Vol

November

doi

ARTICLES

Evolution

of

genes

and

genomes

on

the

Drosophila

phylogeny

Drosophila

Genomes

Consortium

Comparative

analysis

of

multiple

genomes

in

a

phylogenetic

framework

dramatically

improves

the

precision

and

sensitivity

of

evolutionary

inference

producing

more

robust

results

than

single-genome

analyses

can

provide

The

genomes

of

Drosophila

species

ten

of

which

are

presented

here

for

the

first

time

-LRB-

sechellia

simulans

yakuba

erecta

ananassae

persimilis

willistoni

mojavensis

virilis

and

grimshawi

-RRB-

illustrate

how

rates

and

patterns

of

sequence

divergence

across

taxa

can

illuminate

evolutionary

processes

on

a

genomic

scale

These

genome

sequences

augment

the

formidable

genetic

tools

that

have

made

Drosophila

melanogaster

a

pre-eminent

model

for

animal

genetics

and

will

further

catalyse

fundamental

research

on

mechanisms

of

development

cell

biology

genetics

disease

neurobiology

behaviour

physiology

and

evolution

Despite

remarkable

similarities

among

these

Drosophila

species

we

identified

many

putatively

non-neutral

changes

in

protein-coding

genes

non-coding

RNA

genes

and

cis-regulatory

regions

These

may

prove

to

underlie

differences

in

the

ecology

and

behaviour

of

these

diverse

species

As

one

might

expect

from

a

genus

with

species

living

in

deserts

in

the

tropics

on

chains

of

volcanic

islands

and

often

commensally

with

humans

Drosophila

species

vary

considerably

in

their

morphology

ecology

and

Species

in

this

genus

span

a

wide

range

of

global

distributions

the

sequenced

species

originate

from

Africa

Asia

the

Americas

and

the

Pacific

Islands

and

also

include

cosmopolitan

species

that

have

colonized

the

planet

-LRB-

D.

melanogaster

and

D.

simulans

-RRB-

as

well

as

closely

related

species

that

live

on

single

islands

-LRB-

D.

sechellia

-RRB-

A

variety

of

behavioural

strategies

is

also

encompassed

by

the

sequenced

species

ranging

in

feeding

habit

from

generalist

such

as

D.

ananassae

to

specialist

such

as

D.

sechellia

which

feeds

on

the

fruit

of

a

single

plant

species

Despite

this

wealth

of

phenotypic

diversity

Drosophila

species

share

a

distinctive

body

plan

and

life

cycle

Although

only

D.

melanogaster

has

been

extensively

characterized

it

seems

that

the

most

important

aspects

of

the

cellular

molecular

and

developmental

biology

of

these

species

are

well

conserved

Thus

in

addition

to

providing

an

extensive

resource

for

the

study

of

the

relationship

between

sequence

and

phenotypic

diversity

the

genomes

of

these

species

provide

an

excellent

model

for

studying

how

conserved

functions

are

maintained

in

the

face

of

sequence

divergence

These

genome

sequences

provide

an

unprecedented

dataset

to

contrast

genome

structure

genome

content

and

evolutionary

dynamics

across

the

well-defined

phylogeny

of

the

sequenced

species

-LRB-

Fig.

-RRB-

Genome

assembly

annotation

and

alignment

Genome

sequencing

and

assembly

We

used

the

previously

published

sequence

and

updated

assemblies

for

two

Drosophila

species

D.

-LRB-

release

-RRB-

and

D.

-LRB-

release

-RRB-

and

generated

DNA

sequence

data

for

additional

Drosophila

genomes

by

whole-genome

shotgun

These

species

were

chosen

to

span

a

wide

variety

of

evolutionary

distances

from

closely

related

pairs

such

as

D.

sechellia/D

simulans

and

D.

persimilis/D

pseudoobscura

to

the

distantly

related

species

of

the

Drosophila

and

Sophophora

subgenera

Whereas

the

time

to

the

most

recent

common

ancestor

of

the

sequenced

species

may

seem

small

on

an

evolutionary

timescale

the

evolutionary

divergence

spanned

by

the

genus

Drosophila

exceeds

A

list

of

participants

and

affiliations

appears

at

the

end

of

the

paper

that

of

the

entire

mammalian

radiation

when

generation

time

is

taken

into

account

as

discussed

further

in

ref

We

sequenced

seven

of

the

new

species

-LRB-

D.

yakuba

D.

erecta

D.

ananassae

D.

willistoni

D.

virilis

D.

mojavensis

and

D.

grimshawi

-RRB-

to

deep

coverage

-LRB-

to

-RRB-

to

produce

high

quality

draft

sequences

We

sequenced

two

species

D.

sechellia

and

D.

persimilis

to

intermediate

coverage

-LRB-

and

respectively

-RRB-

under

the

assumption

that

the

availability

of

a

sister

species

sequenced

to

high

coverage

would

obviate

the

need

for

deep

sequencing

without

sacrificing

draft

genome

quality

Finally

seven

inbred

strains

of

D.

simulans

were

sequenced

to

low

coverage

-LRB-

coverage

from

and

coverage

of

six

other

strains

-RRB-

to

provide

population

variation

Further

details

of

the

sequencing

strategy

can

be

found

in

Table

Supplementary

Table

and

section

in

Supplementary

Information

We

generated

an

initial

draft

assembly

for

each

species

using

one

of

three

different

whole-genome

shotgun

assembly

programs

-LRB-

Table

-RRB-

For

D.

ananassae

D.

erecta

D.

grimshawi

D.

mojavensis

D.

virilis

and

D.

willistoni

we

also

generated

secondary

assemblies

reconciliation

of

these

with

the

primary

assemblies

resulted

in

a

decrease

in

the

estimated

number

of

misassembled

regions

and

a

increase

in

the

contig

-LRB-

Supplementary

Table

-RRB-

For

D.

yakuba

we

generated

targeted

reads

across

low-quality

regions

and

gaps

to

improve

the

assembly

This

doubled

the

mean

contig

and

scaffold

sizes

and

increased

the

total

fraction

of

high

quality

bases

-LRB-

quality

score

-LRB-

Q

-RRB-

-RRB-

from

to

We

improved

the

initial

D.

simulans

whole-genome

shotgun

assembly

by

filling

assembly

gaps

with

contigs

and

unplaced

reads

from

the

assemblies

of

the

six

other

D.

simulans

strains

generating

a

mosaic

assembly

-LRB-

Supplementary

Table

-RRB-

This

integration

markedly

improved

the

D.

simulans

assembly

the

contig

size

of

the

mosaic

assembly

for

instance

is

more

than

twice

that

of

the

initial

assembly

-LRB-

kb

versus

kb

-RRB-

Finally

one

advantage

of

sequencing

genomes

of

multiple

closely

related

species

is

that

these

evolutionary

relationships

can

be

exploited

to

dramatically

improve

assemblies

D.

yakuba

and

D.

simulans

contigs

and

scaffolds

were

ordered

and

oriented

using

pairwise

alignment

to

the

well-validated

D.

melanogaster

genome

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

D.

melanogaster

melanogaster

subgroup

Subgenus

Sophophora

melanogaster

group

D.

simulans

D.

sechellia

D.

yakuba

D.

erecta

D.

ananassae

obscura

willistoni

group

group

D.

pseudoobscura

D.

persimilis

D.

willistoni

D.

virilis

X

mutations

per

site

PP

MP

Subgenus

Drosophila

D.

mojavensis

Hawaiian

D.

grimshawi

Drosophila

virilis

group

repleta

group

Figure

Phylogram

of

the

sequenced

species

of

Drosophila

Phylogram

derived

using

pairwise

genomic

mutation

distances

and

the

neighbourjoining

Numbers

below

nodes

indicate

the

per

cent

of

genes

supporting

a

given

relationship

based

on

evolutionary

distances

estimated

from

fourfold-degenerate

sites

-LRB-

left

of

solidus

-RRB-

and

second

codon

positions

-LRB-

right

of

solidus

-RRB-

Coloured

blocks

indicate

support

from

bayesian

-LRB-

posterior

probability

-LRB-

PP

-RRB-

upper

blocks

-RRB-

and

maximum

parsimony

-LRB-

MP

bootstrap

values

lower

blocks

-RRB-

analyses

of

data

partitioned

by

chromosome

arm

Branch

lengths

indicate

the

number

of

mutations

per

site

-LRB-

at

fourfolddegenerate

sites

-RRB-

using

the

ordinary

least

squares

method

See

ref

for

a

discussion

of

the

uncertainties

in

the

D.

yakuba/D

erecta

clade

sequence

-LRB-

Supplementary

Information

section

-RRB-

Likewise

the

D.

persimilis

and

D.

sechellia

assemblies

were

improved

by

assisted

assembly

using

the

sister

species

-LRB-

D.

pseudoobscura

and

D.

simulans

respectively

-RRB-

to

validate

both

alignments

between

reads

and

linkage

information

For

the

remaining

species

comparative

syntenic

information

and

in

some

cases

linkage

information

were

also

used

to

pinpoint

locations

of

probable

genome

misassembly

to

assign

assembly

scaffolds

to

chromosome

arms

and

to

infer

their

order

and

orientation

along

euchromatic

chromosome

arms

supplementing

experimental

analysis

based

on

known

markers

-LRB-

A.

Bhutkar

S.

Russo

S.

Schaeffer

T.

F.

Smith

and

W.

M.

Gelbart

personal

communication

-RRB-

-LRB-

Supplementary

Information

section

-RRB-

The

mitochondrial

-LRB-

mt

-RRB-

DNA

of

D.

melanogaster

D.

sechellia

D.

simulans

-LRB-

siII

-RRB-

D.

mauritiana

-LRB-

maII

-RRB-

and

D.

yakuba

have

been

previously

For

the

remaining

species

-LRB-

except

D.

pseudoobscura

the

DNA

from

which

was

prepared

from

embryonic

nuclei

-RRB-

we

were

able

to

assemble

full

mitochondrial

genomes

excluding

the

control

region

-LRB-

Supplementary

Information

section

-RRB-

In

addition

the

genome

sequences

of

three

Wolbachia

endosymbionts

-LRB-

Wolbachia

wSim

Wolbachia

wAna

and

Wolbachia

wWil

-RRB-

were

assembled

from

trace

archives

in

D.

simulans

D.

ananassae

and

D.

willistoni

All

of

the

genome

sequences

described

here

are

available

in

FlyBase

-LRB-

-RRB-

and

GenBank

-LRB-

-RRB-

-LRB-

Supplementary

Tables

and

-RRB-

Repeat

and

transposable

element

annotation

Repetitive

DNA

sequences

such

as

transposable

elements

pose

challenges

for

whole-genome

shotgun

assembly

and

annotation

Because

the

best

approach

to

transposable

element

discovery

and

identification

is

still

an

active

and

unresolved

research

question

we

used

several

repeat

libraries

and

computational

strategies

to

estimate

the

transposable

element/repeat

content

of

the

Drosophila

genome

assemblies

-LRB-

Supplementary

Information

section

-RRB-

Previously

curated

transposable

element

libraries

in

D.

melanogaster

provided

the

starting

point

for

our

analysis

to

limit

the

effects

of

ascertainment

bias

we

also

developed

de

novo

repeat

libraries

using

and

We

used

four

transposable

element/repeat

detection

methods

-LRB-

RepeatMasker

BLASTER-TX

RepeatRunner

and

CompTE

-RRB-

in

conjunction

with

these

transposable

element

libraries

to

identify

repetitive

elements

in

non-melanogaster

species

We

assessed

the

accuracy

of

each

method

by

calibration

with

the

estimated

transposable

element

content

in

the

D.

melanogaster

genome

which

is

based

on

a

high-resolution

transposable

element

-LRB-

Supplementary

Fig.

