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What

is

a

gene

post-ENCODE

History

and

updated

definition

Mark

B.

Gerstein

Can

Bruce

Joel

S.

Rozowsky

Deyou

Zheng

Jiang

Du

Jan

O.

Korbel

Olof

Emanuelsson

Zhengdong

D.

Zhang

Sherman

Weissman

and

Michael

Snyder

Genome

Res

Access

the

most

recent

version

at

doi

gr

Supplementary

data

References

Fig

This

article

cites

articles

of

which

can

be

accessed

free

at

Article

cited

in

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Access

Email

alerting

service

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available

online

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Research

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Perspective

What

is

a

gene

post-ENCODE

History

and

updated

definition

Mark

B.

Gerstein

Can

Bruce

Joel

S.

Rozowsky

Deyou

Zheng

Jiang

Du

Jan

O.

Korbel

Olof

Emanuelsson

Zhengdong

D.

Zhang

Sherman

Weissman

and

Michael

Program

in

Computational

Biology

Bioinformatics

Yale

University

New

Haven

Connecticut

USA

Biophysics

Biochemistry

Department

Yale

University

New

Haven

Connecticut

USA

Science

Department

Yale

University

New

Haven

Connecticut

USA

for

Medical

Informatics

Yale

University

New

Haven

Connecticut

USA

Molecular

Biology

Laboratory

Heidelberg

Germany

Bioinformatics

Center

Albanova

University

Center

Stockholm

University

Stockholm

Sweden

Department

Yale

University

New

Haven

Connecticut

USA

Cellular

Developmental

Biology

Department

Yale

University

New

Haven

Connecticut

USA

While

sequencing

of

the

human

genome

surprised

us

with

how

many

protein-coding

genes

there

are

it

did

not

fundamentally

change

our

perspective

on

what

a

gene

is

In

contrast

the

complex

patterns

of

dispersed

regulation

and

pervasive

transcription

uncovered

by

the

ENCODE

project

together

with

non-genic

conservation

and

the

abundance

of

noncoding

RNA

genes

have

challenged

the

notion

of

the

gene

To

illustrate

this

we

review

the

evolution

of

operational

definitions

of

a

gene

over

the

past

century

from

the

abstract

elements

of

heredity

of

Mendel

and

Morgan

to

the

present-day

ORFs

enumerated

in

the

sequence

databanks

We

then

summarize

the

current

ENCODE

findings

and

provide

a

computational

metaphor

for

the

complexity

Finally

we

propose

a

tentative

update

to

the

definition

of

a

gene

A

gene

is

a

union

of

genomic

sequences

encoding

a

coherent

set

of

potentially

overlapping

functional

products

Our

definition

sidesteps

the

complexities

of

regulation

and

transcription

by

removing

the

former

altogether

from

the

definition

and

arguing

that

final

functional

gene

products

-LRB-

rather

than

intermediate

transcripts

-RRB-

should

be

used

to

group

together

entities

associated

with

a

single

gene

It

also

manifests

how

integral

the

concept

of

biological

function

is

in

defining

genes

Introduction

The

classical

view

of

a

gene

as

a

discrete

element

in

the

genome

has

been

shaken

by

ENCODE

The

ENCODE

consortium

recently

completed

its

characterization

of

of

the

human

genome

by

various

high-throughput

experimental

and

computational

techniques

designed

to

characterize

functional

elements

-LRB-

The

ENCODE

Project

Consortium

-RRB-

This

project

represents

a

major

milestone

in

the

characterization

of

the

human

genome

and

the

current

findings

show

a

striking

picture

of

complex

molecular

activity

While

the

landmark

human

genome

sequencing

surprised

many

with

the

small

number

-LRB-

relative

to

simpler

organisms

-RRB-

of

protein-coding

genes

that

sequence

annotators

could

identify

-LRB-

according

to

the

latest

estimate

-LSB-

see

-RSB-

-RRB-

ENCODE

highlighted

the

number

and

complexity

of

the

RNA

transcripts

that

the

genome

produces

In

this

regard

ENCODE

has

changed

our

view

of

what

is

a

gene

considerably

more

than

the

sequencing

of

the

Haemophilus

influenza

and

human

genomes

did

-LRB-

Fleischmann

et

al.

Lander

et

al.

Venter

et

al.

-RRB-

The

discrepancy

between

our

previous

protein-centric

view

of

the

gene

and

one

that

is

revealed

by

the

extensive

transcriptional

activity

of

the

genome

prompts

us

to

reconsider

now

what

a

gene

is

Here

we

review

how

the

concept

of

the

gene

has

changed

over

Corresponding

author

E-mail

Mark.Gerstein@yale.edu

fax

-LRB-360-RRB- 838-7861

Article

is

online

at

Freely

available

online

through

the

Genome

Research

Open

Access

option

the

past

century

summarize

the

current

thinking

based

on

the

latest

ENCODE

findings

and

propose

a

new

updated

gene

definition

that

takes

these

findings

into

account

History

of

the

gene

to

just

before

ENCODE

Definition

Gene

as

a

discrete

unit

of

heredity

The

concept

of

the

gene

has

evolved

and

become

more

complex

since

it

was

first

proposed

-LRB-

see

timeline

in

Fig.

accompanying

poster

-RRB-

There

are

various

definitions

of

the

term

although

common

initial

descriptions

include

the

ability

to

determine

a

particular

characteristic

of

an

organism

and

the

heritability

of

this

characteristic

In

particular

the

word

gene

was

first

used

by

Wilhelm

Johannsen

in

based

on

the

concept

developed

by

Gregor

Mendel

in

-LRB-

Mendel

-RRB-

The

word

was

a

derivative

of

pangene

which

was

used

by

Hugo

De

Vries

for

entities

involved

in

pangenesis

Darwin

's

hypothetical

mechanism

of

heredity

-LRB-

Heimans

-RRB-

Johnannsen

called

a

gene

the

special

conditions

foundations

and

determiners

which

are

present

-LSB-

in

the

gametes

-RSB-

in

unique

separate

and

thereby

independent

ways

-LSB-

by

which

-RSB-

many

characteristics

of

the

organism

are

specified

-LRB-

Johannsen

p.

