LRB-

featureBits

-RRB-

The

CDS

UTR

UTR

other

mRNA

other

transcribed

and

intron

sets

were

kept

disjoint

by

giving

priority

to

annotation

classes

in

the

order

listed

e.g.

if

a

base

was

annotated

as

both

CDS

and

UTR

then

it

was

counted

as

belonging

to

the

CDS

class

Statistics

describing

overlapping

features

-LRB-

e.g.

the

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Evolutionarily

conserved

elements

fraction

of

exons

overlapped

by

conserved

elements

-RRB-

were

based

on

a

version

of

the

annotations

containing

only

unique

nonoverlapping

instances

of

each

feature

type

-LRB-

e.g.

only

one

of

several

CDS

exons

associated

with

different

isoforms

of

the

same

gene

-RRB-

The

longest

member

of

each

set

of

overlapping

features

was

selected

Similar

procedures

were

used

with

the

other

species

groups

For

D.

melanogaster

known

protein-coding

genes

from

FlyBase

were

used

-LRB-

release

annotations

-RRB-

-LRB-

FlyBase

Consortium

-RRB-

and

for

S.

cerevisiae

known

genes

from

the

Saccharomyces

Genome

Database

-LRB-

SGD

-RRB-

-LRB-

Christie

et

al.

-RRB-

were

used

-LRB-

ORFs

classified

in

SGD

as

verified

and

uncharacterized

were

included

and

those

classified

as

dubious

were

excluded

-RRB-

For

C.

elegans

known

protein-coding

genes

from

WormBase

-LRB-

Harris

et

al.

-RRB-

and

RefSeq

-LRB-

Pruitt

et

al.

-RRB-

were

combined

in

order

to

maximize

data

on

UTRs

Using

these

average

parameter

estimates

conserved

elements

were

then

predicted

and

conservation

scores

were

generated

for

each

alignment

fragment

in

a

second

genome-wide

pass

Conserved

elements

were

predicted

using

the

Viterbi

algorithm

-LRB-

Durbin

et

al.

-RRB-

Conservation

scores

posterior

probabilities

that

each

site

was

generated

by

the

conserved

state

were

computed

using

the

forward/backward

algorithm

-LRB-

Durbin

et

al.

-RRB-

Each

predicted

conserved

element

was

assigned

a

log-odds

score

indicating

how

much

more

likely

it

is

under

the

conserved

phylogenetic

model

than

under

the

nonconserved

model

-LRB-

see

Supplemental

material

-RRB-

For

purposes

of

both

parameter

estimation

and

prediction

missing

data

in

the

alignments

-LRB-

e.g.

from

large-scale

insertions

and

deletions

assembly

gaps

or

extreme

sequence

divergence

-RRB-

and

smaller

scale

alignment

gaps

-LRB-

from

micro-indels

-RRB-

were

handled

by

marginalizing

over

missing

bases

when

computing

emission

probabilities

Predicted

vertebrate

elements

were

discarded

if

they

did

not

fall

on

the

syntenic

net

between

human

and

mouse

-LRB-

Kent

et

al.

-RRB-

and

predicted

insect

elements

were

discarded

if

they

did

not

fall

on

either

the

D.

melanogaster/D

yakuba

syntenic

net

or

the

D.

melanogaster/D

pseudoobscura

syntenic

net

See

the

Supplemental

material

for

additional

details

PhastCons

PhastCons

is

based

on

a

two-state

phylogenetic

hidden

Markov

model

-LRB-

phylo-HMM

-RRB-

with

a

state

for

conserved

regions

and

a

state

for

nonconserved

regions

-LRB-

Fig.

-RRB-

Phylo-HMMs

are

hidden

Markov

models

whose

states

are

associated

with

probability

distributions

over

alignment

columns

as

defined

by

phylogenetic

models

-LRB-

Yang

Felsenstein

and

Churchill

Siepel

and

Haussler

-RRB-

In

the

model

used

by

phastCons

the

phylogenetic

models

associated

with

the

two

states

are

identical

except

for

a

scaling

parameter

-LRB-

-RRB-

which

is

applied

to

the

branch

lengths

of

the

conserved

phylogeny

and

represents

the

average

rate

of

substitution

in

conserved

regions

as

a

fraction

of

the

average

rate

in

nonconserved

regions

The

model

is

defined

more

precisely

in

the

Supplemental

material

The

free

parameters

of

the

model

were

estimated

from

a

multiple

alignment

by

maximum

likelihood

using

an

expectation

maximization

-LRB-

EM

-RRB-

algorithm

The

algorithm

alternates

between

an

expectation

-LRB-

E

-RRB-

step

and

a

maximization

-LRB-

M

-RRB-

step

until

convergence

The

E

step

involves

computing

posterior

expected

counts

of

the

number

of

times

each

distinct

alignment

column

is

emitted

by

each

state

of

the

HMM

and

posterior

expected

counts

of

the

number

of

times

each

possible

state

transition

occurs

The

M

step

involves

updating

the

parameters

of

the

model

to

maximize

a

quantity

called

the

expected

complete

log

likelihood

which

is

based

on

the

posterior

expected

counts

This

is

a

completely

unsupervised

learning

procedure

i.e.

the

parameters

of

the

model

and

a

separation

between

conserved

and

nonconserved

sequences

are

learned

directly

from

the

data

without

relying

on

annotations

of

known

conserved

elements

Details

are

given

in

the

Supplemental

material

For

practical

reasons

exact

maximum

likelihood

estimates

-LRB-

m.l.e.