-RRB-

On

the

basis

of

our

results

we

suggest

a

hybrid

strategy

for

new

genome

sequences

employing

translated

BLAST

with

general

transposable

element

libraries

and

RepeatMasker

with

species-specific

ReAS

libraries

to

estimate

the

upper

and

lower

bound

on

transposable

element

content

Protein-coding

gene

annotation

We

annotated

protein-coding

sequences

in

the

non-melanogaster

genomes

using

four

different

de

novo

gene

predictors

-LRB-

and

-RRB-

three

homology-based

predictors

that

transfer

annotations

from

D.

melanogaster

-LRB-

-RRB-

and

one

predictor

that

combined

de

novo

and

homology-based

evidence

-LRB-

-RRB-

These

gene

prediction

sets

Table

A

summary

of

sequencing

and

assembly

properties

of

each

new

genome

Final

assembly

Genome

centre

coverage

-LRB-

-RRB-

Assembly

size

-LRB-

Mb

-RRB-

No

of

contigs

kb

contig

kb

-LRB-

kb

-RRB-

Per

cent

of

base

pairs

with

quality

D.

simulans

D.

sechellia

D.

yakuba

D.

erecta

D.

ananassae

D.

persimilis

D.

willistoni

D.

virilis

D.

mojavensis

D.

grimshawi

WUGSC

Broad

-LCB-

WUGSC

Agencourt

-LCB-

Agencourt

-LCB-

Broad

-LCB-

JCVI

-LCB-

Agencourt

-LCB-

Agencourt

-LCB-

Agencourt

-LCB-

17 43 125 458

113 20 197 136

Contigs

contiguous

sequences

not

interrupted

by

gaps

the

largest

length

L

such

that

of

all

nucleotides

are

contained

in

contigs

of

size

L

The

coverage

of

contigs

is

based

on

the

number

of

assembled

reads

average

readlength

and

the

assembled

size

excluding

gaps

Assemblers

used

-LCB-

and

-LCB-

Celera

Assembler

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

Table

A

summary

of

annotated

features

across

all

genomes

Protein-coding

gene

annotations

Total

no

of

protein

coding

genes

-LRB-

per

cent

with

D.

melanogaster

homologue

-RRB-

Coding

sequence

intron

-LRB-

Mb

-RRB-

tRNA

-LRB-

pseudo

-RRB-

snoRNA

Non-coding

RNA

annotations

miRNA

rRNA

-LRB-

S

-RRB-

snRNA

Repeat

coverage

-LRB-

-RRB-

Genome

size

-LRB-

Mb

assembly

-LCB-

flow

cytometry

-LCB-

-RRB-

D.

melanogaster

D.

simulans

D.

sechellia

D.

yakuba

D.

erecta

D.

ananassae

D.

pseudoobscura

D.

persimilis

D.

willistoni

D.

virilis

D.

mojavensis

D.

grimshawi

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

250 246 242 255

252 194 203 199

216 165 139 154

133 55 101 134

Repeat

coverage

calculated

as

the

fraction

of

scaffolds

kb

covered

by

repeats

estimated

as

the

midpoint

between

BLASTER-tx

PILER

and

RepeatMasker

ReAS

-LRB-

Supplementary

Information

section

-RRB-

-LCB-

Total

genome

size

estimated

as

the

sum

of

base

pairs

in

genomic

scaffold

bp

-LCB-

Genome

size

estimates

based

on

flow

were

combined

using

GLEAN

a

gene

model

combiner

that

chooses

the

most

probable

combination

of

start

stop

donor

and

acceptor

sites

from

the

input

All

analyses

reported

here

unless

otherwise

noted

relied

on

a

reconciled

consensus

set

of

predicted

gene

models

the

GLEAN-R

set

-LRB-

Table

and

Supplementary

Information

section

-RRB-

Quality

of

gene

models

As

the

first

step

in

assessing

the

quality

of

the

GLEAN-R

gene

models

we

used

expression

data

from

microarray

experiments

on

adult

flies

with

arrays

custom-designed

for

D.

simulans

D.

yakuba

D.

ananassae

D.

pseudoobscura

D.

virilis

and

D.

-LRB-

GEO

series

Supplementary

Information

section

-RRB-

We

detected

expression

significantly

above

negative

controls

-LRB-

false-discovery-rate-corrected

Mann

Whitney

U

-LRB-

MWU

-RRB-

P

-RRB-

for

of

assayed

GLEAN-R

models

representing

of

the

total

GLEAN-R

predictions

in

each

species

-LRB-

Supplementary

Table

-RRB-

Evolutionarily

conserved

gene

models

are

much

more

likely

to

be

expressed

than

lineage-specific

ones

-LRB-

Fig.

-RRB-

Although

these

data

can

not

confirm

the

detailed

structure

of

gene

models

they

do

suggest

that

the

majority

of

GLEAN-R

models

contain

sequence

that

is

part

of

a

poly-adenylated

transcript

Approximately

of

transcription

in

D.

melanogaster

seems

to

be

unassociated

with

protein-coding

and

our

microarray

experiments

fail

to

detect

conditionally

expressed

genes

Thus

D.

melanogaster

D.

simulans

D.

sechellia

D.

yakuba

D.

erecta

D.

ananassae

D.

pseudoobscura

D.

persimilis

D.

willistoni

D.

virilis

D.

mojavensis

D.

grimshawi

Single-copy

orthologues

transcript

abundance

can

not

conclusively

establish

the

presence

or

absence

of

a

protein-coding

gene

Nonetheless

we

believe

these

expression

data

increase

our

confidence

in

the

reliability

of

the

GLEAN-R

models

particularly

those

supported

by

homology

evidence

-LRB-

Fig.

-RRB-

Because

the

GLEAN-R

gene

models

were

built

using

assemblies

that

were

not

repeat

masked

it

is

likely

that

some

proportion

of

gene

models

are

false

positives

corresponding

to

coding

sequences

of

transposable

elements

We

used

RepeatMasker

with

de

novo

ReAS

libraries

and

PFAM

structural

annotations

of

the

GLEAN-R

gene

set

to

flag

potentially

transposable

element-contaminated

gene

models

-LRB-

Supplementary

Information

section

-RRB-

These

procedures

suggest

that

of

gene

models

in

non-melanogaster

species

correspond

to

protein-coding

content

derived

from

transposable

elements

-LRB-

Supplementary

Table

-RRB-

these

transposable

element-contaminated

gene

models

are

almost

exclusively

confined

to

gene

predictions

without

strong

homology

support

-LRB-

Fig.

-RRB-

Transposable

elementcontaminated

gene

models

are

excluded

from

the

final

gene

prediction

set

used

for

subsequent

analysis

unless

otherwise

noted

Homology

assignment

Two

independent

approaches

were

used

to

assign

orthology

and

paralogy

relationships

among

euchromatic

D.

melanogaster

gene

models

and

GLEAN-R

predictions

The

first

approach

was

a

fuzzy

reciprocal

BLAST

-LRB-

FRB

-RRB-

algorithm

which

is

an

Expressed

no

transposable

element

contamination

Expressed

possible

transposable

element

contamination

Expression

not

detected

no

transposable

element

contamination

Expression

not

detected

possible

transposable

element

contamination

Number

of

gene

models

Lineage

specific

Conserved

homologues

Patchy

homologues

-LRB-

with

mel

-RRB-

Patchy

homologues

-LRB-

no

mel

-RRB-

Figure

Gene

models

in

Drosophila

genomes

Number

of

gene

models

that

fall

into

one

of

five

homology

classes

single-copy

orthologues

in

all

species

-LRB-

single-copy

orthologues

-RRB-

conserved

in

all

species

as

orthologues

or

paralogues

-LRB-

conserved

homologues

-RRB-

a

D.

melanogaster

homologue

but

not

found

in

all

species

-LRB-

patchy

homologues

with

mel

-RRB-

conserved

in

at

least

two

species

but

without

a

D.

melanogaster

homologue

-LRB-

patchy

homologues

no

mel

-RRB-

and

found

only

in

a

single

lineage

-LRB-

lineage

specific

-RRB-

For

those

species

with

expression

pie

charts

indicate

the

fraction

of

genes

in

each

homology

class

that

fall

into

one

of

four

evidence

classes

-LRB-

see

text

for

details

-RRB-

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

extension

of

the

reciprocal

BLAST

applicable

to

multiple

species

simultaneously

-LRB-

Supplementary

Information

section

-RRB-

Because

the

FRB

algorithm

does

not

integrate

syntenic

information

we

also

used

a

second

approach

based

on

Synpipe

-LRB-

Supplementary

Information

section

-RRB-

a

tool

for

synteny-aided

orthology

To

generate

a

reconciled

set

of

homology

calls

pairwise

Synpipe

calls

-LRB-

between

each

species

and

D.

melanogaster

-RRB-

were

mapped

to

GLEAN-R

models

filtered

to

retain

only

relationships

and

added

to

the

FRB

calls

when

they

did

not

conflict

and

were

non-redundant

This

reconciled

FRB

Synpipe

set

of

homology

calls

forms

the

basis

of

our

subsequent

analyses

There

were

genes

with

single-copy

orthologues

in

the

melanogaster

group

and

genes

with

single-copy

orthologues

in

all

species

similar

numbers

of

genes

were

also

obtained

with

an

independent

Most

single-copy

orthologues

are

expressed

and

are

free

from

potential

transposable

element

contamination

suggesting

that

the

reconciled

orthologue

set

contains

robust

and

high-quality

gene

models

-LRB-

Fig.

-RRB-

Validation

of

homology

calls

Because

both

the

FRB

algorithm

and

Synpipe

rely

on

BLAST-based

methods

to

infer

similarities

rapidly

evolving

genes

may

be

overlooked

Moreover

assembly

gaps

and

poor-quality

sequence

may

lead

to

erroneous

inferences

of

gene

loss

To

validate

putative

gene

absences

we

used

a

synteny-based

GeneWise

pipeline

to

find

potentially

missed

homologues

of

D.

melanogaster

proteins

-LRB-

Supplementary

Information

section

-RRB-

Of

the

cases

in

which

a

D.

melanogaster

gene

was

absent

from

another

species

in

the

initial

homology

call

set

we

identified

plausible

homologues

for

-LRB-

-RRB-

confirmed

-LRB-

-RRB-

as

genuine

absences

and

were

unable

to

resolve

-LRB-

-RRB-

Because

this

approach

is

conservative

and

only

confirms

strongly

supported

absences

we

are

probably

underestimating

the

number

of

genuine

absences

Coding

gene

alignment

and

filtering

Investigating

the

molecular

evolution

of

orthologous

and

paralogous

genes

requires

accurate

multi-species

alignments

Initial

amino

acid

alignments

were

generated

using

and

converted

to

nucleotide

alignments

-LRB-

Supplementary

Table

-RRB-

To

reduce

biases

in

downstream

analyses

a

simple

computational

screen

was

developed

to

identify

and

mask

problematic

regions

of

each

alignment

-LRB-

Supplementary

Information

section

-RRB-

Overall

of

bases

were

masked

in

the

melanogaster

group

alignments

and

of

bases

were

masked

in

the

full

species

alignments

representing

and

of

alignment

columns

respectively

The

vast

majority

of

masked

bases

are

masked

in

no

more

than

one

species

-LRB-

Supplementary

Fig.

-RRB-

suggesting

that

the

masking

procedure

is

not

simply

eliminating

rapidly

evolving

regions

of

the

genome

We

find

an

appreciably

higher

frequency

of

masked

bases

in

lower-quality

D.

simulans

and

D.

sechellia

assemblies

compared

to

the

more

divergent

-LRB-

from

D.

melanogaster

-RRB-

but

higherquality

D.

erecta

and

D.

yakuba

assemblies

suggesting

a

higher

error

rate

in

accurately

predicting

and

aligning

gene

models

in

lowerquality

assemblies

-LRB-

Supplementary

Information

section

and

Supplementary

Fig.

-RRB-

We

used

masked

versions

of

the

alignments

including

only

the

longest

D.

melanogaster

transcripts

for

all

subsequent

analysis

unless

otherwise

noted

Annotation

of

non-coding

-LRB-

nc

-RRB-

RNA

genes

Using

de

novo

and

homology-based

approaches

we

annotated

over

ncRNA

genes

from

recognized

ncRNA

classes

-LRB-

Table

and

Supplementary

Information

section

-RRB-

In

contrast

to

the

large

number

of

predictions

observed

for

many

ncRNA

families

in

vertebrates

-LRB-

due

in

part

to

large

numbers

of

ncRNA

-RRB-

the

number

of

ncRNA

genes

per

family

predicted

by

RFAM

and

tRNAscan

in

Drosophila

is

relatively

low

-LRB-

Table

-RRB-

This

suggests

that

ncRNA

pseudogenes

are

largely

absent

from

Drosophila

genomes

which

is

consistent

with

the

low

number

of

protein-coding

pseudogenes

in

The

relatively

low

numbers

of

some

classes

of

ncRNA

genes

-LRB-

for

example

small

nucleolar

-LRB-

sno

-RRB-

RNAs

-RRB-

in

the

Drosophila

subgenus

are

likely

to

be

an

artefact

of

rapid

rates

of

evolution

in

these

types

of

genes

and

the

limitation

of

the

homology-based

methods

used

to

annotate

distantly

related

species

Evolution

of

genome

structure

Coarse-level

similarities

among

Drosophilids

At

a

coarse

level

genome

structure

is

well

conserved

across

the

sequenced

species

Total

genome

size

estimated

by

flow

cytometry

varies

less

than

threefold

across

the

phylogeny

ranging

from

Mb

-LRB-

D.

mojavensis

-RRB-

to

Mb

-LRB-

D.

virilis

-RRB-

-LRB-

Table

-RRB-

in

contrast

to

the

order

of

magnitude

difference

between

Drosophila

and

mammals

Total

protein-coding

sequence

ranges

from

Mb

in

D.

melanogaster

to

Mb

in

D.

willistoni

Intronic

DNA

content

is

also

largely

conserved

ranging

from

Mb

in

D.

simulans

to

Mb

in

D.

pseudoobscura

-LRB-

Table

-RRB-

This

contrasts

dramatically

with

transposable

elementderived

genomic

DNA

content

which

varies

considerably

across

genomes

-LRB-

Table

-RRB-

and

correlates

significantly

with

euchromatic

genome

size

-LRB-

estimated

as

the

summed

length

of

contigs

kb

-RRB-

-LRB-

Kendall

's

t

P

-RRB-

To

investigate

overall

conservation

of

genome

architecture

at

an

intermediate

scale

we

analysed

synteny

relationships

across

species

using

-LRB-

Supplementary

Information

section

-RRB-

Synteny

block

size

and

average

number

of

genes

per

block

varies

across

the

phylogeny

as

expected

with

the

number

of

blocks

increasing

and

the

average

size

of

blocks

decreasing

with

increasing

evolutionary

distance

from

D.

melanogaster

-LRB-

A.

Bhutkar

S.

Russo

T.

F.

Smith

and

W.

M.

Gelbart

personal

communication

-RRB-

-LRB-

Supplementary

Fig.