-RRB-

The

etymology

of

the

term

derives

from

the

Greek

genesis

-LRB-

birth

-RRB-

or

genos

-LRB-

origin

-RRB-

The

related

word

genetics

was

used

by

the

geneticist

William

Bateson

in

-LRB-

-RRB-

Mendel

showed

that

when

breeding

plants

some

traits

such

as

height

or

flower

color

do

not

appear

blended

in

their

off

by

Cold

Spring

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Press

ISSN

Genome

Research

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from

on

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by

Cold

Spring

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Press

Gerstein

et

al.

Figure

-LRB-

Enclosed

poster

-RRB-

Timeline

of

the

history

of

the

term

gene

A

term

invented

almost

a

century

ago

gene

with

its

beguilingly

simple

orthography

has

become

a

central

concept

in

biology

Given

a

specific

meaning

at

its

coinage

this

word

has

evolved

into

something

complex

and

elusive

over

the

years

reflecting

our

ever-expanding

knowledge

in

genetics

and

in

life

sciences

at

large

The

stunning

discoveries

made

in

the

ENCODE

Project

like

many

before

that

significantly

enriched

the

meaning

of

this

term

are

harbingers

of

another

tide

of

change

in

our

understanding

of

what

a

gene

is

in

the

early

years

of

bacteriology

A

practical

view

of

the

gene

was

that

of

the

cistron

a

region

of

DNA

defined

by

mutations

that

in

trans

could

not

genetically

complement

each

other

-LRB-

Benzer

-RRB-

Definition

Gene

as

transcribed

code

It

was

the

solution

of

the

three-dimensional

structure

of

DNA

by

Watson

and

Crick

in

-LRB-

Watson

and

Crick

-RRB-

that

explained

how

DNA

could

function

as

the

molecule

of

heredity

Base

pairing

explained

how

genetic

information

could

be

copied

and

the

existence

of

two

strands

explained

how

occasional

errors

in

replication

could

lead

to

a

mutation

in

one

of

the

daughter

copies

of

the

DNA

molecule

From

the

on

molecular

biology

developed

at

a

rapid

pace

The

RNA

transcript

of

the

protein-coding

sequences

was

translated

using

the

genetic

code

-LRB-

solved

in

by

Nirenberg

et

al.

-LSB-

-RSB-

and

S

ll

et

al.

-LSB-

-RSB-

-RRB-

into

an

amino

acid

sequence

Francis

Crick

-LRB-

-RRB-

summarized

the

flow

of

information

in

gene

expression

as

from

nucleic

acid

to

protein

-LRB-

the

beginnings

of

the

Central

Dogma

-RRB-

However

there

were

some

immediate

exceptions

to

this

It

was

known

that

some

genes

code

not

for

protein

but

for

functional

RNA

molecules

such

as

rRNA

and

tRNA

In

addition

in

RNA

viruses

the

gene

is

made

of

RNA

The

molecular

view

of

the

gene

that

developed

through

the

can

be

summarized

in

general

terms

to

be

a

code

residing

on

nucleic

acid

that

gives

rise

to

a

functional

product

spring

that

is

these

traits

are

passed

on

as

distinct

discrete

entities

-LRB-

Mendel

-RRB-

His

work

also

demonstrated

that

variations

in

traits

were

caused

by

variations

in

inheritable

factors

-LRB-

or

in

today

's

terminology

phenotype

is

caused

by

genotype

-RRB-

It

was

only

after

Mendel

's

work

was

repeated

and

rediscovered

by

Carl

Correns

Erich

von

Tschermak-Seysenegg

and

Hugo

De

Vries

in

that

further

work

on

the

nature

of

the

unit

of

inheritance

truly

began

-LRB-

Tschermak

Vries

Rheinberger

-RRB-

Definition

Gene

as

a

distinct

locus

In

the

next

major

development

the

American

geneticist

Thomas

Hunt

Morgan

and

his

students

were

studying

the

segregation

of

mutations

in

Drosophila

melanogaster

They

were

able

to

explain

their

data

with

a

model

that

genes

are

arranged

linearly

and

their

ability

to

cross-over

is

proportional

to

the

distance

that

separated

them

The

first

genetic

map

was

created

in

-LRB-

Sturtevant

-RRB-

and

Morgan

and

his

students

published

The

Mechanism

of

Mendelian

Inheritance

in

-LRB-

Morgan

et

al.

-RRB-

To

the

early

geneticists

a

gene

was

an

abstract

entity

whose

existence

was

reflected

in

the

way

phenotypes

were

transmitted

between

generations

The

methodology

used

by

early

geneticists

involved

mutations

and

recombination

so

the

gene

was

essentially

a

locus

whose

size

was

determined

by

mutations

that

inactivated

-LRB-

or

activated

-RRB-

a

trait

of

interest

and

by

the

size

of

the

recombining

regions

The

fact

that

genetic

linkage

corresponded

to

physical

locations

on

chromosomes

was

shown

later

in

by

Barbara

McClintock

in

her

cytogenetic

studies

on

maize

-LRB-

McClintock

-RRB-

Definition

Gene

as

open

reading

frame

-LRB-

ORF

-RRB-

sequence

pattern

The

development

of

cloning

and

sequencing

techniques

in

the

combined

with

knowledge

of

the

genetic

code

revolutionized

the

field

of

molecular

biology

by

providing

a

wealth

of

information

on

how

genes

are

organized

and

expressed

The

first

gene

to

be

sequenced

was

from

the

bacteriophage

which

was

also

the

first

organism

to

be

fully

sequenced

-LRB-

Fiers

et

al.