's

-RRB-

of

free

parameters

were

not

obtained

for

entire

genomewide

data

sets

but

instead

the

genome-wide

alignments

were

divided

into

fragments

of

at

most

about

Mb

in

length

-LRB-

in

the

coordinate

system

of

the

reference

genome

-RRB-

and

parameters

were

estimated

separately

for

each

fragment

-LRB-

Wherever

possible

the

cuts

between

fragments

were

made

in

regions

of

no

crossspecies

alignment

e.g.

in

transposon

insertions

in

the

reference

genome

-RRB-

These

separately

estimated

parameters

were

then

averaged

to

obtain

a

single

approximate

m.l.e.

for

each

genome-wide

data

set

Fragments

with

sparse

data

-LRB-

sites

aligned

-RRB-

were

excluded

from

this

procedure

but

the

amount

of

data

discarded

in

this

way

was

negligible

and

the

average

parameter

estimates

can

reasonably

be

said

to

represent

the

entire

genome-wide

data

sets

The

individual

parameter

estimates

were

fairly

consistent

and

their

averages

should

be

close

to

true

genome-wide

m.l.e.

's

-LRB-

see

Supplemental

material

-RRB-

Constraints

on

coverage

and

smoothness

The

parameters

of

the

model

were

estimated

by

maximum

likelihood

subject

to

two

constraints

a

coverage

constraint

determining

how

much

of

the

target

genome

is

predicted

to

be

conserved

and

a

smoothness

constraint

determining

how

similar

the

conservation

scores

are

from

one

site

to

the

next

and

how

fragmented

the

conserved

elements

are

As

noted

above

the

coverage

constraint

was

that

some

target

fraction

of

the

bases

in

known

coding

regions

must

be

covered

by

predicted

conserved

elements

after

adjusting

for

alignment

coverage

in

coding

regions

A

target

of

was

used

for

the

main

analysis

but

we

also

experimented

with

targets

of

and

-LRB-

see

Supplemental

material

-RRB-

The

smoothness

constraint

was

that

a

quantity

called

the

phylogenetic

information

threshold

-LRB-

PIT

-RRB-

must

be

the

same

for

all

species

groups

This

constraint

was

designed

to

ensure

that

predicted

conserved

elements

were

supported

by

similar

-LRB-

minimal

-RRB-

amounts

of

phylogenetic

evidence

taking

into

consideration

differences

in

phylogenetic

information

per

site

Briefly

let

Lmin

be

the

expected

minimum

length

of

a

sequence

of

conserved

sites

-LRB-

in

the

midst

of

a

stretch

of

nonconserved

sites

-RRB-

required

for

a

conserved

element

to

be

predicted

Assuming

conserved

and

nonconserved

sites

are

drawn

independently

from

the

distributions

associated

with

c

and

n

respectively

Lmin

is

given

by

Lmin

log

log

log

log

log

log

H

c

n

-LRB-

-RRB-

where

H

-LRB-

c

n

-RRB-

is

the

relative

entropy

of

the

distribution

associated

with

c

with

respect

to

the

distribution

associated

with

n

The

PIT

is

defined

as

the

product

of

Lmin

and

the

relative

entropy

H

-LRB-

c

n

-RRB-

it

can

be

interpreted

as

the

expected

minimum

amount

of

phylogenetic

information

required

to

predict

a

conserved

element

The

PIT

was

constrained

to

be

equal

to

bits

for

all

data

sets

More

details

are

given

in

the

Supplemental

material

These

constraints

were

met

by

iteratively

adjusting

two

tuning

parameters

as

follows

defined

as

the

expected

coverage

by

conserved

elements

and

defined

as

the

expected

length

of

a

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Siepel

et

al.

conserved

element

These

tuning

parameters

are

related

to

the

state-transition

parameters

and

by

the

equations

and

Acknowledgments

We

thank

Tom

Gingeras

for

permission

to

use

the

Affymetrix

transcriptional

fragments

for

the

SK-N-AS

cell

line

prior

to

publication

Doug

Smith

for

permission

to

use

preliminary

D.

virilis

and

D.

mojavensis

assemblies

and

Karin

Remington

for

permission

to

use

a

preliminary

D.