-RRB-

We

inferred

syntenic

blocks

between

D.

melanogaster

and

D.

sechellia

-LRB-

with

an

average

of

genes

per

block

-RRB-

compared

to

syntenic

blocks

between

D.

melanogaster

and

D.

grimshawi

-LRB-

with

an

average

of

genes

per

block

-RRB-

On

average

of

each

genome

assembly

was

covered

by

syntenic

blocks

ranging

from

in

D.

sechellia

to

in

D.

grimshawi

Similarity

across

genomes

is

largely

recapitulated

at

the

level

of

individual

genes

with

roughly

comparable

numbers

of

predicted

protein-coding

genes

across

the

species

-LRB-

Table

-RRB-

The

majority

of

predicted

genes

in

each

species

have

homologues

in

D.

melanogaster

-LRB-

Table

Supplementary

Table

-RRB-

Moreover

most

of

the

protein-coding

genes

in

D.

melanogaster

are

conserved

across

the

entire

phylogeny

have

identifiable

homologues

in

all

genomes

can

be

identified

as

single-copy

orthologues

in

the

six

genomes

of

the

melanogaster

group

and

can

be

identified

as

single-copy

orthologues

in

all

genomes

The

number

of

functional

non-coding

RNA

genes

predicted

in

each

Drosophila

genome

is

also

largely

conserved

ranging

from

in

D.

mojavensis

to

in

D.

ananassae

-LRB-

Table

-RRB-

There

are

several

possible

explanations

for

the

observed

interspecific

variation

in

gene

content

First

approximately

D.

melanogaster

gene

models

have

been

newly

annotated

since

the

FlyBase

Release

annotations

used

in

the

current

study

reducing

the

discrepancy

between

D.

melanogaster

and

the

other

sequenced

genomes

in

this

study

Second

because

low-coverage

genomes

tend

to

have

more

predicted

gene

models

we

suspect

that

artefactual

duplication

of

genomic

segments

due

to

assembly

errors

inflates

the

number

of

predicted

genes

in

some

species

Finally

the

non-melanogaster

species

have

many

more

predicted

lineage-specific

genes

than

D.

melanogaster

and

it

is

possible

that

some

of

these

are

artefactual

In

the

absence

of

experimental

evidence

it

is

difficult

to

distinguish

genuine

lineage-specific

genes

from

putative

artefacts

Future

experimental

work

will

be

required

to

fully

disentangle

the

causes

of

interspecific

variation

in

gene

number

Abundant

genome

rearrangements

during

Drosophila

evolution

To

study

the

structural

relationships

among

genomes

on

a

finer

scale

we

analysed

gene-level

synteny

between

species

pairs

These

synteny

maps

allowed

us

to

infer

the

history

and

locations

of

fixed

genomic

rearrangements

between

species

Although

Drosophila

species

vary

in

their

number

of

chromosomes

there

are

six

fundamental

chromosome

arms

common

to

all

species

For

ease

of

denoting

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

chromosomal

homology

these

six

arms

are

referred

to

as

Muller

elements

after

Hermann

J.

Muller

and

are

denoted

A

F.

Although

most

pairs

of

orthologous

genes

are

found

on

the

same

Muller

element

there

is

extensive

gene

shuffling

within

Muller

elements

between

even

moderately

diverged

genomes

-LRB-

Fig.

and

Supplementary

Information

section

-RRB-

Previous

analysis

has

revealed

heterogeneity

in

rearrangement

rates

among

close

relatives

careful

inspection

of

inversions

that

differentiate

the

chromosomes

of

D.

melanogaster

and

D.

yakuba

revealed

that

were

fixed

in

the

lineage

leading

to

D.

yakuba

and

only

one

was

fixed

on

the

lineage

leading

to

D.

Rearrangement

rates

are

also

heterogeneous

across

the

genome

among

the

species

simulations

reject

a

random-breakage

model

which

assumes

that

all

sites

are

free

to

break

in

inversion

events

but

fail

to

reject

a

model

of

coldspots

and

hotspots

for

breakpoints

-LRB-

S.

Schaeffer

personal

communication

-RRB-

Furthermore

inversions

seem

to

have

played

important

roles

in

the

process

of

speciation

in

at

least

some

of

these

One

particularly

striking

example

of

the

dynamic

nature

of

genome

micro-structure

in

Drosophila

is

the

homeotic

homeobox

-LRB-

Hox

-RRB-

gene

cluster

-LRB-

s

-RRB-

Hox

genes

typically

occur

in

genomic

clusters

and

this

clustering

is

conserved

across

many

vertebrate

and

invertebrate

taxa

suggesting

a

functional

role

for

the

precise

and

collinear

arrangement

of

these

genes

However

several

cluster

splits

have

been

previously

identified

in

and

the

Drosophila

genome

sequences

provide

additional

evidence

against

the

functional

importance

of

Hox

gene

clustering

in

Drosophila

There

are

seven

different

gene

arrangements

found

across

Drosophila

species

-LRB-

the

sequenced

genomes

and

D.

buzzatii

-RRB-

with

no

species

retaining

the

inferred

ancestral

gene

It

thus

seems

that

in

Drosophila

Hox

genes

do

not

require

clustering

to

maintain

proper

function

and

are

a

powerful

illustration

of

the

dynamism

of

genome

structure

across

the

sequenced

genomes

Transposable

element

evolution

Mobile

repetitive

transposable

element

sequences

are

a

particularly

dynamic

component

of

eukaryotic

genomes

Transposable

element/repeat

content

-LRB-

in

scaffolds

kb

-RRB-

varies

by

over

an

order

of

magnitude

across

the

genus

ranging

from

in

D.

simulans

and

D.

grimshawi

to

in

D.

ananassae

-LRB-

Table

and

Supplementary

Fig.

-RRB-

These

data

support

the

lower

euchromatic

transposable

element

content

in

D.

simulans

relative

to

D.

and

reveal

that

euchromatic

transposable

element/repeat

content

is

generally

similar

within

the

melanogaster

subgroup

Within

the

Drosophila

subgenus

a

D.

simulans

Muller

B

Muller

C

D.

grimshawi

has

the

lowest

transposable

element/repeat

content

possibly

relating

to

its

ecological

status

as

an

island

endemic

which

may

minimize

the

chance

for

horizontal

transfer

of

transposable

element

families

Finally

the

highest

levels

of

transposable

element

repeat

content

are

found

in

D.

ananassae

and

D.

willistoni

These

species

also

have

the

highest

numbers

of

pseudo-transfer

-LRB-

t

-RRB-

RNA

genes

-LRB-

Table

-RRB-

indicating

a

potential

relationship

between

pseudo-tRNA

genesis

and

repetitive

DNA

as

has

been

established

in

the

mouse

Different

classes

of

transposable

elements

can

vary

in

abundance

owing

to

a

variety

of

host

factors

motivating

an

analysis

of

the

intragenomic

ecology

of

transposable

elements

in

the

genomes

In

D.

melanogaster

long

terminal

repeat

-LRB-

LTR

-RRB-

retrotransposons

have

the

highest

abundance

followed

by

LINE

-LRB-

long

interspersed

nuclear

element

-RRB-

like

retrotransposons

and

terminal

inverted

repeat

-LRB-

TIR

-RRB-

DNA-based

An

unbiased

conservative

approach

-LRB-

Supplementary

Information

section

-RRB-

for

estimating

the

rank

order

abundance

of

major

transposable

element

classes

suggests

that

these

abundance

trends

are

conserved

across

the

entire

genus

-LRB-

Supplementary

Fig.

-RRB-

Two

exceptions

are

an

increased

abundance

of

TIR

elements

in

D.

erecta

and

a

decreased

abundance

of

LTR

elements

in

D.

pseudoobscura

the

latter

observation

may

represent

an

assembly

artefact

because

the

sister

species

D.

persimilis

shows

typical

LTR

abundance

Given

that

individual

instances

of

transposable

element

repeats

and

transposable

element

families

themselves

are

not

conserved

across

the

genus

the

stability

of

abundance

trends

for

different

classes

of

transposable

elements

is

striking

and

suggests

common

mechanisms

for

host

transposable

element

co-evolution

in

Drosophila

Although

comprehensive

analysis

of

the

structural

and

evolutionary

relationships

among

families

of

transposable

elements

in

the

genomes

remains

a

major

challenge

for

Drosophila

genomics

some

initial

insights

can

be

gleaned

from

analysis

of

particularly

wellcharacterized

transposable

element

families

Previous

analysis

has

shown

variable

dynamics

for

the

most

abundant

transposable

element

family

-LRB-

-RRB-

in

the

D.

melanogaster

although

inactive

in

D.

has

experienced

a

recent

transpositional

burst

in

D.

Our

analysis

confirms

that

this

element

is

highly

abundant

in

all

of

the

other

sequenced

genomes

of

Drosophila

but

is

not

found

outside

of

Moreover

the

inferred

phylogenetic

relationship

of

paralogues

from

several

Drosophila

species

suggests

vertical

transmission

as

the

major

mechanism

for

propagation

Likewise

analysis

of

the

Galileo

Muller

C

b

D.

yakuba

Muller

B

c

Muller

B

Muller

C

D.

melanogaster

D.

melanogaster

D.

erecta

D.

melanogaster

d

D.

ananassae

Muller

B

Muller

C

e

D.

willstoni

Muller

B

Muller

C

f

Muller

B

Muller

C

D.

melanogaster

D.

melanogaster

D.

virilis

D.

melanogaster

Figure

Synteny

plots

for

Muller

elements

B

and

C

with

respect

to

D.

melanogaster

gene

order

The

horizontal

axis

shows

D.

melanogaster

gene

order

for

Muller

elements

B

and

C

and

the

vertical

axis

maps

homologous

in

individual

species

-LRB-

a

f

in

increasing

evolutionary

distance

from

D.

melanogaster

-RRB-

Left

to

right

on

the

x

axis

is

from

telomere

to

centromere

for

Muller

element

B

followed

by

Muller

element

C

from

centromere

to

telomere

Red

and

green

lines

represent

syntenic

segments

in

the

same

or

reverse

orientation

along

the

chromosome

relative

to

D.

melanogaster

respectively

Blue

segments

show

gene

transposition

of

genes

from

one

element

to

the

other

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

and

transposons

reveals

a

widespread

but

discontinuous

phylogenetic

distribution

for

both

families

notably

with

both

families

absent

in

the

geographically

isolated

Hawaiian

species

D.

These

results

are

consistent

with

an

ancient

origin

of

the

Galileo

and

families

in

the

genus

and

subsequent

horizontal

transfer

and/or

loss

in

some

lineages

The

use

of

these

genomes

also

facilitated

the

discovery

of

transposable

element

lineages

not

yet

documented

in

Drosophila

specifically

the

P

instability

factor

-LRB-

PIF

-RRB-

superfamily

of

DNA

transposons

Our

analysis

indicates

that

there

are

four

distinct

lineages

of

this

transposon

in

Drosophila

and

that

this

element

has

indeed

colonized

many

of

the

sequenced

This

superfamily

is

particularly

intriguing

given

that

PIF-transposase-like

genes

have

been

implicated

in

the

origin

of

at

least

seven

different

genes

during

the

Drosophila

suggesting

that

not

only

do

transposable

elements

affect

the

evolution

of

genome

structure

but

that

their

domestication

can

play

a

part

in

the

emergence

of

novel

genes

D.

melanogaster

maintains

its

telomeres

by

occasional

targeted

transposition

of

three

telomere-specific

non-LTR

retrotransposons

-LRB-

HeT-A

TART

and

TAHRE

-RRB-

to

chromosome

and

not

by

the

more

common

mechanism

of

telomerase-generated

G-rich

Multiple

telomeric

retrotransposons

have

originated

within

the

genus

where

they

now

maintain

telomeres

and

recurrent

loss

of

most

of

the

from

telomeric

retrotransposons

-LRB-

for

example

TAHRE

-RRB-

has

given

rise

to

half-telomeric-retrotransposons

-LRB-

for

example

HeT-A

-RRB-

during

Drosophila

The

phylogenetic

relationship

among

these

telomeric

elements

is

congruent

with

the

species

phylogeny

suggesting

that

they

have

been

vertically

transmitted

from

a

common

ncRNA

gene

family

evolution

Using

ncRNA

gene

annotations

across

the

phylogeny

we

inferred

patterns

of

gene

copy

number

evolution

in

several

ncRNA

families

Transfer

RNA

genes

are

the

most

abundant

family

of

ncRNA

genes

in

all

genomes

with

tRNAs

in

D.

melanogaster

and

tRNA

genes

in

the

other

species

-LRB-

Table

-RRB-

Each

genome

encodes

a

single

selenocysteine

tRNA

with

the

exception

of

D.

willistoni

which

seems

to

lack

this

gene

-LRB-

R.