-RRB-

The

parallel

development

of

computational

tools

led

to

algorithms

for

the

identification

of

genes

based

on

their

sequence

characteristics

-LRB-

e.g.

for

review

see

Rogic

et

al.

-RRB-

In

many

cases

a

DNA

sequence

could

be

used

to

infer

structure

and

function

for

the

gene

and

its

products

This

situation

created

a

new

concept

of

the

nominal

gene

which

is

defined

by

its

predicted

sequence

rather

than

as

a

genetic

locus

responsible

for

a

phenotype

-LRB-

Griffiths

and

Stotz

-RRB-

The

identification

of

most

genes

in

sequenced

genomes

is

based

either

on

their

similarity

to

other

known

genes

or

the

statistically

significant

signature

of

a

protein-coding

sequence

In

many

cases

the

gene

effectively

became

identified

as

an

annotated

ORF

in

the

genome

-LRB-

Doolittle

-RRB-

Definition

Gene

as

a

blueprint

for

a

protein

Beadle

and

Tatum

-LRB-

-RRB-

who

studied

Neurospora

metabolism

discovered

that

mutations

in

genes

could

cause

defects

in

steps

in

metabolic

pathways

This

was

stated

as

the

one

gene

one

enzyme

view

which

later

became

one

gene

one

polypeptide

In

this

viewpoint

the

gene

is

being

implicitly

considered

as

the

information

behind

the

individual

molecules

in

a

biochemical

pathway

This

view

became

progressively

more

explicit

and

mechanistic

in

later

decades

Definition

Gene

as

a

physical

molecule

The

fact

that

heredity

has

a

physical

molecular

basis

was

demonstrated

by

the

observation

that

X

rays

could

cause

mutations

-LRB-

Muller

-RRB-

Griffith

's

-LRB-

-RRB-

demonstration

that

something

in

virulent

but

dead

Pneumococcus

strains

could

be

taken

up

by

live

nonvirulent

Pneumococcus

and

transform

them

into

virulent

bacteria

was

further

evidence

in

this

direction

It

was

later

shown

that

this

substance

could

be

destroyed

by

the

enzyme

DNase

-LRB-

Avery

et

al.

-RRB-

In

Hershey

and

Chase

established

that

the

substance

actually

transmitted

by

bacteriophage

to

their

progeny

is

DNA

and

not

protein

-LRB-

Hershey

and

Chase

-RRB-

Moreover

the

idea

that

a

gene

's

product

is

a

diffusible

substance

underlies

the

complementation

test

that

was

used

to

define

genes

Definition

Annotated

genomic

entity

enumerated

in

the

databanks

-LRB-

current

view

pre-ENCODE

-RRB-

The

current

definition

of

a

gene

used

by

scientific

organizations

that

annotate

genomes

still

relies

on

the

sequence

view

Thus

a

gene

was

defined

by

the

Human

Genome

Nomenclature

Organization

as

a

DNA

segment

that

contributes

to

phenotype

function

In

the

absence

of

demonstrated

function

a

gene

may

be

characterized

by

sequence

transcription

or

homology

-LRB-

Wain

et

al.

-RRB-

Recently

the

Sequence

Ontology

Consortium

reportedly

called

the

gene

a

locatable

region

of

genomic

sequence

corresponding

to

a

unit

of

inheritance

which

is

associated

with

Genome

Research

Downloaded

from

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Spring

Harbor

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Press

What

is

a

gene

regulatory

regions

transcribed

regions

and/or

other

functional

sequence

regions

-LRB-

Pearson

-RRB-

The

sequencing

of

first

the

Haemophilus

influenza

genome

and

then

the

human

genome

-LRB-

Fleischmann

et

al.

Lander

et

al.

Venter

et

al.

-RRB-

led

to

an

explosion

in

the

amount

of

sequence

that

definitions

such

as

the

above

could

be

applied

to

In

fact

there

was

a

huge

popular

interest

in

counting

the

number

of

genes

in

various

organisms

This

interest

was

crystallized

originally

by

Gene

Sweepstake

's

wager

on

the

number

of

genes

in

the

human

genome

which

received

extensive

media

coverage

-LRB-

Wade

-RRB-

It

has

been

pointed

out

that

these

enumerations

overemphasize

traditional

protein-coding

genes

In

particular

when

the

number

of

genes

present

in

the

human

genome

was

reported

in

it

was

acknowledged

that

too

little

was

known

about

RNAcoding

genes

such

that

the

given

number

was

that

of

proteincoding

genes

The

Ensembl

view

of

the

gene

was

specifically

summarized

in

the

rules

of

the

Gene

Sweepstake

as

follows

alternatively

spliced

transcripts

all

belong

to

the

same

gene

even

if

the

proteins

that

are

produced

are

different

-LRB-

-RRB-

post-translational

modification

Such

sequences

could

reside

within

the

coding

sequence

as

well

as

in

the

flanking

regions

and

in

the

case

of

enhancers

and

related

elements

very

far

away

from

the

coding

sequence

Although

functionally

required

for

the

expression

of

the

gene

product

regulatory

elements

especially

the

distant

ones

made

the

concept

of

the

gene

as

a

compact

genetic

locus

problematic

Regulation

is

integral

to

many

current

definitions

of

the

gene

In

particular

one

current

textbook

definition

of

a

gene

in

molecular

terms

is

the

entire

nucleic

acid

sequence

that

is

necessary

for

the

synthesis

of

a

functional

polypeptide

-LRB-

or

RNA

-RRB-

-LRB-

Lodish

et

al.