ananassae

assembly

to

check

our

insect

results

Krishna

Roskin

for

preparing

Figure

Shan

Yang

and

John

Karro

for

looking

at

correlations

of

conserved

elements

with

local

rates

of

neutral

human/mouse

substitutions

Elliott

Margulies

for

sharing

his

manuscript

with

us

ahead

of

publication

Ivan

Ovcharenko

Chuck

Sugnet

and

Ross

Hardison

for

helpful

conversations

Stefan

Bekiranov

for

comments

on

the

manuscript

and

the

anonymous

reviewers

for

their

especially

thorough

reading

of

the

manuscript

and

their

insightful

suggestions

Funding

was

provided

by

the

Howard

Hughes

Medical

Institute

the

National

Human

Genome

Research

Institute

-LRB-

grants

and

-RRB-

the

Achievements

Rewards

for

College

Scientists

-LRB-

ARCS

-RRB-

foundation

the

University

of

California

Biotechnology

Research

and

Education

Program

-LRB-

Graduate

Research

and

Education

in

Adaptive

Biotechnology

fellowship

-RRB-

and

the

Danish

Research

Council

-LRB-

Grant

-RRB-

-LRB-

see

Supplemental

material

-RRB-

Because

and

are

completely

determined

by

and

they

need

not

be

estimated

by

maximum

likelihood

when

and

are

set

by

the

user

to

satisfy

coverage

and

smoothing

constraints

Secondary

structure

The

folding

potential

score

-LRB-

FPS

-RRB-

is

based

on

two

phylo-SCFGs

one

with

a

stem-pairing

and

a

nonstem-pairing

component

-LRB-

sp

-RRB-

and

one

with

only

a

nonstem-pairing

component

-LRB-

nsp

-RRB-

Given

a

multiple

alignment

x

the

FPS

is

given

by

s

-LRB-

x

-RRB-

log

P

-LRB-

x

sp

-RRB-

log

P

-LRB-

x

nsp

-RRB-

where

P

-LRB-

x

i

-RRB-

is

the

total

probability

of

x

under

model

i

-LRB-

a

sum

over

all

allowable

structures

-RRB-

The

phylogenetic

models

in

sp

and

nsp

for

stem-pairing

and

nonpairing

positions

were

trained

on

known

RNA

structures

from

Rfam

-LRB-

Griffiths-Jones

et

al.

-RRB-

but

were

forced

to

have

equal

expected

rates

of

substitution

to

avoid

biases

related

to

conservation

level

In

addition

the

rate

matrix

in

nsp

is

a

marginalized

version

of

the

rate

matrix

in

sp

so

that

the

two

models

make

use

of

the

same

nucleotide

distribution

Possible

biases

related

to

alignment

gaps

and

missing

data

were

avoided

by

constraining

the

structures

such

that

alignment

columns

with

gaps

or

missing

data

had

to

fall

in

nonpairing

regions

See

the

Supplemental

material

for

additional

details

The

FPSs

for

both

the

HCE

and

the

data

sets

were

computed

from

local

multiple

alignments

extracted

from

the

genome-wide

MULTIZ

alignments

To

avoid

length

biases

we

did

not

score

whole

UTRs

but

instead

computed

the

FPS

locally

in

a

sliding

window

of

bp

-LRB-

step

size

bp

-RRB-

The

distribution

of

FPSs

for

windows

in

UTR

HCEs

were

simply

compared

with

the

distributions

of

FPSs

for

windows

in

randomly

selected

non-HCE

UTRs

i.e.

the

scores

were

not

combined

per

UTR

Similarly

the

distributions

of

FPSs

for

intronic

intergenic

and

coding

HCEs

represented

individual

windows

only

These

distributions

reflect

the

potential

for

local

structural

features

-LRB-

e.g.

stem

loops

-RRB-

in

each

set

rather

than

the

potential

for

global

structures

Distributions

of

FPSs

were

compared

using

the

Wilcoxon

rank

sum

test

For

the

purposes

of

statistical

testing

only

the

FPSs

for

nonoverlapping

windows

were

considered

Using

different

window

sizes

relaxing

the

constraints

on

columns

with

missing

data

and

using

the

Kolmogorov-Smirnov

test

instead

of

the

Wilcoxon

test

did

not

produce

significant

differences

in

our

results

References

Aruscavage

P.J.

and

Bass

B.L.

A

phylogenetic

analysis

reveals

an

unusual

sequence

conservation

within

introns

involved

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Genome

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Genome

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N.

and

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MAVID

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Genome

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Genome

Res

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Genome

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be

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the

tail

of

the

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No

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but

there

were

fewer

than

individual

tests

so

P

can

be

considered

significant

At

most

one

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background

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Received

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in

revised

form

June

Genome

Research

selection evolution yeast phastcons noncoding insects conserved worm