Guigo

personal

communication

-RRB-

Elevated

tRNA

gene

counts

in

D.

ananassae

and

D.

willistoni

are

explained

almost

entirely

by

pseudo-tRNA

gene

predictions

We

infer

from

the

lack

of

pseudotRNAs

in

most

Drosophila

species

and

from

similar

numbers

of

tRNAs

obtained

from

an

analysis

of

the

chicken

genome

-LRB-

n

-RRB-

that

the

minimal

metazoan

tRNA

set

is

encoded

by

genes

in

contrast

to

previous

estimates

of

in

human

and

in

Caenorhabditis

Similar

numbers

of

snoRNAs

are

predicted

in

the

D.

melanogaster

subgroup

-LRB-

n

-RRB-

in

which

sequence

similarity

is

high

enough

for

annotation

by

homology

with

fewer

snoRNAs

-LRB-

n

-RRB-

annotated

in

more

distant

members

of

the

Sophophora

subgenus

and

even

fewer

snoRNAs

-LRB-

n

-RRB-

predicted

in

the

Drosophila

subgenus

in

which

annotation

by

homology

becomes

much

more

difficult

Of

previously

reported

micro

-LRB-

mi

-RRB-

RNA

genes

-LRB-

-RRB-

are

highly

conserved

across

the

entire

genus

with

the

remaining

seven

genes

-LRB-

and

-RRB-

restricted

to

the

subgenus

Sophophora

-LRB-

Supplementary

Information

section

-RRB-

All

the

species

contain

similar

numbers

of

spliceosomal

snRNA

genes

-LRB-

Table

-RRB-

including

at

least

one

copy

each

of

the

four

-LRB-

minor

-RRB-

spliceosomal

RNAs

despite

evidence

for

birth

and

death

of

these

genes

and

the

absence

of

stable

The

unusual

lineage-specific

expansion

in

size

of

snRNA

previously

described

in

is

even

more

extreme

in

D.

willistoni

We

annotated

copies

of

the

ribosomal

-LRB-

r

-RRB-

RNA

gene

in

a

cluster

in

D.

melanogaster

and

between

and

partial

rRNA

genes

in

clusters

in

the

other

genomes

Finally

we

identified

members

of

several

other

classes

of

ncRNA

genes

including

the

RNA

components

of

the

RNase

P

-LRB-

per

genome

-RRB-

and

the

signal

recognition

particle

-LRB-

SRP

-RRB-

RNA

complexes

-LRB-

per

genome

-RRB-

suggesting

that

these

functional

RNAs

are

involved

in

similar

biological

processes

throughout

the

genus

We

were

only

able

to

locate

the

roX

-LRB-

RNA

on

X

-RRB-

genes

involved

in

dosage

compensation

using

nucleotide

homology

in

the

melanogaster

subgroup

although

analyses

incorporating

structural

information

have

identified

roX

genes

in

other

members

of

the

We

investigated

the

evolution

of

rRNA

genes

in

the

sequenced

genomes

using

trace

archives

to

locate

sequence

variants

within

the

transcribed

portions

of

these

genes

This

analysis

revealed

moderate

levels

of

variation

that

are

not

distributed

evenly

across

the

rRNA

genes

with

fewest

variants

in

conserved

core

coding

regions

more

variants

in

coding

expansion

regions

and

higher

still

variant

abundances

in

non-coding

regions

The

level

and

distribution

of

sequence

variation

in

rRNA

genes

are

suggestive

of

concerted

evolution

in

which

recombination

events

uniformly

distribute

variants

throughout

the

rDNA

loci

and

selection

dictates

the

frequency

to

which

variants

can

Protein-coding

gene

family

evolution

For

a

general

perspective

on

how

the

protein-coding

composition

of

these

genomes

has

changed

we

examined

gene

family

expansions

and

contractions

in

the

gene

families

-LRB-

including

those

of

size

one

in

each

species

-RRB-

predicted

to

be

present

in

the

most

recent

common

ancestor

of

the

two

subgenera

We

applied

a

maximum

likelihood

model

of

gene

gain

and

to

estimate

rates

of

gene

turnover

This

analysis

suggests

that

gene

families

expand

or

contract

at

a

rate

of

gains

and

losses

per

gene

per

million

years

or

roughly

one

fixed

gene

gain

loss

across

the

genome

every

Many

gene

families

-LRB-

or

-RRB-

changed

in

size

in

at

least

one

species

and

families

showed

significantly

elevated

-LRB-

P

-RRB-

rates

of

gene

gain

and

loss

compared

to

the

genomic

average

indicating

that

non-neutral

processes

may

play

a

part

in

gene

family

evolution

Twenty-two

families

exhibit

rapid

copy

number

evolution

along

the

branch

leading

to

D.

melanogaster

-LRB-

eighteen

contractions

and

four

expansions

Supplementary

Table

-RRB-

The

most

common

Gene

Ontology

-LRB-

GO

-RRB-

terms

among

families

with

elevated

rates

of

gain/loss

include

defence

response

protein

binding

zinc

ion

binding

proteolysis

and

trypsin

activity

Interestingly

genes

involved

in

defence

response

and

proteolysis

also

show

high

rates

of

protein

evolution

-LRB-

see

below

-RRB-

We

also

found

heterogeneity

in

overall

rates

of

gene

gain

and

loss

across

lineages

although

much

of

this

variation

could

result

from

interspecific

differences

in

assembly

Lineage-specific

genes

The

vast

majority

of

D.

melanogaster

proteins

that

can

be

unambiguously

assigned

a

homology

pattern

-LRB-

Supplementary

Information

section

-RRB-

are

inferred

to

be

ancestrally

present

at

the

genus

root

-LRB-

or

-RRB-

Of

the

nonancestrally

present

genes

are

either

Sophophora-specific

or

have

a

complicated

pattern

of

homology

requiring

more

than

one

gain

and/or

loss

on

the

phylogeny

and

are

not

discussed

further

The

remaining

proteins

include

present

in

the

melanogaster

group

present

only

in

the

melanogaster

subgroup

unique

to

the

melanogaster

species

complex

and

found

in

D.

melanogaster

only

Because

we

restricted

this

analysis

to

unambiguous

homologues

of

high-confidence

protein-coding

genes

in

D.

we

are

probably

undercounting

the

number

of

genes

that

have

arisen

de

novo

in

any

particular

lineage

However

ancestrally

heterochromatic

genes

that

are

currently

euchromatic

in

D.

melanogaster

may

spuriously

seem

to

be

lineage-specific

The

lineage-specific

genes

-LRB-

Supplementary

Table

-RRB-

differ

from

ancestrally

present

genes

in

several

ways

They

have

a

shorter

median

predicted

protein

length

-LRB-

lineage-specific

median

amino

acids

other

median

amino

acids

MWU

P

-RRB-

are

more

likely

to

be

intronless

-LRB-

Fisher

's

exact

test

-LRB-

FET

-RRB-

P

-RRB-

and

are

more

likely

to

be

located

in

the

intron

of

another

gene

on

the

opposite

strand

-LRB-

FET

P

-RRB-

In

addition

of

these

genes

are

testis

or

accessory-gland-specific

in

D.

melanogaster

a

significantly

greater

fraction

than

is

found

in

the

ancestral

set

-LRB-

FET

P

-RRB-

This

is

consistent

with

previous

observations

that

novel

genes

are

often

testis-specific

in

and

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

expression

studies

on

seven

of

the

species

show

that

species-restricted

genes

are

more

likely

to

exhibit

male-biased

Further

these

genes

are

significantly

more

tissue-specific

in

expression

-LRB-

as

measured

by

t

ref

-RRB-

-LRB-

MWU

P

-RRB-

and

this

pattern

is

not

solely

driven

by

genes

with

testis-specific

expression

patterns

Protein-coding

gene

evolution

Positive

selection

and

selective

constraints

in

Drosophila

genomes

To

study

the

molecular

evolution

of

protein-coding

genes

we

estimated

rates

of

synonymous

and

non-synonymous

substitution

in

single-copy

orthologues

within

the

six

melanogaster

group

species

using

-LRB-

Supplementary

Information

section

-RRB-

synonymous

site

saturation

prevents

analysis

of

more

divergent

comparisons

We

investigate

only

single-copy

orthologues

because

when

paralogues

are

included

alignments

become

increasingly

problematic

Rates

of

amino

acid

divergence

for

single-copy

orthologues

in

all

species

were

also

calculated

these

results

are

largely

consistent

with

the

analysis

of

non-synonymous

divergence

in

the

melanogaster

group

and

are

not

discussed

further

To

understand

global

patterns

of

divergence

and

constraint

across

functional

classes

of

genes

we

examined

the

distributions

of

v

-LRB-

the

ratio

of

non-synonymous

to

synonymous

divergence

-RRB-

across

Gene

Ontology

categories

-LRB-

GO

-RRB-

excluding

GO

a

Biological

process

Unknown

Defence

response

Other

biological

process

Proteolysis

DNA

metabolic

process

Cell

cycle

Regulation

of

metabolic

process

Regulation

of

cellular

process

Transcription

Adult

reproduction

and

gametogenesis

Organ

development

Cell

differentiation

Signal

transduction

Embryonic

development

Nucleic

acid

metabolism

Other

anatomical

structure

development

Post-embryonic

development

Lipid

metabolic

process

Pattern

specification

process

Other

cellular

process

Nervous

system

development

Cell

morphogenesis

Protein

modification

Regulation

of

other

biological

process

Phosphorylation

Cell

organization

and

biogenesis

RNA

metabolic

process

Catabolic

process

Ion

transport

Protein

metabolic

process

Protein

transport

Carbohydrate

metabolic

process

Generation

of

precursor

metabolites

and

energy

Cellular

localization

Transport

Biosynthetic

process

Amino

acid

and

derivative

metabolic

process

Translation

Cell

cell

signalling

Vesicle-mediated

transport

annotations

based

solely

on

electronic

support

-LRB-

Supplementary

Information

section

-RRB-

Most

functional

categories

of

genes

are

strongly

constrained

with

median

estimates

of

v

much

less

than

one

In

general

functionally

similar

genes

are

similarly

constrained

of

GO

categories

have

significantly

lower

variance

in

v

than

expected

-LRB-

q-value

true-positive

-RRB-

Only

of

GO

categories

had

statistically

significantly

elevated

v

-LRB-

relative

to

the

median

of

all

genes

with

GO

annotations

-RRB-

at

a

false-discovery

rate

-LRB-

FDR

-RRB-

suggesting

either

positive

selection

or

a

reduction

in

selective

constraint

The

GO

categories

with

elevated

v

include

the

biological

process

terms

defence

response

proteolysis

DNA

metabolic

process

and

response

to

biotic

stimulus

the

molecular

function

terms

transcription

factor

activity

peptidase

activity

receptor

binding

odorant

binding

DNA

binding

receptor

activity

and

G-protein-coupled

receptor

activity

and

the

cellular

location

term

extracellular

-LRB-

Fig.

and

Supplementary

Table

-RRB-

Similar

results

are

obtained

when

dN

is

compared

across

GO

categories

suggesting

that

in

most

cases

differences

in

v

among

GO

categories

is

driven

by

amino

acid

rather

than

synonymous

site

substitutions

The

two

exceptions

are

the

molecular

function

terms

transcription

factor

activity

and

DNA

binding

activity

for

which

we

observe

significantly

decelerated

dS

-LRB-

FDR

for

both

Supplementary

Information

section

-RRB-

and

no

significant

differences

in

dN

b

log

-LRB-

probability

of

positive

selection

-RRB-

Cellular

component

Unknown

Extracellular

Nucleus

Mitochondrion

Cell

log

-LRB-

probability

of

positive

selection

-RRB-

Plasma

membrane

Intracellular

Non-nuclear

membrane-bound

organelle

Cytoplasm

Protein

complex

c

Molecular

function

Unknown

Transcription

factor

activity

Receptor

activity

Peptidase

activity

DNA

binding

Transcription

regulator

activity

Nucleic

acid

binding

Hydrolase

activity

Enzyme

regulator

activity

Transporter

activity

Other

binding

Oxidoreductase

activity

Transferase

activity

Protein

binding

Protein

kinase

activity

RNA

binding

Structural

molecule

activity

Ion

binding

Nucleotide

binding

log

-LRB-

probability

of

positive

selection

-RRB-

log

-LRB-

probability

of

positive

selection

-RRB-

Figure

Patterns

of

constraint

and

positive

selection

among

GO

terms

Distribution

of

average

v

per

gene

and

the

negative

of

the

probability

of

positive

selection

-LRB-

Supplementary

Information

section

-RRB-

for

genes

annotated

with

a

biological

process

GO

terms

b

cellular

component

GO

terms

and

c

molecular

function

GO

terms

Only

GO

terms

with

or

more

genes

annotated

are

plotted

See

Supplementary

Table

for

median

values

and

significance

Note

that

most

genes

evolve

under

evolutionary

constraint

at

most

of

their

sites

leading

to

low

values

of

v

even

genes

that

experience

positive

selection

do

not

typically

have

an

average

v

across

all

codons

that

exceeds

one

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

To

distinguish

possible

positive

selection

from

relaxed

constraint

we

tested

explicitly

for

genes

that

have

a

subset

of

codons

with

signatures

of

positive

selection

using

codon-based

likelihood

models

of

molecular

evolution

implemented

in

-LRB-

Supplementary

Information

section

-RRB-

Although

this

test

is

typically

regarded

as

a

conservative

test

for

positive

selection

it

may

be

confounded

by

selection

at

synonymous

sites

However

selection

at

synonymous

sites

-LRB-

that

is

codon

bias

see

below

-RRB-

is

quite

weak

Moreover

variability

in

v

presented

here

tends

to

reflect

variability

in

dN

We

therefore

believe

that

it

is

appropriate

to

treat

synonymous

sites

as

nearly

neutral

and

sites

with

v

as

consistent

with

positive

selection

Despite

a

number

of

functional

categories

with

evidence

for

elevated

v

helicase

activity

is

the

only

functional

category

significantly

more

likely

to

be

positively

selected

-LRB-

permutation

test

P

FDR

Supplementary

Table

-RRB-

the

biological

significance

of

this

finding

merits

further

investigation

Furthermore

within

each

GO

class

there

is

greater

dispersion

among

genes

in

their

probability

of

positive

selection

than

in

their

estimate

of

v

-LRB-

MWU

one-tailed

P

Supplementary

Information

section

-RRB-

suggesting

that

although

functionally

similar

genes

share

patterns

of

constraint

they

do

not

necessarily

show

similar

patterns

of

positive

selection

-LRB-

Fig.