-RRB-

If

that

implies

appropriately

regulated

synthesis

the

DNA

sequences

in

a

gene

would

include

not

only

those

coding

for

the

pre-mRNA

and

its

flanking

control

regions

but

also

enhancers

Moreover

many

enhancers

are

distant

along

the

DNA

sequence

although

they

are

actually

quite

close

due

to

three-dimensional

chromatin

structure

Overlapping

and

spliced

genes

Overlapping

As

genes

mRNAs

and

eventually

complete

genomes

were

sequenced

the

simple

operon

model

turned

out

to

be

applicable

only

to

genes

of

prokaryotes

and

their

phages

Eukaryotes

were

different

in

many

respects

including

genetic

organization

and

information

flow

The

model

of

genes

as

hereditary

units

that

are

nonoverlapping

and

continuous

was

shown

to

be

incorrect

by

the

precise

mapping

of

the

coding

sequences

of

genes

In

fact

some

genes

have

been

found

to

overlap

one

another

sharing

the

same

DNA

sequence

in

a

different

reading

frame

or

on

the

opposite

strand

The

discontinuous

structure

of

genes

potentially

allows

one

gene

to

be

completely

contained

inside

another

one

's

intron

or

one

gene

to

overlap

with

another

on

the

same

strand

without

sharing

any

exons

or

regulatory

elements

A

current

computational

metaphor

Genes

as

subroutines

in

the

genomic

operating

system

Given

that

counting

genes

in

the

genome

is

such

a

large-scale

computational

endeavor

and

that

genes

fundamentally

deal

with

information

processing

the

lexicon

of

computer

science

naturally

has

been

increasingly

applied

to

describing

them

In

particular

people

in

the

computational

biology

community

have

used

the

description

of

a

formal

language

to

describe

the

structure

of

genes

in

very

much

the

same

way

that

grammars

are

used

to

describe

computer

programs

with

a

precise

syntax

of

upstream

regulation

exons

and

introns

-LRB-

Searls

-RRB-

Moreover

one

metaphor

that

is

increasingly

popular

for

describing

genes

is

to

think

of

them

in

terms

of

subroutines

in

a

huge

operating

system

-LRB-

OS

-RRB-

That

is

insofar

as

the

nucleotides

of

the

genome

are

put

together

into

a

code

that

is

executed

through

the

process

of

transcription

and

translation

the

genome

can

be

thought

of

as

an

operating

system

for

a

living

being

Genes

are

then

individual

subroutines

in

this

overall

system

that

are

repetitively

called

in

the

process

of

transcription

Splicing

Splicing

was

discovered

in

-LRB-

Berget

et

al.

Chow

et

al.

Gelinas

and

Roberts

-RRB-

It

soon

became

clear

that

the

gene

was

not

a

simple

unit

of

heredity

or

function

but

rather

a

series

of

exons

coding

for

in

some

cases

discrete

protein

domains

and

separated

by

long

noncoding

stretches

called

introns

With

alternative

splicing

one

genetic

locus

could

code

for

multiple

different

mRNA

transcripts

This

discovery

complicated

the

concept

of

the

gene

radically

For

instance

in

the

sequencing

of

the

genome

Celera

defined

a

gene

as

a

locus

of

co-transcribed

exons

-LRB-

Venter

et

al.

-RRB-

and

Ensembl

's

Gene

Sweepstake

Web

page

originally

defined

a

gene

as

a

set

of

connected

transcripts

where

connected

meant

sharing

one

exon

-LRB-

-RRB-

The

latter

definition

implies

that

a

group

of

transcripts

may

share

a

set

of

exons

but

no

one

exon

is

common

to

all

of

them

Problematic

issues

with

the

current

definition

of

a

gene

There

are

a

number

of

problematic

aspects

of

the

current

definition

of

a

gene

as

applied

to

the

human

genome

which

we

discuss

below

Several

additional

complications

are

summarized

in

Table

Gene

regulation

Jacob

and

Monod

-LRB-

-RRB-

in

their

study

of

the

lac

operon

of

Escherichia

coli

provided

a

paradigm

for

the

mechanism

of

regulation

of

the

gene

It

consisted

of

a

region

of

DNA

consisting

of

sequences

coding

for

one

or

more

proteins

a

promoter

sequence

for

the

binding

of

RNA

polymerase

and

an

operator

sequence

to

which

regulatory

genes

bind

Later

other

sequences

were

found

to

exist

that

could

affect

practically

every

aspect

of

gene

regulation

from

transcription

to

mRNA

degradation

and

Trans-splicing

The

phenomenon

of

trans-splicing

-LRB-

ligation

of

two

separate

mRNA

molecules

-RRB-

further

complicated

our

understanding

-LRB-

Blumenthal

-RRB-

There

are

examples

of

transcripts

from

the

same

gene

or

the

opposite

DNA

strand

or

even

another

chromosome

being

joined

before

being

spliced

Clearly

the

classical

concept

of

the

gene

as

a

locus

no

longer

applies

for

these

gene

products

whose

DNA

sequences

are

widely

separated

across

the

genome

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Gerstein

et

al.