-RRB-

Interestingly

protein-coding

genes

with

no

annotated

-LRB-

unknown

-RRB-

function

in

the

GO

database

seem

to

be

less

constrained

-LRB-

permutation

test

P

FDR

-RRB-

and

to

have

on

average

lower

P-values

for

the

test

of

positive

selection

than

genes

with

annotated

functions

-LRB-

permutation

test

P

FDR

-RRB-

It

is

unlikely

that

this

observation

results

entirely

from

an

over-representation

of

mis-annotated

or

non-protein-coding

genes

in

the

unknown

functional

class

because

this

finding

is

robust

to

the

removal

of

all

D.

melanogaster

genes

predicted

to

be

non-proteincoding

in

ref

The

bias

in

the

way

biological

function

is

ascribed

to

genes

-LRB-

to

laboratory-induced

easily

scorable

functions

-RRB-

leaves

open

the

possibility

that

unannotated

biological

functions

may

have

an

important

role

in

evolution

Indeed

genes

with

characterized

mutant

alleles

in

FlyBase

evolve

significantly

more

slowly

than

other

genes

-LRB-

median

vwith

alleles

and

vwithout

alleles

MWU

P

-RRB-

Previous

work

has

suggested

that

a

substantial

fraction

of

nonsynonymous

substitutions

in

Drosophila

were

fixed

through

positive

We

estimate

that

of

single-copy

orthologues

in

the

melanogaster

group

have

experienced

positive

selection

on

at

least

a

subset

of

codons

-LRB-

q-value

true-positive

-RRB-

-LRB-

Supplementary

Information

section

-RRB-

This

may

be

an

underestimate

because

we

have

only

examined

single-copy

orthologues

owing

to

difficulties

in

producing

accurate

alignments

of

paralogues

by

automated

methods

On

the

basis

of

the

genes

inferred

to

have

experienced

positive

selection

with

high

confidence

-LRB-

FDR

-RRB-

we

estimated

that

an

average

of

of

codons

in

positively

selected

genes

have

v

Thus

several

lines

of

evidence

based

on

different

methodologies

suggest

that

patterns

of

amino

acid

fixation

in

Drosophila

genomes

have

been

shaped

extensively

by

positive

selection

The

presence

of

functional

domains

within

a

protein

may

lead

to

heterogeneity

in

patterns

of

constraint

and

adaptation

along

its

length

Among

genes

inferred

to

be

evolving

by

positive

selection

at

a

FDR

-LRB-

q-value

true-positive

-RRB-

show

evidence

for

spatial

clustering

of

positively

selected

codons

-LRB-

Supplementary

Information

section

-RRB-

Spatial

heterogeneity

in

constraint

is

further

supported

by

contrasting

v

for

codons

inside

versus

outside

defined

InterPro

domains

-LRB-

genes

lacking

InterPro

domains

are

treated

as

outside

a

defined

InterPro

domain

-RRB-

Codons

within

InterPro

domains

were

significantly

more

conserved

than

codons

outside

InterPro

domains

-LRB-

median

v

InterPro

domains

outside

InterPro

domains

MWU

P

Supplementary

Information

section

-RRB-

Similarly

there

were

significantly

more

positively

selected

codons

outside

of

InterPro

domains

than

inside

domains

-LRB-

FET

P

-RRB-

suggesting

that

in

addition

to

being

more

constrained

codons

in

protein

domains

are

less

likely

to

be

targets

of

positive

selection

-LRB-

Supplementary

Fig.

-RRB-

Factors

affecting

the

rate

of

protein

evolution

in

Drosophila

The

sequenced

genomes

of

the

melanogaster

group

provide

unprecedented

statistical

power

to

identify

factors

affecting

rates

of

protein

evolution

Previous

analyses

have

suggested

that

although

the

level

of

gene

expression

consistently

seems

to

be

a

major

determinant

of

variation

in

rates

of

evolution

among

other

factors

probably

play

a

significant

if

perhaps

minor

In

Drosophila

although

highly

expressed

genes

do

evolve

more

slowly

breadth

of

expression

across

tissues

gene

essentiality

and

intron

number

all

also

independently

correlate

with

rates

of

protein

evolution

suggesting

that

the

additional

complexities

of

multicellular

organisms

are

important

factors

in

modulating

rates

of

protein

The

presence

of

repetitive

amino

acid

sequences

has

a

role

as

well

nonrepeat

regions

in

proteins

containing

repeats

evolve

faster

and

show

more

evidence

for

positive

selection

than

genes

lacking

These

data

also

provide

a

unique

opportunity

to

examine

the

impact

of

chromosomal

location

on

evolutionary

rates

Population

genetic

theory

predicts

that

for

new

recessive

mutations

both

purifying

and

positive

selection

will

be

more

efficient

on

the

X

chromosome

given

its

hemizygosity

in

In

contrast

the

lack

of

recombination

on

the

small

mainly

heterochromatic

dot

is

expected

to

reduce

the

efficacy

of

Because

codon

bias

or

the

unequal

usage

of

synonymous

codons

in

proteincoding

sequences

reflects

weak

but

pervasive

selection

it

is

a

sensitive

metric

for

evaluating

the

efficacy

of

purifying

selection

Consistent

with

expectation

in

all

species

we

find

significantly

elevated

levels

of

codon

bias

on

the

X

chromosome

and

significantly

reduced

levels

of

codon

bias

on

the

dot

Furthermore

X-chromosome-linked

genes

are

marginally

over-represented

within

the

set

of

positively

selected

genes

in

the

melanogaster

group

-LRB-

FET

P

-RRB-

which

is

consistent

with

increased

rates

of

adaptive

substitution

on

this

chromosome

This

analysis

suggests

that

chromosomal

context

also

serves

to

modulate

rates

of

molecular

evolution

in

protein-coding

genes

To

examine

further

the

impact

of

genomic

location

on

protein

evolution

we

examined

the

subset

of

genes

that

have

moved

within

or

between

chromosome

Genes

inferred

to

have

moved

between

Muller

elements

have

a

significantly

higher

rate

of

protein

evolution

than

genes

inferred

to

have

moved

within

a

Muller

element

-LRB-

MWU

P

-RRB-

and

genes

that

have

maintained

their

genomic

position

-LRB-

MWU

P

-RRB-

-LRB-

Supplementary

Fig.

-RRB-

Interestingly

genes

that

move

within

Muller

elements

have

a

significantly

lower

rate

of

protein

evolution

than

those

for

which

genomic

locations

have

been

maintained

-LRB-

MWU

P

-RRB-

It

remains

unclear

whether

these

differences

reflect

underlying

biases

in

the

types

of

genes

that

move

inter

versus

intra-chromosomally

or

whether

they

are

due

to

in

situ

patterns

of

evolution

in

novel

genomic

contexts

Codon

bias

Codon

bias

is

thought

to

enhance

the

efficiency

and/or

accuracy

of

and

seems

to

be

maintained

by

mutation

selection

drift

Across

the

Drosophila

genomes

there

is

more

codon

bias

in

the

Sophophora

subgenus

than

in

the

Drosophila

subgenus

and

a

previously

striking

reduction

in

codon

bias

in

D.

-LRB-

Fig.

-RRB-

However

with

only

minor

exceptions

codon

preferences

for

each

amino

acid

seem

to

be

conserved

across

of

the

species

The

striking

exception

is

D.

willistoni

in

which

codon

usage

for

of

redundant

amino

acids

has

diverged

-LRB-

Fig.

-RRB-

Mutation

alone

is

not

sufficient

to

explain

codonusage

bias

in

D.

willistoni

which

is

suggestive

of

a

lineage-specific

shift

in

codon

We

found

evidence

for

a

lineagespecific

genomic

reduction

in

codon

bias

in

D.

melanogaster

-LRB-

Fig.

-RRB-

as

has

been

suggested

In

addition

maximum-likelihood

estimation

of

the

strength

of

selection

on

synonymous

sites

in

melanogaster

group

single-copy

orthologues

revealed

a

marked

reduction

in

the

number

of

genes

under

selection

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

for

increased

codon

bias

in

D.

melanogaster

relative

to

its

sister

species

D.

Evolution

of

genes

associated

with

ecology

and

reproduction

Given

the

ecological

and

environmental

diversity

encompassed

by

the

Drosophila

species

we

examined

the

evolution

of

genes

and

gene

families

associated

with

ecology

and

reproduction

Specifically

we

selected

genes

with

roles

in

chemoreception

detoxification

metabolism

immunity/defence

and

sex/reproduction

for

more

detailed

study

Chemoreception

Drosophila

species

have

complex

olfactory

and

gustatory

systems

used

to

identify

food

sources

hazards

and

mates

which

depend

on

odorant-binding

proteins

and

olfactory/odorant

and

gustatory

receptors

-LRB-

Ors

and

Grs

-RRB-

The

D.

melanogaster

genome

has

approximately

Ors

Grs

and

odorant-binding

protein

genes

Despite

overall

conservation

of

gene

number

across

the

species

and

widespread

evidence

for

purifying

selection

within

the

melanogaster

group

there

is

evidence

that

a

subset

of

Or

and

Gr

genes

experiences

positive

Furthermore

clear

lineagespecific

differences

are

detectable

between

generalist

and

specialist

species

within

the

melanogaster

subgroup

First

the

two

independently

evolved

specialists

-LRB-

D.

sechellia

and

D.

erecta

-RRB-

are

losing

Gr

genes

approximately

five

times

more

rapidly

than

the

generalist

We

believe

this

result

is

robust

to

sequence

quality

because

all

pseudogenes

and

deletions

were

verified

by

direct

re-sequencing

and

synteny-based

orthologue

searches

respectively

Generalists

are

expected

to

encounter

the

most

diverse

set

of

tastants

and

seem

to

have

maintained

the

greatest

diversity

of

gustatory

receptors

Second

Or

and

Gr

genes

that

remain

intact

in

D.

sechellia

and

D.

erecta

evolve

significantly

more

rapidly

along

these

two

lineages

-LRB-

v

for

Ors

and

for

Grs

-RRB-

than

along

the

generalist

lineages

-LRB-

v

for

Ors

and

for

Grs

paired

Wilcoxon

P

and

-RRB-

There

is

some

evidence

that

odorant-binding

protein

genes

also

evolve

significantly

faster

in

specialists

compared

to

This

elevated

v

reflects

a

trend

observed

throughout

the

genomes

of

the

two

specialists

and

is

likely

to

result

at

least

in

part

from

demographic

phenomena

However

the

difference

between

specialist

and

generalist

v

for

Or/Gr

genes

-LRB-

-RRB-

is

significantly

greater

than

the

difference

for

genes

across

the

genome

-LRB-

MWU

P

-RRB-

suggesting

a

change

in

selective

regime

Moreover

the

observation

that

elevated

v

as

well

as

accelerated

gene

loss

disproportionately

affect

groups

of

Or

and

Gr

genes

that

respond

to

specific

chemical

ligands

and/or

are

expressed

during

specific

life

stages

suggests

that

rapid

evolution

at

Or/Gr

loci

in

specialists

is

related

to

the

ecological

shifts

these

species

have

D.

mel

D.

sim

D.

sec

D.

yak

D.

ere

D.

ana

D.

pse

D.

per

D.

wil

D.

vir

D.

moj

D.

gri

Arg

Leu

Ser

Asn

His

Asp

Tyr

CGC

CTG

TCC

AAC

CAC

GAC

TAC

CGT

TTG

AGC

AGC

AGC

AGC

AGC

AAT

GAC

GAT

TAT

Figure

Deviations

in

codon

bias

from

D.

melanogaster

in

Drosophila

species

The

upper

panel

depicts

differences

in

ENC

-LRB-

effective

number

of

codons

-RRB-

between

D.

melanogaster

and

the

non-melanogaster

species

calculated

on

a

gene-by-gene

basis

Note

that

increasing

levels

of

ENC

indicates

a

decrease

in

codon

bias

The

Sophophora

subgenus

in

general

has

higher

levels

of

codon

bias

than

the

Drosophila

subgenus

with

the

exception

of

D.

willistoni

which

shows

a

dramatic

reduction

in

codon

bias

The

lower

panel

shows

the

codons

for

which

preference

changes

across

the

Drosophila

species

A

dot

indicates

identical

codon

preference

to

D.

melanogaster

otherwise

the

preferred

codon

is

indicated

Detoxification/metabolism

The

larval

food

sources

for

many

Drosophila

species

contain

a

cocktail

of

toxic

compounds

and

consequently

Drosophila

genomes

encode

a

wide

variety

of

detoxification

proteins

These

include

members

of

the

cytochrome

-LRB-

-RRB-

carboxyl/choline-esterase

-LRB-

CCE

-RRB-

and

glutathione

S-transferase

-LRB-

GST

-RRB-

multigene

families

all

of

which

also

have

critical

roles

in

resistance

to

Among

the

the

five

enzymes

associated

with

insecticide

resistance

are

highly

dynamic

across

the

phylogeny

with

duplication

events

and

loss

events

since

the

last

common

ancestor

of

the

genus

which

is

in

striking

contrast

to

genes

with

known

developmental

roles

eight

of

which

are

present

as

a

single

copy

in

all

species

-LRB-

C.

Robin

personal

communication

-RRB-

As

with

chemoreceptors

specialists

seem

to

lose

detoxification

genes

at

a

faster

rate

than

generalists

For

instance

D.

sechellia

has

lost

the

most

genes

these

losses

comprise

almost

one-third

of

all

loss

events

-LRB-

Supplementary

Table

-RRB-

-LRB-

C.

Robin

personal

communication

-RRB-

Positive

selection

has

been

implicated

in

detoxification-gene

evolution

as

well

because

a

search

for

positive

selection

among

GSTs

identified

the

parallel

evolution

of

a

radical

glycine

to

lysine

amino

acid

change

in

an

enzyme

known

to

degrade

Finally

although

metabolic

enzymes

in

general

are

highly

constrained

-LRB-

median

v

for

enzymes

for

nonenzymes

MWU

P

-RRB-

enzymes

involved

in

xenobiotic

metabolism

evolve

significantly

faster

than

other

enzymes

-LRB-

median

v

for

the

xenobiotic

group

versus

v

overall

two-tailed

permutation

test

P

A.

J.