Table

Phenomena

complicating

the

concept

of

the

gene

Phenomenon

Gene

location

and

structure

Intronic

genes

Genes

with

overlapping

reading

frames

Enhancers

silencers

Description

Issue

A

gene

exists

within

an

intron

of

another

-LRB-

Henikoff

et

al.

-RRB-

A

DNA

region

may

code

for

two

different

protein

products

in

different

reading

frames

-LRB-

Contreras

et

al.

-RRB-

Distant

regulatory

elements

-LRB-

Spilianakis

et

al.

-RRB-

Two

genes

in

the

same

locus

No

one-to-one

correspondence

between

DNA

and

protein

sequence

DNA

sequences

determining

expression

can

be

widely

separated

from

one

another

in

genome

Many-to-many

relationship

between

genes

and

their

enhancers

A

genetic

element

may

be

not

constant

in

its

location

Gene

structure

is

not

hereditary

or

structure

may

differ

across

individuals

or

cells/tissues

Genetic

elements

may

differ

in

their

number

Structural

variation

Mobile

elements

Gene

rearrangements/structural

variants

Copy-number

variants

Genetic

element

appears

in

new

locations

over

generations

-LRB-

McClintock

-RRB-

DNA

rearrangement

or

splicing

in

somatic

cells

results

in

many

alternative

gene

products

-LRB-

Early

et

al.

-RRB-

Copy

number

of

genes/regulatory

elements

may

differ

between

individuals

-LRB-

Iafrate

et

al.

Sebat

et

al.

Tuzun

et

al.

-RRB-

Inherited

information

may

not

be

DNA-sequence

based

-LRB-

e.g.

Dobrovic

et

al.

-RRB-

a

gene

's

expression

depends

on

whether

it

is

of

paternal

or

maternal

origin

-LRB-

Sager

and

Kitchin

-RRB-

Chromatin

structure

which

does

influence

gene

expression

only

loosely

associated

with

particular

DNA

sequences

-LRB-

Paul

-RRB-

One

transcript

can

generate

multiple

mRNAs

resulting

in

different

protein

products

-LRB-

Berget

et

al.

Gelinas

and

Roberts

-RRB-

Alternative

reading

frames

of

the

tumor

suppressor

gene

encodes

two

unrelated

proteins

-LRB-

Quelle

et

al.

-RRB-

Distant

DNA

sequences

can

code

for

transcripts

ligated

in

various

combinations

-LRB-

Borst

-RRB-

Two

identical

transcripts

of

a

gene

can

trans-splice

to

generate

an

mRNA

where

the

same

exon

sequence

is

repeated

-LRB-

Takahara

et

al.

-RRB-

RNA

is

enzymatically

modified

-LRB-

Eisen

-RRB-

Epigenetics

and

chromosome

structure

Epigenetic

modifications

imprinting

Phenotype

is

not

determined

strictly

by

genotype

Effect

of

chromatin

structure

Gene

expression

depends

on

packing

of

DNA

DNA

sequence

is

not

enough

to

predict

gene

product

Multiple

products

from

one

genetic

locus

information

in

DNA

not

linearly

related

to

that

on

protein

Two

alternative

splicing

products

of

a

pre-mRNA

produce

protein

products

with

no

sequence

in

common

A

protein

can

result

from

the

combined

information

encoded

in

multiple

transcripts

Post-transcriptional

events

Alternative

splicing

of

RNA

Alternatively

spliced

products

with

alternate

reading

frames

RNA

trans-splicing

homotypic

trans-splicing

RNA

editing

Post-translational

events

Protein

splicing

viral

polyproteins

Protein

trans-splicing

Protein

modification

Pseudogenes

and

retrogenes

Retrogenes

The

information

on

the

DNA

is

not

encoded

directly

into

RNA

sequence

Start

and

end

sites

of

protein

not

determined

by

genetic

code

Start

and

end

sites

of

protein

not

determined

by

genetic

code

The

information

on

the

DNA

is

not

encoded

directly

into

protein

sequence

RNA-to-DNA

flow

of

information

Protein

product

self-cleaves

and

can

generate

multiple

functional

products

-LRB-

Villa-Komaroff

et

al.

-RRB-

Distinct

proteins

can

be

spliced

together

in

the

absence

of

a

trans-spliced

transcript

-LRB-

Handa

et

al.

-RRB-

Protein

is

modified

to

alter

structure

and

function

of

the

final

product

-LRB-

Wold

-RRB-

A

retrogene

is

formed

from

reverse

transcription

of

its

parent

gene

's

mRNA

-LRB-

Vanin

et

al.

-RRB-

and

by

insertion

of

the

DNA

product

into

a

genome

A

pseudogene

is

transcribed

-LRB-

Zheng

et

al.

-RRB-

Transcribed

pseudogenes

Biochemical

activity

of

supposedly

dead

elements

Finally

a

number

of

recent

studies

have

highlighted

a

phenomenon

dubbed

tandem

chimerism

where

two

consecutive

genes

are

transcribed

into

a

single

RNA

-LRB-

Akiva

et

al.

Parra

et

al.