Greenberg

personal

communication

-RRB-

Metazoans

deal

with

excess

selenium

in

the

diet

by

sequestration

in

selenoproteins

which

incorporate

the

rare

amino

acid

selenocysteine

-LRB-

Sec

-RRB-

at

sites

specified

by

the

TGA

codon

The

recoding

of

the

normally

terminating

signal

TGA

as

a

Sec

codon

is

mediated

by

the

selenocystein

insertion

sequence

-LRB-

SECIS

-RRB-

a

secondary

structure

in

the

UTR

of

selenoprotein

messenger

RNAs

All

animals

examined

so

far

have

selenoproteins

three

have

been

identified

in

D.

melanogaster

-LRB-

SELG

SELM

and

-RRB-

Interestingly

although

the

three

known

melanogaster

selenoproteins

are

all

present

in

the

genomes

of

the

other

Drosophila

species

in

D.

willistoni

the

TGA

Sec

codons

have

been

substituted

by

cysteine

codons

-LRB-

TGT/TGC

-RRB-

Consistent

with

this

finding

analysis

of

the

seven

genes

implicated

to

date

in

selenoprotein

synthesis

including

the

Sec-specific

tRNA

suggests

that

most

of

these

genes

are

absent

in

D.

willistoni

-LRB-

R.

Guigo

personal

communication

-RRB-

D.

willistoni

thus

seems

to

be

the

first

animal

known

to

lack

selenoproteins

If

correct

this

observation

is

all

the

more

remarkable

given

the

ubiquity

of

selenoproteins

and

the

selenoprotein

biosynthesis

machinery

in

metazoans

the

toxicity

of

excess

selenium

and

the

protection

from

oxidative

stress

mediated

by

selenoproteins

However

it

remains

possible

that

this

species

encodes

selenoproteins

in

a

different

way

and

this

represents

an

exciting

avenue

of

future

research

Immunity/defence

Drosophila

like

all

insects

possesses

an

innate

immune

system

with

many

components

analogous

to

the

innate

immune

pathways

of

mammals

although

it

lacks

an

antibodymediated

adaptive

immune

Immune

system

genes

often

evolve

rapidly

and

adaptively

driven

by

selection

pressures

from

pathogens

and

The

genus

Drosophila

is

no

exception

immune

system

genes

evolve

more

rapidly

than

non-immune

genes

showing

both

high

total

divergence

rates

and

specific

signs

of

positive

In

particular

of

receptor

genes

involved

in

phagocytosis

seem

to

evolve

under

positive

selection

suggesting

that

molecular

co-evolution

between

Drosophila

pattern

recognition

receptors

and

pathogen

antigens

is

driving

adaptation

in

the

immune

Somewhat

surprisingly

genes

encoding

effector

proteins

such

as

antimicrobial

peptides

are

far

less

likely

to

exhibit

adaptive

sequence

evolution

Only

of

effector

genes

-LRB-

and

no

antimicrobial

peptides

-RRB-

show

evidence

of

adaptive

evolution

compared

to

of

genes

genome-wide

Instead

effector

genes

seem

to

evolve

by

rapid

duplication

and

deletion

Whereas

of

genes

genome-wide

ENC

deviation

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

of

genes

involved

in

pathogen

recognition

and

of

genes

implicated

in

immune-related

signal

transduction

can

be

found

as

singlecopy

orthologues

in

all

species

only

of

effector

genes

exist

as

single-copy

orthologues

across

the

genus

-LRB-

P

-RRB-

suggesting

rapid

radiation

of

effector

protein

classes

along

particular

Thus

much

of

the

Drosophila

immune

system

seems

to

evolve

rapidly

although

the

mode

of

evolution

varies

across

immune-gene

functional

classes

Sex/reproduction

Genes

encoding

sex

and

reproduction-related

proteins

are

subject

to

a

wide

array

of

selective

forces

including

sexual

conflict

sperm

competition

and

cryptic

female

choice

and

to

the

extent

that

these

selective

forces

are

of

evolutionary

consequence

this

should

lead

to

rapid

evolution

in

these

-LRB-

for

an

overview

see

refs

-RRB-

The

analysis

of

sex

and

reproduction-related

genes

within

the

melanogaster

group

indicated

that

male

sex

and

reproduction-related

genes

evolve

more

rapidly

at

the

protein

level

than

genes

not

involved

in

sex

or

reproduction

or

than

female

sex

and

reproduction-related

genes

-LRB-

Supplementary

Fig.

-RRB-

Positive

selection

seems

to

be

at

least

partially

responsible

for

these

patterns

because

genes

involved

in

spermatogenesis

have

significantly

stronger

evidence

for

positive

selection

than

do

nonspermatogenesis

genes

-LRB-

permutation

test

P

-RRB-

Similarly

genes

that

encode

components

of

seminal

fluid

have

significantly

stronger

evidence

for

positive

selection

than

non-sex

Moreover

protein-coding

genes

involved

in

male

reproduction

especially

seminal

fluid

and

testis

genes

are

particularly

likely

to

be

lost

or

gained

across

Drosophila

Evolutionary

forces

in

the

mitochondrial

genome

Functional

elements

in

mtDNA

are

strongly

conserved

as

expected

tRNAs

are

relatively

more

conserved

than

the

mtDNA

overall

-LRB-

average

pairwise

nucleotide

distance

substitutions

per

site

for

tRNAs

versus

substitutions

per

site

overall

-RRB-

We

observe

a

deficit

of

substitutions

occurring

in

the

stem

regions

of

the

stem-loop

structure

in

tRNAs

consistent

with

strong

selective

pressure

to

maintain

RNA

secondary

structure

and

there

is

a

strong

signature

of

purifying

selection

in

protein-coding

However

despite

their

shared

role

in

aerobic

respiration

there

is

marked

heterogeneity

in

the

rates

of

amino

acid

divergence

between

the

oxidative

phosphorylation

enzyme

complexes

across

the

species

-LRB-

NADH

dehydrogenase

ATPase

CytB

cytochrome

oxidase

mean

pairwise

dN

-RRB-

which

contrasts

with

the

relative

homogeneity

in

synonymous

substitution

rates

A

model

with

distinct

substitution

rates

for

each

enzyme

complex

rather

than

a

single

rate

provides

a

significantly

better

fit

to

the

data

-LRB-

P

-RRB-

suggesting

complexspecific

selective

effects

of

mitochondrial

Non-coding

sequence

evolution

ncRNA

sequence

evolution

The

availability

of

complete

sequence

from

Drosophila

genomes

combined

with

the

tractability

of

RNA

structure

predictions

offers

the

exciting

opportunity

to

connect

patterns

of

sequence

evolution

directly

with

structural

and

functional

constraints

at

the

molecular

level

We

tested

models

of

RNA

evolution

focusing

on

specific

ncRNA

gene

classes

in

addition

to

inferring

patterns

of

sequence

evolution

using

more

general

datasets

that

are

based

on

predicted

intronic

RNA

structures

The

exquisite

simplicity

of

miRNAs

and

their

shared

stem-loop

structure

makes

these

ncRNAs

particularly

amenable

to

evolutionary

analysis

Most

miRNAs

are

highly

conserved

within

the

Drosophila

genus

for

the

previously

described

miRNA

genes

inferred

to

be

present

in

the

common

ancestor

of

these

species

mature

miRNA

sequences

are

nearly

invariant

However

we

do

find

a

small

number

of

substitutions

and

a

single

deletion

in

mature

miRNA

sequences

-LRB-

Supplementary

Table

-RRB-

which

may

have

functional

consequences

for

miRNA

target

interactions

and

may

ultimately

help

identify

targets

through

sequence

covariation

Pre-miRNA

sequences

are

also

highly

conserved

evolving

at

about

of

the

rate

of

synonymous

sites

To

link

patterns

of

evolution

with

structural

constraints

we

inferred

ancestral

pre-miRNA

sequences

and

deduced

secondary

structures

at

each

ancestral

node

on

the

phylogeny

-LRB-

Supplementary

Information

section

-RRB-

Although

conserved

miRNA

genes

show

little

structural

change

-LRB-

little

change

in

free

energy

-RRB-

the

five

melanogaster

group-specific

miRNA

genes

-LRB-

and

the

cluster

-RRB-

have

undergone

numerous

changes

across

the

entire

pre-miRNA

sequence

including

the

ordinarily

invariant

mature

miRNA

Patterns

of

polymorphism

and

divergence

in

these

lineage-specific

miRNA

genes

including

a

high

frequency

of

derived

mutations

are

suggestive

of

positive

Although

lineagespecific

miRNAs

may

evolve

under

less

constraint

because

they

have

fewer

target

transcripts

in

the

genome

it

is

also

possible

that

recent

integration

into

regulatory

networks

causes

accelerated

rates

of

miRNA

evolution

We

further

investigated

patterns

of

sequence

evolution

for

the

subset

of

conserved

pre-miRNAs

with

mature

miRNA

sequences

at

their

end

by

calculating

evolutionary

rates

in

distinct

site

classes

-LRB-

Fig.

and

Supplementary

Information

section

-RRB-

Outside

the

mature

miRNA

and

its

complementary

sequence

loops

had

the

highest

rate

of

evolution

followed

by

unpaired

sites

with

paired

sites

having

the

lowest

rate

of

evolution

Inside

the

mature

miRNA

unpaired

sites

evolve

more

slowly

than

paired

sites

whereas

the

opposite

is

true

for

the

sequence

complementary

to

the

mature

miRNA

Surprisingly

a

large

fraction

of

unpaired

bulges

or

internal

loops

in

the

mature

miRNA

seem

to

be

conserved

a

pattern

which

may

have

implications

for

models

of

miRNA

biogenesis

and

the

degree

of

mismatch

allowed

in

miRNA

target

prediction

methods

Overall

these

results

support

the

qualitative

model

proposed

in

ref

for

the

canonical

progression

of

miRNA

evolution

and

show

that

functional

constraints

on

the

miRNA

itself

supersede

structural

constraints

imposed

by

maintenance

of

the

hairpin-loop

To

assess

constraint

on

stem

regions

of

RNA

structures

more

generally

we

compared

substitution

rates

in

stems

-LRB-

S

-RRB-

to

those

in

nominally

unconstrained

loop

regions

-LRB-

L

-RRB-

in

a

wide

variety

of

ncRNAs

-LRB-

Supplementary

Information

section

-RRB-

We

estimated

substitution

rates

using

a

maximum

likelihood

framework

and

compared

the

observed

L/S

ratio

with

the

average

L/S

ratio

estimated

from

published

secondary

structures

in

RFAM

which

we

normalized

to

L/S

ratios

for

Drosophila

ncRNA

families

range

from

a

highly

constrained

for

the

nuclear

RNase

P

family

to

for

the

ribosomal

RNA

-LRB-

Supplementary

Table

-RRB-

Substitution

rate

relative

to

class

Site

class

Figure

Substitution

rate

of

site

classes

within

miRNAs

Bootstrap

distributions

of

miRNA

substitution

rates

Structural

alignments

of

miRNA

precursor

hairpins

were

partitioned

into

six

site-classes

-LRB-

inset

-RRB-

-LRB-

-RRB-

hairpin

loops

unpaired

sites

-LRB-

-RRB-

outside

-LRB-

-RRB-

in

the

complementary

region

of

and

-LRB-

-RRB-

inside

the

miRNA

and

base

pairs

-LRB-

-RRB-

adjacent

to

and

-LRB-

-RRB-

involving

the

miRNA

Whiskers

show

approximate

confidence

intervals

for

median

differences

boxes

show

interquartile

range

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

Finally

we

predicted

a

set

of

conserved

intronic

RNA

structures

and

analysed

patterns

of

compensatory

nucleotide

substitution

in

D.

melanogaster

D.

yakuba

D.

ananassae

D.

pseudoobscura

D.

virilis

and

D.

mojavensis

-LRB-

Supplementary

Information

section

-RRB-

Signatures

of

compensatory

evolution

in

RNA

helices

are

detected

as

covarying

nucleotide

sites

or

covariations

-LRB-

that

is

two

Watson

Crick

bases

that

interact

in

species

A

replaced

by

a

different

Watson

Crick

pair

in

species

B

-RRB-

The

number

of

covariations

-LRB-

per

base

pair

of

a

helix

-RRB-

depends

on

the

physical

distance

between

the

interacting

nucleotides

-LRB-

Supplementary

Fig.

-RRB-

as

has

been

observed

for

the

RNA

helices

in

the

Drosophila

bicoid

UTR

Shortrange

pairings

exhibit

a

higher

average

number

of

covariations

with

a

larger

variance

among

helices

than

longer-range

pairings

The

decrease

in

rate

of

covariation

with

increasing

distance

may

be

explained

by

physical

properties

of

a

helix

which

may

impose

selective

constraints

on

the

evolution

of

covarying

nucleotides

within

a

helix

Alternatively

if

individual

mutations

at

each

locus

are

deleterious

but

compensated

by

mutations

at

a

second

locus

given

sufficiently

strong

selection

against

the

first

deleterious

mutation

these

epistatic

fitness

interactions

could

generate

the

observed

distance

Evolution

of

cis-regulatory

DNAs

Comparative

analyses

of

cisregulatory

sequences

may

provide

insights

into

the

evolutionary

forces

acting

on

regulatory

components

of

genes

shed

light

on

the

constraints

of

the

cis-regulatory

code

and

aid

in

annotation

of

new

regulatory

sequences

Here

we

rely

on

two

recently

compiled

databases

and

present

results

comparing

cis-regulatory

and

transcription

factor

binding

sites

-LRB-

derived

from

DNase

I

footprints

-RRB-

between

D.

melanogaster

and

D.

simulans

-LRB-

Supplementary

Information

section

-RRB-

We

estimated

mean

selective

constraint

-LRB-

C

the

fraction

of

mutations

removed

by

natural

selection

-RRB-

relative

to

the

fastest

evolving

intron

sites

at

the

end

of

short

introns

which

represent

putatively

unconstrained

neutral

standards

-LRB-

Supplementary

Information

section

-RRB-

Note

that

this

approach

ignores

the

contribution

of

positively

selected

sites

potentially

underestimating

the

fraction

of

functionally

relevant

Consistent

with

previous

findings

Drosophila

cis-regulatory

sequences

are

highly

Mean

constraint

within

cisregulatory

modules

is

-LRB-

bootstrap

confidence

interval

-RRB-

and

within

footprints

is

-LRB-

-RRB-

both

of

which

are

significantly

higher

than

mean

constraint

in

non-coding

DNA

overall

-LRB-

-LRB-

-RRB-

-RRB-

and

significantly

lower

than

constraint

at

non-degenerate

coding

sites

-LRB-

-LRB-

-RRB-

-RRB-

and

ncRNA

genes

-LRB-

-LRB-

-RRB-

-RRB-

-LRB-

Supplementary

Fig.