-RRB-

The

translation

-LRB-

after

splicing

-RRB-

of

such

RNAs

can

lead

to

a

new

fused

protein

having

parts

from

both

original

proteins

Parasitic

and

mobile

genes

A

challenge

to

our

concept

of

the

gene

has

been

that

of

the

selfish

or

parasitic

gene

The

idea

first

proposed

by

Richard

Dawkins

is

that

the

unit

of

evolution

is

not

the

organism

but

the

gene

-LRB-

Dawkins

-RRB-

Organisms

are

just

tools

that

genes

use

to

rep

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

What

is

a

gene

licate

themselves

Dawkins

concept

of

the

optimon

-LRB-

or

selecton

-RRB-

is

a

unit

of

DNA

that

survives

recombination

for

enough

generations

to

be

selected

for

together

The

term

parasitic

certainly

appears

appropriate

for

transposons

whose

only

function

is

to

replicate

themselves

and

which

do

not

provide

any

obvious

benefit

to

the

organism

Transposons

can

change

their

locations

in

addition

to

copying

themselves

by

excision

recombination

or

reverse

transcription

They

were

first

discovered

in

the

in

maize

and

were

later

found

to

exist

in

all

branches

of

life

including

humans

-LRB-

McClintock

-RRB-

Transposons

have

altered

our

view

of

the

gene

by

demonstrating

that

a

gene

is

not

fixed

in

its

location

Unannotated

and

alternative

TSSs

A

second

observation

is

that

there

are

a

large

number

of

unannotated

transcription

start

sites

-LRB-

TSSs

-RRB-

identified

by

either

sequencing

of

the

end

of

transcribed

mRNAs

or

the

mapping

of

promoter-associated

transcription

factors

via

ChIP

chip

or

ChIP

PET

-LRB-

The

ENCODE

Project

Consortium

-RRB-

Furthermore

the

consortium

found

that

many

known

protein

genes

have

alternative

TSSs

that

are

sometimes

kb

upstream

of

the

annotated

transcription

start

site

In

particular

Denoeud

et

al.

-LRB-

-RRB-

performed

rapid

amplification

of

cDNA

ends

-LRB-

RACE

-RRB-

on

all

well-characterized

protein-coding

loci

contained

in

the

ENCODE

regions

The

RACE

primer

was

selected

from

a

exon

that

was

shared

among

most

annotated

transcripts

from

each

locus

and

the

RACE

products

were

hybridized

to

arrays

and

mapped

They

found

that

more

than

half

of

the

loci

had

an

alternative

transcription

start

site

upstream

of

the

known

site

in

at

least

one

of

the

tissues

tested

Some

of

these

distal

TSSs

used

the

promoter

of

an

entirely

different

gene

locus

-LRB-

i.e.

they

share

the

same

transcription

start

site

-RRB-

The

significance

of

this

discovery

is

that

the

alternative

TSS

for

some

of

these

transcripts

started

two

or

three

gene

loci

upstream

of

the

locus

from

which

the

RACE

primer

was

selected

Thus

some

alternative

isoforms

are

transcripts

that

span

multiple

gene

loci

-LRB-

A

cartoon

schematic

is

shown

in

Fig.

-RRB-

Many

of

the

alternative

isoforms

code

for

the

same

protein

differing

only

in

their

untranslated

regions

-LRB-

UTRs

-RRB-

The

large

amount

of

junk

DNA

under

selection

The

ORF

sequence

pattern

concept

of

the

gene

as

it

existed

from

the

onward

made

it

clear

that

there

were

large

expanses

of

nongenic

elements

in

eukaryotic

genomes

particularly

the

human

genome

In

the

absence

of

knowledge

of

a

function

for

these

regions

it

was

proposed

that

they

lacked

a

function

by

some

who

used

the

label

of

junk

DNA

-LRB-

Ohno

-RRB-

This

was

underscored

by

the

subsequent

sequencing

of

the

human

genome

where

it

was

shown

that

only

of

the

DNA

bases

code

for

exons

-LRB-

Lander

et

al.

Venter

et

al.

-RRB-

However

some

early

pilot

functional

genomics

experiments

on

chromosomes

and

indicated

that

appreciable

amounts

of

the

supposedly

junk

DNA

were

transcribed

-LRB-

Kapranov

et

al.

Rinn

et

al.

-RRB-

Moreover

comparison

of

the

human

dog

mouse

and

other

vertebrate

genomes

showed

that

a

large

fraction

of

these

was

conserved

with

under

negative

selection

since

the

divergence

of

these

species

-LRB-

Waterston

et

al.

Lindblad-Toh

et

al.

-RRB-

More

alternative

splicing

Taking

these

findings

into

account

the

Havana

team

at

the

Sanger

Institute

produced

the

well-curated

GENCODE

annotation

-LRB-

Harrow

et

al.

-RRB-

They

have

not

found

that

the

number

of

known

protein-coding

gene

loci

has

increased

significantly

over

time

Conversely

the

number

of

annotated

alternative

isoforms

per

locus

has

increased

-LRB-

The

GENCODE

annotation

currently

contains

on

average

transcripts

per

locus

-RRB-

Thus

while

part

of

the

large

amount

of

new

unannotated

transcription

could

correspond

to

entirely

new

protein-coding

gene

loci

most

of

it

is

likely

to

correspond

to

segments

of

unannotated

alternatively

spliced

transcripts

involving

known

gene

loci

or

to

entirely

novel

noncoding

RNAs

The

modern

ENCODE

view

of

dispersed

genome

activity

As

described

above

before

the

advent

of

the

ENCODE

project

there

were

a

number

of

aspects

of

genes

that

were

very

complicated

but

much

of

this

complexity

was

in

some

sense

swept

under

the

rug

and

did

not

really

affect

the

fundamental

definition

of

a

gene

The

experience

of

the

ENCODE

project

particularly

the

mapping

of

transcriptional

activity

and

regulation

using

tiling

arrays

has

extended

these

puzzling

and

confusing

aspects

of

genes

bringing

them

to

the

forefront

where

one

has

to

grapple

more

directly

with

them

in

relation

to

the

definition

of

what

a

gene

is

Dispersed

regulation

As

schematized

in

Figure

the

ENCODE

project

has

provided

evidence

for

dispersed

regulation

spread

throughout

the

genome

-LRB-

The

ENCODE

Project

Consortium

-RRB-

Moreover

the

regulatory

sites

for

a

given

gene

are

not

necessarily

directly

upstream

of

it

and

can

in

fact

be

located

far

away

on

the

chromosome

closer

to

another

gene

While

the

binding

of

many

transcription

factors

appears

to

blanket

the

entire

genome

it

is

not

arranged

according

to

simple

random

expectations

and

tends

to

be

clumped

into

regulatory

rich

forests

and

poor

deserts

-LRB-

Zhang

et

al.