-RRB-

The

high

level

of

constraint

in

cis-regulatory

sequences

also

extends

into

flanking

sequences

only

declining

to

constraint

levels

typical

of

non-coding

DNA

bp

away

This

is

consistent

with

previous

findings

that

transcription

factor

binding

sites

tend

to

be

found

in

larger

blocks

of

constraint

that

cluster

to

form

cis-regulatory

To

understand

selective

constraints

on

nucleotides

within

cis-regulatory

sequences

that

have

direct

contact

with

transcription

factors

we

estimated

the

selective

constraint

for

the

best

match

to

position

weight

matrices

within

each

core

motifs

in

transcription-factor-binding

sites

have

a

mean

constraint

of

-LRB-

-RRB-

significantly

greater

than

the

mean

for

the

footprints

as

a

whole

and

approaching

the

level

of

constraint

found

at

non-degenerate

coding

sites

and

in

ncRNA

genes

-LRB-

Supplementary

Fig.

-RRB-

We

next

examined

the

variation

in

selective

constraint

across

cisregulatory

sequences

Surprisingly

we

find

no

evidence

that

selective

constraint

is

correlated

with

predicted

transcription-factor-binding

strength

-LRB-

estimated

as

the

position

weight

matrix

score

P-value

-RRB-

-LRB-

Spearman

's

r

P

-RRB-

We

observe

significant

variation

in

constraint

both

among

target

genes

-LRB-

Kruskal

Wallis

tests

footprints

P

and

position

weight

matrix

matches

within

footprints

P

-RRB-

and

among

chromosomes

-LRB-

cis-regulatory

modules

P

footprints

P

and

position

weight

matrix

matches

within

footprints

P

Supplementary

Table

-RRB-

Discussion

and

conclusion

Each

new

genome

sequence

affords

novel

opportunities

for

comparative

genomic

inference

What

makes

the

analysis

of

these

Drosophila

genomes

special

is

the

ability

to

place

every

one

of

these

genomic

comparisons

on

a

phylogeny

with

a

taxon

separation

that

is

ideal

for

asking

a

wealth

of

questions

about

evolutionary

patterns

and

processes

It

is

without

question

that

this

phylogenomic

approach

places

additional

burdens

on

bioinformatics

efforts

multiplying

the

amount

of

data

many-fold

requiring

extra

care

in

generating

multispecies

alignments

and

accommodating

the

reality

that

not

all

genome

sequences

have

the

same

degree

of

sequencing

or

assembly

accuracy

These

difficulties

notwithstanding

phylogenomics

has

extraordinary

advantages

not

only

for

the

analyses

that

are

possible

but

also

for

the

ability

to

produce

high-quality

assemblies

and

accurate

annotations

of

functional

features

in

a

genome

by

using

closely

related

genomes

as

guides

The

use

of

multi-species

orthology

provides

especially

convincing

evidence

in

support

of

particular

gene

models

not

only

for

protein-coding

genes

but

also

for

miRNA

and

other

ncRNA

genes

Many

attributes

of

the

genomes

of

Drosophila

are

remarkably

conserved

across

species

Overall

genome

size

number

of

genes

distribution

of

transposable

element

classes

and

patterns

of

codon

usage

are

all

very

similar

across

these

genomes

although

D.

willistoni

is

an

exceptional

outlier

by

several

criteria

including

its

unusually

skewed

codon

usage

increased

transposable

element

content

and

potential

lack

of

selenoproteins

At

a

finer

scale

the

number

of

structural

changes

and

rearrangements

is

much

larger

for

example

there

are

several

different

rearrangements

of

genes

in

the

Hox

cluster

found

in

these

Drosophila

species

The

vast

majority

of

multigene

families

are

found

in

all

genomes

although

gene

family

size

seems

to

be

highly

dynamic

almost

half

of

all

gene

families

change

in

size

on

at

least

one

lineage

and

a

noticeable

fraction

shows

rapid

and

lineage-specific

expansions

and

contractions

Particularly

notable

are

cases

consistent

with

adaptive

hypotheses

such

as

the

loss

of

Gr

genes

in

ecological

specialists

and

the

lineage-specific

expansions

of

antimicrobial

peptides

and

other

immune

effectors

All

species

were

found

to

have

novel

genes

not

seen

in

other

species

Although

lineage-specific

genes

are

challenging

to

verify

computationally

we

can

confirm

at

least

protein-coding

genes

unique

to

the

melanogaster

group

and

these

proteins

have

very

different

properties

from

ancestral

proteins

Similarly

although

the

relative

abundance

of

transposable

element

subclasses

across

these

genomes

does

not

differ

dramatically

total

genomic

transposable

element

content

varies

substantially

among

species

and

several

instances

of

lineage-specific

transposable

elements

were

discovered

There

is

considerable

variation

among

protein-coding

genes

in

rates

of

evolution

and

patterns

of

positive

selection

Functionally

similar

proteins

tend

to

evolve

at

similar

rates

although

variation

in

genomic

features

such

as

gene

expression

level

as

well

as

chromosomal

location

are

also

associated

with

variation

in

evolutionary

rate

among

proteins

Whereas

broad

functional

classes

do

not

seem

to

share

patterns

of

positive

selection

and

although

very

few

GO

categories

show

excesses

of

positive

selection

a

number

of

genes

involved

in

interactions

with

the

environment

and

in

sex

and

reproduction

do

show

signatures

of

adaptive

evolution

It

thus

seems

likely

that

adaptation

to

changing

environments

as

well

as

sexual

selection

shape

the

evolution

of

protein-coding

genes

Annotation

of

ncRNA

genes

across

all

species

allows

comprehensive

analysis

of

the

evolutionary

divergence

of

these

genes

MicroRNA

genes

in

particular

are

more

conserved

than

proteincoding

genes

with

respect

to

their

primary

DNA

sequence

and

the

substitutions

that

do

occur

often

have

compensatory

changes

such

that

the

average

estimated

free

energy

of

the

folding

structures

remains

remarkably

constant

across

the

phylogeny

Surprisingly

Nature

Publishing

Group

ARTICLES

NATURE

Vol

November

mismatches

in

miRNAs

seem

to

be

highly

conserved

which

may

impact

models

of

miRNA

biogenesis

and

target

recognition

Lineage-restricted

miRNAs

however

have

considerably

elevated

rates

of

change

suggesting

either

reduced

constraint

due

to

novel

miRNAs

having

fewer

targets

or

adaptive

evolution

of

evolutionarily

young

miRNAs

Virtually

any

question

about

the

function

of

genome

features

in

Drosophila

is

now

empowered

by

being

embedded

in

the

context

of

this

species

phylogeny

allowing

an

analysis

of

the

ways

by

which

evolution

has

tuned

myriad

biological

processes

across

the

hundreds

of

millions

of

years

spanned

in

total

by

this

phylogeny

The

analyses

presented

herein

have

generated

more

questions

than

they

have

answered

and

these

results

represent

a

small

fraction

of

that

which

is

possible

Because

much

of

this

rich

and

extraordinary

comparative

genomic

dataset

remains

to

be

explored

we

believe

that

these

Drosophila

genome

sequences

will

serve

as

a

powerful

tool

for

gleaning

further

insight

into

genetic

developmental

regulatory

and

evolutionary

processes

METHODS

The

full

methods

for

this

paper

are

described

in

Supplementary

Information

Here

we

describe

the

datasets

generated

by

this

project

and

their

availability

Genomic

sequence

Scaffolds

and

assemblies

for

all

genomic

sequence

generated

by

this

project

are

available

from

GenBank

-LRB-

Supplementary

Tables

and

-RRB-

and

FlyBase

-LRB-

-RRB-

Genome

browsers

are

available

from

UCSC

-LRB-

clade

insect

org

db

-RRB-

and

Flybase

-LRB-

cgi-bin/gbrowse/dmel

-RRB-

BLAST

search

of

these

genomes

is

available

at

FlyBase

-LRB-

-RRB-

Predicted

gene

models

Consensus

gene

predictions

for

the

non-melanogaster

species

produced

by

combining

several

different

GLEAN

runs

that

weight

homology

evidence

more

or

less

strongly

are

available

from

FlyBase

as

GFF

files

for

each

species

-LRB-

-RRB-

These

gene

models

can

also

be

accessed

from

the

Genome

Browser

in

FlyBase

-LRB-

Gbrowse

http

-RRB-

Predictions

of

non-protein-coding

genes

are

also

available

in

GFF

format

for

each

species

from

FlyBase

-LRB-

-RRB-

Homology

Multiway

homology

assignments

are

available

from

FlyBase

-LRB-

ftp

-RRB-

and

also

in

the

Genome

Browser

-LRB-

Gbrowse

-RRB-

Alignments

All

alignment

sets

produced

are

available

in

FASTA

format

from

FlyBase

-LRB-

-RRB-

PAML

parameters

Output

from

PAML

models

for

the

alignments

of

single

copy

orthologues

in

the

melanogaster

group

including

the

q-value

for

the

test

for

positive

selection

are

available

from

FlyBase

-LRB-

-RRB-

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Supplementary

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is

linked

to

the

online

version

of

the

paper

at

Acknowledgements

Agencourt

Bioscience

Corporation

The

Broad

Institute

of

MIT

and

Harvard

and

the

Washington

University

Genome

Sequencing

Center

were

supported

by

grants

and

contracts

from

the

National

Human

Genome

Research

Insititute

-LRB-

NHGRI

-RRB-

T.C.

Kaufman

acknowledges

support

from

the

Indian

Genomics

Initiative

Author

Contributions

The

laboratory

groups

of

A.

G.

Clark

-LRB-

including

A.

M.

Larracuente

T.

B.

Sackton

and

N.

D.

Singh

-RRB-

and

Michael

B.

Eisen

-LRB-

including

V.

N.

Iyer

and

D.

A.

Pollard

-RRB-

played

the

part

of

coordinating

the

primary

writing

and

editing

of

the

manuscript

with

the

considerable

help

of

D.

R.

Smith

C.

M.

Bergman

W.

M.

Gelbart

B.

Oliver

T.

A.

Markow

T.

C.

Kaufman

and

M.

Kellis

D.

R.

Smith

served

as

primary

coordinator

for

the

assemblies

The

remaining

authors

contributed

either

through

their

efforts

in

sequence

production

assembly

and

annotation

or

in

the

analysis

of

specific

topics

that

served

as

the

focus

of

more

than

companion

papers

Author

Information

Reprints

and

permissions

information

is

available

at

Correspondence

and

requests

for

materials

should

be

addressed

to

A.G.C.

-LRB-

-RRB-

M.B.E.

-LRB-

mbeisen@lbl.gov

-RRB-

D.R.S.

-LRB-

douglas.smith@agencourt.com

-RRB-

C.M.B.

-LRB-

casey.bergman@manchester.ac.uk

-RRB-

W.G.

-LRB-

gelbart@morgan.harvard.edu

-RRB-

B.O.

-LRB-

oliver@helix.nih.gov

-RRB-

T.A.M.

-LRB-

tmarkow@public.arl.arizona.edu

-RRB-

T.C.K.

-LRB-

kaufman@indiana.edu

-RRB-

M.K.

-LRB-

manoli@mit.edu

-RRB-

V.N.I.

-LRB-

venky@berkeley.edu

-RRB-

T.B.S.

-LRB-

-RRB-

A.M.L.

-LRB-

-RRB-

D.A.P.

-LRB-

danielapollard@alum.bowdoin.edu

-RRB-

N.D.S.

-LRB-

-RRB-

or

collectively

to

Drosophila

Genomes

Consortium

Project

Leaders

Andrew

G.

Michael

B.

Douglas

R.

Casey

M.

Brian

Therese

A.

Thomas

C.

Manolis

William

Annotation

Coordination

Venky

N.

Daniel

A.

Analysis/Writing

Coordination

Timothy

B.

Amanda

M.

Nadia

D.

Sequencing

Assembly

Annotation

and

Analysis

Contributors

Jose

P.

Dawn

N.

Boris

Montserrat

Hiroshi

Wyatt

W.

Charles

F.

David

H.

Roman

Carlo

G.

Daniel

A.

Daniel

Paolo

Phil

Serafim

Dave

Arjun

Enrico

Stephanie

A.

Robert

K.

Adrianne

D.

Michael

R.

Angela

N.

Randall

H.

Roger

K.

Corrado

Brian

R.

A.

Bernardo

de

Anat

Sergio

Susan

E.

Jean

L.

Charles

Sourav

Asif

Alberto

Sandra

W.

Josep

M.

James

C.

Jerry

A.

Jennifer

Robert

G.

Arthur

L.

Kim

Chuong

B.

Heather

Kevin

Thomas

Jay

D.

Alan

Sven

Findei

Eva

Lucinda

Robert

Ana

C.

L.

Anastasia

David

A.

Barry

E.

Greg

Don

Sante

Jennifer

Robert

Valer

Brenton

Anthony

J.

Sam

Samuel

Roderic

Erik

A.

Wilfried

Matthew

W.

Daniel

L.

Aaron

L.

Gillian

M.

Mira

V.

Andreas

LaDeana

Angie

S.

Ian

Roger

A.

Melissa

J.

Dan

Melanie

A.

David

B.

Santosh

William

R.

Justin

Corbin

D.

William

C.

Gary

H.

Eiko

Peter

D.

Pouya

Ewen

F.

Leonardo

B.

Karsten

Dave

Nature

Publishing

Group

NATURE

Vol

November

ARTICLES

University

of

Maryland

College

Park

Maryland

USA

of

Biological

Sciences

Illinois

State

University

Normal

Illinois

USA

of

Biology

University

of

Rochester

Rochester

New

York

USA

Research

Lab

USDA-ARS

Beltsville

Maryland

USA

for

Evolutionary

Functional

Genomics

Biodesign

Institute

Arizona

State

University

Tempe

Arizona

USA

Department

of

Computer

Science

University

of

Leipzig

Leipzig

Germany

Departamento

de

Genetica

Universidade

Federal

do

Rio

Grande

do

Sul

Porto

Alegre

RS

Brazil

of

Biology

Duke

University

Durham

New

Carolina

USA

Department

of

Genetics

North

Carolina

State

University

Raleigh

North

Caroline

USA

Center

University

of

Connecticut

Farmington

Connecticut

USA

of

Genomic

Regulation

Barcelona

Catalonia

Spain

of

Evolutionary

Biology

University

of

Edinburgh

Edinburgh

UK

Craig

Venter

Institute

Rockville

Maryland

USA

Functional

Genetics

Unit

University

of

Oxford

Oxford

UK

of

Physiology

Anatomy

and

Genetics

University

of

Oxford

Oxford

UK

for

Biomolecular

Science

and

Engineering

University

of

California

at

Santa

Cruz

Santa

Cruz

California

USA

of

Human

Genetics

University

of

Chicago

Chicago

Illinois

USA

Center

for

Molecular

Pathogenesis

Umea

University

Umea

Sweden

of

Biology

and

Carolina

Center

for

Genome

Sciences

The

University

of

North

Carolina

at

Chapel

Hill

Chapel

Hill

North

Carolina

USA

of

Zoology

Regent

's

Park

London

UK

Drosophila

Heterochromatin

Genome

Project

Department

of

Genome

and

Computational

Biology

Lawrence

Berkeley

National

Laboratory

Berkeley

California

USA

University

School

of

Medicine

Mitaka

Tokyo

Japan

Department

of

Biochemistry

and

Molecular

Biology

University

of

Southern

Denmark

Odense

M

Denmark

Genomics

Institute

Department

of

Plant

Sciences

and

University

of

Arizona

Tucson

Arizona

USA

of

Organismic

and

Evolutionary

Biology

Harvard

University

Cambridge

Massachusetts

USA

of

Life

Sciences

Arizona

State

University

Tempe

Arizona

USA

of

Environmental

Science

Policy

and

Management

University

of

California

at

Berkeley

Berkeley

California

USA

of

Entomology

Cornell

University

Ithaca

New

York

USA

Genomics

Institute

at

ShenZhen

ShenZhen

China

Genetica

i

Microbiologia

Universitat

Autonoma

de

Barcelona

Bellaterra

Spain

of

Cell

Biology

and

Molecular

Genetics

University

of

Maryland

College

Park

Maryland

USA

Farm

Research

Campus

Howard

Hughes

Medical

Institue

Ashburn

Viginia

USA

of

Zoology

University

of

Cambridge

Cambridge

UK

of

Biology

University

of

Copenhagen

Copenhagen

Denmark

Centre

Department

of

Molecular

Biology

University

of

Copenhagen

Copenhagen

N

Denmark

di

Biochimica

e

Biologia

Molecolare

Universita

di

Bari

and

Istituto

Tecnologie

Biomediche

del

Consiglio

Nazionale

delle

Ricerche

Bari

Italy

of

Ecology

and

Evolutionary

Biology

Yale

University

New

Haven

Connecticut

USA

Department

of

Biomedical

Informatics

Arizona

State

University

Tempe

Arizona

USA

Center

for

Biotechnology

Information

National

Institutes

of

Health

Bethesda

Maryland

USA

and

Genomics

Laboratory

Institut

Jacques

Monod

Paris

France

of

Molecular

Biology

Cell

Biology

and

Biochemistry

Brown

University

Providence

Rhode

Island

USA

Departamento

de

Genetica

Centro

de

Ciencias

Biologicas

Universidade

Federal

de

Pernambuco

Recife/PE

Brazil

Academico

de

Vitoria

Universidade

Federal

de

Pernambuco

Vitoria

de

Santo

Antao/PE

Brazil

Institute

CSIC

Madrid

Spain

Department

of

Biology

Emory

University

Atlanta

Georgia

USA

of

Biological

Sciences

Carnegie

Mellon

University

Pittsburgh

Pennsylvania

USA

Informatics

Stanford

University

Stanford

California

USA

of

Biology

San

Francisco

State

University

San

Francisco

California

USA

of

Biology

University

of

Munich

Planegg-Martinsried

Germany

of

Evolutionary

Biology

Setagaya-ku

Tokyo

Japan

Gakuen

Minato-ku

Tokyo

Japan

Bioinformatics

Institute

Hinxton

UK

of

Biology

City

University

of

New

York

at

Queens

Flushing

New

York

USA

Department

of

Biological

Sciences

and

Department

of

Medicine

University

of

Alberta

Edmonton

Alberta

Canada

of

Developmental

Biology

and

Neurosciences

Tohoku

University

Sendai

Japan

for

Physical

Science

and

Technology

University

of

Maryland

College

Park

Maryland

USA

Hokkaido

University

EESBIO

Sapporo

Hokkaido

Japan

of

Medecine

Universite

de

Geneve

Geneva

Switzerland

Broad

Institute

Genome

Sequencing

Platform

Jennifer

Amr

Jamal

Adal

Brikti

Justin

St

Christophe

Lynne

Allen

Peter

Erica

Scott

Harindra

Marc

Pasang

Andrew

Tashi

Aaron

Daniel

Toby

Jason

Leonid

Claude

Boris

Imane

Adam

Patrick

Sheridon

Yama

Lisa

Mieke

Alville

Patrick

Maura

Katie

Riza

Georgius

De

Stuart

Christina

Norbu

Kimberly

Erin

Missole

Passang

Kunsang

Alan

Richard

Jill

Abderrahim

Susan

Diallo

Sheila

Chelsea

D.

Alicia

Dennis

Loryn

Gary

Christina

R.

Georgia

Tina

Joseph

Edward

Sharleen

Kunsang

Nabil

Birhane

Jennifer

Charlotte

Andrew

Tracey

Monika

D.

Leanne

Brian

M

Erii

Asha

Ben

Rob

J.

Sudhir

Roberta

Eric

Charles

H.

Richard

Brian

P.

So-Jeong

Lisa

Ruiqiang

Chiao-Feng

Michael

F.

Kerstin

Ana

Manyuan

Lloyd

Elena

Jian

Meizhong

Carlos

A.

Wojciech

Mar

Muneo

Luciano

Bryant

Carolyn

S.

Brendan

Kevin

Maria

Patrick

Michael

U.

Kristi

Stephen

M.

Xu

Eugene

Barbara

Stuart

Rasmus

Mohamed

A.

F.

Patrick

Lior

Montserrat

Matthew

J.

Michael

Leopold

Jakob

S.

Graziano

Adam

M.

Chris

P.

Mihai

Damiano

Jeffrey

R.

Sonja

Kim

Marta

Hadi

Kristipati

Ravi

David

Matthew

D.

Laura

K.

Robert

Amy

Karin

A.

Tania

T.

Michael

G.

Charles

Yu-Hui

Claudia

Julio

Marc

J.

Alfredo

Susan

Steven

L.

Alejandro

David

J.

Hajime

Stephen

W.

Michael

C.

Todd

Russell

Carmen

Rama

S.

Laura

Marina

Nicholas

B.

Chris

D.

Temple

F.

John

Deborah

E.

Alexander

Wolfgang

Robert

L.

Sebastian

David

Granger

Granger

G.

Wei

Sarah

Yoshiko

N.

Yoshihiko

Jason

M.

Vera

L.

S.

Eli

J.

Craig

Saverio

Filipe

G.

Albert

J.

Alfredo

Brian

Jun

Marvin

Thomas

Derek

Richard

K.

Rod

A.

Mariana

F.

Alex

Gane

Ka-Shu

Chung-I

Gabriel

Daisuke

Hsiao-Pei

Shiaw-Pyng

James

A.

Kiyohito

Evgeny

Peili

Yu

Aleksey

V.

Broad

Institute

Genome

Sequencing

Platform

Broad

Institute

Whole

Genome

Assembly

Team

Department

of

Molecular

Biology

and

Genetics

Cornell

University

Ithaca

New

York

USA

Sciences

Division

Lawrence

Berkeley

National

Laboratory

Berkeley

California

USA

for

Integrative

Genomics

Department

of

Molecular

and

Cell

Biology

University

of

California

at

Berkeley

Berkeley

California

USA

Agencourt

Bioscience

Corporation

Beverly

Massachusetts

USA

of

Life

Sciences

University

of

Manchester

Manchester

PT

UK

of

Cellular

and

Developmental

Biology

National

Institutes

of

Health

Bethesda

Maryland

USA

of

Ecology

and

Evolutionary

Biology

University

of

Arizona

Tucson

Arizona

USA

of

Biology

Indiana

University

Bloomington

Indiana

USA

Science

and

Artificial

Intelligence

Laboratory

Cambridge

Massachusetts

USA

Institute

of

MIT

and

Harvard

Cambridge

Center

Cambridge

Massachusetts

USA

of

Molecular

and

Cellular

Biology

Harvard

University

Cambridge

Massachusetts

USA

The

Biological

Laboratories

Harvard

University

Cambridge

Massachusetts

USA

of

Molecular

and

Cell

Biology

University

of

California

at

Berkeley

Berkeley

California

USA

Graduate

Group

University

of

California

at

Berkeley

Berkeley

California

USA

of

Ecology

and

Evolutionary

Biology

Cornell

University

a

Ithaca

New

York

USA

de

Biologi

Molecular

Severo

Ochoa

Universidad

Autonoma

de

Madrid

Madrid

Spain

of

Ecology

and

Evolutionary

Biology

Brown

University

Providence

Rhode

Island

USA

Structural

Studies

Division

MRC

Laboratory

of

Molecular

Biology

Cambridge

UK

de

Genetica

Universitat

de

Barcelona

Barcelona

Spain

Department

of

Biology

Pennsylvania

State

University

University

Park

Pennsylvania

USA

Department

of

Genetics

University

of

Georgia

Athens

Georgia

USA

Centre

for

Bioinformatics

Uppsala

Universitet

Uppsala

Sweden

of

Ecology

and

Evolution

University

of

Chicago

Chicago

Illinois

USA

of

Biology

McMaster

University

Hamilton

Ontario

Canada

of

Biology

University

of

St.

Andrews

Fife

UK

Dipartimento

di

Genetica

e

Microbiologia

dell

Universita

di

Bari

Bari

Italy

Department

of

Genetics

University

of

Melbourne

Melbourne

Australia

Computer

Science

Department

Stanford

University

Stanford

California

USA

Section

of

Evolution

and

Ecology

and

Center

for

Population

Biology

University

of

California

at

Davis

Davis

California

USA

Engineering

Research

Center

Boston

University

Boston

Massachusetts

USA

Group

in

Biomedical

Informatics

Institut

Municipal

d'Investigacio

Medica

Universitat

Pompeu

Fabra

Barcelona

Catalonia

Spain

of

Bioengineering

University

of

California

at

Berkeley

Berkeley

California

USA

for

Computational

Genomics

Washington

University

St

Louis

Missouri

USA

and

Plant

Sciences

The

University

of

Sheffield

Sheffield

UK

of

Biology

Syracuse

University

Syracuse

New

York

USA

de

Genetica

Universidade

Federal

do

Rio

de

Janeiro

Rio

de

Janeiro

Brazil

Stock

Center

Tucson

Arizona

USA

of

Mathematics

University

of

California

at

Berkeley

Berkeley

California

USA

Center

University

of

California

at

Davis

Davis

California

USA

Sequencing

Center

Washington

University

School

of

Medicine

St

Louis

Missouri

USA

Department

of

Biology

University

of

Winnipeg

Winnipeg

Manitoba

Canada

Department

of

Biological

Sciences

University

of

Iowa

Iowa

City

Iowa

USA

School

of

Informatics

Indiana

University

Bloomington

Indiana

USA

Wellcome

Trust

Sanger

Institute

Wellcome

Trust

Genome

Campus

Hinxton

Cambridge

UK

for

Bioinformatics

and

Computational

Biology

Nature

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Group

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Seva

Dmitry

Peter

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Alex

Xiaohong

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Tashi

Yeshi

Rakela

Annie

Pen

Vasilia

Kebede

Charles

William

Susan

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James

Louis

Oana

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Tanya

Rachel

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Leonidas

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Jerome

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Thu

Nga

Robert

Choe

Nyima

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Sahal

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Otero

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Pema

Fritz

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Filip

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NATURE

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Peter

Keenan

Elizabeth

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Terry

Ngawang

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Diana

Todd

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John

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Christopher

Senait

Talene

Yama

Dawa

Kerri

Ira

Tsamla

Helen

Andy

Tsering

Tsering

Michael

Jane

Adam

Shailendra

Geneva

Qing

Lisa

Danni

Andrew

Zac

Broad

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Team

David

B.

Pablo

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Jonathan

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Sante

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