-RRB-

Moreover

it

appears

that

some

of

regulatory

elements

may

actually

themselves

be

transcribed

In

a

conventional

and

concise

gene

model

a

DNA

element

-LRB-

e.g.

promoter

enhancer

and

insulator

-RRB-

regulating

gene

expression

is

not

transcribed

and

thus

is

not

part

of

a

gene

's

transcript

However

many

early

studies

have

discovered

in

specific

cases

that

regulatory

elements

can

reside

in

transcribed

regions

such

as

the

lac

operator

-LRB-

Jacob

and

Monod

-RRB-

an

enhancer

for

regulating

the

beta-globin

gene

-LRB-

Tuan

et

al.

-RRB-

and

the

DNA

binding

site

of

factor

-LRB-

Shi

et

al.

-RRB-

The

ENCODE

project

and

other

recent

ChIP

chip

ex

What

the

ENCODE

experiments

show

Lattices

of

long

transcripts

and

dispersed

regulation

Unannotated

transcription

A

first

finding

from

the

ENCODE

consortium

that

has

reproduced

earlier

results

-LRB-

Bertone

et

al.

Cheng

et

al.

-RRB-

is

that

a

vast

amount

of

DNA

not

annotated

as

known

genes

is

transcribed

into

RNA

-LRB-

The

ENCODE

Project

Consortium

-RRB-

These

novel

transcribed

regions

are

usually

called

TARs

-LRB-

i.e.

transcriptionally

active

regions

-RRB-

and

transfrags

While

the

majority

of

the

genome

appears

to

be

transcribed

at

the

level

of

primary

transcripts

only

about

half

of

the

processed

-LRB-

spliced

-RRB-

transcription

detected

across

all

the

cell

lines

and

conditions

mapped

is

currently

annotated

as

genes

Genome

Research

Downloaded

from

on

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by

Cold

Spring

Harbor

Laboratory

Press

Gerstein

et

al.

there

is

less

of

a

distinction

to

be

made

between

genic

and

intergenic

regions

Genes

now

appear

to

extend

into

what

was

once

called

intergenic

space

with

newly

discovered

transcripts

originating

from

additional

regulatory

sites

Moreover

there

is

much

activity

between

annotated

genes

in

the

intergenic

space

Two

well-characterized

sources

can

contribute

to

this

transcribed

non-proteincoding

RNAs

-LRB-

ncRNAs

-RRB-

and

transcribed

pseudogenes

and

an

appreciable

fraction

of

these

transcribed

elements

are

under

evolutionary

constraint

A

number

of

these

transcribed

pseudogenes

and

ncRNA

genes

are

in

fact

located

within

introns

of

protein-coding

genes

One

can

not

simply

ignore

these

components

within

introns

because

some

of

them

may

influence

the

expression

of

their

host

genes

either

directly

or

indirectly

Noncoding

RNAs

The

roles

of

ncRNA

genes

are

quite

diverse

including

gene

regulation

-LRB-

e.g.

miRNAs

-RRB-

RNA

processing

-LRB-

e.g.

snoRNAs

-RRB-

and

protein

synthesis

-LRB-

tRNAs

and

rRNA

-RRB-

-LRB-

Eddy

Mattick

and

Makunin

-RRB-

Due

to

the

lack

of

codons

and

thus

open

reading

frames

ncRNA

genes

are

hard

to

identify

and

thus

probably

only

a

fraction

of

the

functional

ncRNAs

in

humans

is

known

Figure

Biological

complexity

revealed

by

ENCODE

-LRB-

A

-RRB-

Representation

of

a

typical

genomic

reto

date

with

the

exception

of

the

ones

gion

portraying

the

complexity

of

transcripts

in

the

genome

-LRB-

Top

-RRB-

DNA

sequence

with

annotated

with

the

strongest

evolutionary

and/or

exons

of

genes

-LRB-

black

rectangles

-RRB-

and

novel

TARs

-LRB-

hollow

rectangles

-RRB-

-LRB-

Bottom

-RRB-

The

various

transcripts

structural

constraints

which

can

be

that

arise

from

the

region

from

both

the

forward

and

reverse

strands

-LRB-

Dashed

lines

-RRB-

Spliced-out

introns

Conventional

gene

annotation

would

account

for

only

a

portion

of

the

transcripts

coming

identified

computationally

through

from

the

four

genes

in

the

region

-LRB-

indicated

-RRB-

Data

from

the

ENCODE

project

reveal

that

many

RNA

folding

and

coevolution

analyses

transcripts

are

present

that

span

across

multiple

gene

loci

some

using

distal

transcription

start

sites

-LRB-

e.g.

miRNAs

that

display

characteristic

-LRB-

B

-RRB-

Representation

of

the

various

regulatory

sequences

identified

for

a

target

gene

For

Gene

we

show

hairpin-shaped

precursor

structures

or

all

the

component

transcripts

including

many

novel

isoforms

in

addition

to

all

the

sequences

idenncRNAs

in

ribonucleoprotein

complexes

tified

to

regulate

Gene

-LRB-

gray

circles

-RRB-

We

observe

that

some

of

the

enhancer

sequences

are

actually

promoters

for

novel

splice

isoforms

Additionally

some

of

the

regulatory

sequences

for

Gene

might

that

in

combination

with

peptides

form

actually

be

closer

to

another

gene

and

the

target

would

be

misidentified

if

chosen

purely

based

on

specific

secondary

structures

-RRB-

-LRB-

Washietl

proximity

et

al.

Pedersen

et

al.

-RRB-

However

the

example

of

the

large

periments

have

provided

large-scale

evidence

that

the

concise

XIST

gene

involved

in

dosage

compensation

shows

that

funcgene

model

may

be

too

simple

and

many

regulatory

elements

tional

ncRNAs

can

expand

significantly

beyond

constrained

actually

reside

within

the

first

exon

introns

or

the

entire

body

of

computationally

identifiable

regions

-LRB-

Chureau

et

al.

Duret

a

gene

-LRB-

Cawley

et

al.

Euskirchen

et

al.

Kim

et

al.

et

al.

-RRB-

The

ENCODE

Project

Consortium

Zhang

et

al.

-RRB-

It

is

also

possible

that

the

RNA

products

themselves

do

not

have

a

function

but

rather

reflect

or

are

important

for

a

particular

cellular

process

For

example

transcription

of

a

regulatory

Genic

versus

intergenic

Is

there

a

distinction

region

might

be

important

for

chromatin

accessibility

for

transcription

factor

binding

or

for

DNA

replication

Such

transcripOverall

the

ENCODE

experiments

have

revealed

a

rich

tapestry

tion

has

been

found

in

the

locus

control

region

-LRB-

LCR

-RRB-

of

the

of

transcription

involving

alternative

splicing

covering

the

gebeta-globin

locus

and

polymerase

activity

has

been

suggested

to

nome

in

a

complex

lattice

of

transcripts

According

to

traditional

be

important

for

DNA

replication

in

E.

coli

Alternatively

trandefinitions

genes

are

unitary

regions

of

DNA

sequence

separated

scription

might

reflect

nonspecific

activity

of

a

particular

region

from

each

other

ENCODE

reveals

that

if

one

attempts

to

define

for

example

the

recruitment

of

polymerase

to

regulatory

sites

In

a

gene

on

the

basis

of

shared

overlapping

transcripts

then

many

either

of

these

scenarios

the

transcripts

themselves

would

lack

a

annotated

distinct

gene

loci

coalesce

into

bigger

genomic

refunction

and

be

unlikely

to

be

conserved

gions

One

obvious

implication

of

the

ENCODE

results

is

that

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

What

is

a

gene

Pseudogenes

Pseudogenes

are

yet

another

group

of

mysterious

genomic

components

that

are

often

found

in

introns

of

genes

or

in

intergenic

space

-LRB-

Torrents

et

al.

Zhang

et

al.

-RRB-

They

are

derived

from

functional

genes

-LRB-

through

retrotransposition

or

duplication

-RRB-

but

have

lost

the

original

functions

of

their

parental

genes

-LRB-

Balakirev

and

Ayala

-RRB-

Sometimes

swinging

between

dead

and

alive

pseudogenes

can

influence

the

structure

and

function

of

the

human

genome

Their

prevalence

-LRB-

as

many

as

protein-coding

genes

-RRB-

and

their

close

similarity

to

functional

genes

have

already

confounded

gene

annotation

Recently

it

has

also

been

found

that

a

significant

fraction

-LRB-

up

to

-RRB-

of

them

are

transcriptionally

alive

suggesting

that

care

has

to

be

taken

when

using

expression

as

evidence

for

locating

genes

-LRB-

Yano

et

al.

Harrison

et

al.

Zheng

et

al.

Frith

et

al.

-RRB-

Indeed

some

of

the

novel

TARs

can

be

attributed

to

pseudogene

transcription

-LRB-

Bertone

et

al.

Zheng

et

al.

-RRB-

In

a

few

surprising

cases

a

pseudogene

RNA

or

at

least

a

piece

of

it

was

found

to

be

spliced

with

the

transcript

of

its

neighboring

gene

to

form

a

gene

pseudogene

chimeric

transcript

These

findings

add

one

extra

layer

of

complexity

to

establishing

the

precise

structure

of

a

gene

locus

Furthermore

functional

pseudogene

transcripts

have

also

been

discovered

in

eukaryotic

cells

such

as

the

neurons

of

the

snail

Lymnaea

stagnalis

-LRB-

Korneev

et

al.

-RRB-

Also

interestingly

the

human

XIST

gene

mentioned

above

actually

arises

from

the

dead

body

of

a

pseudogene

-LRB-

Duret

et

al.

-RRB-

Pseudogene

transcription

and

the

blurring

boundary

between

genes

and

pseudogenes

-LRB-

Zheng

and

Gerstein

-RRB-

emphasizes

once

more

that

the

functional

nature

of

many

novel

TARs

needs

to

be

resolved

by

future

biochemical

or

genetic

experiments

-LRB-

for

review

see

Gingeras

-RRB-

tive

calls

to

a

discrete

subroutine

in

a

normal

computer

OS

However

the

framework

of

describing

the

genome

as

executed

code

still

has

some

merit

That

is

one

can

still

understand

gene

transcription

in

terms

of

parallel

threads

of

execution

with

the

caveat

that

these

threads

do

not

follow

canonical

modular

subroutine

structure

Rather

threads

of

execution

are

intertwined

in

a

rather

higgledy-piggledy

fashion

very

much

like

what

would

be

described

as

a

sloppy

unstructured

computer

program

code

with

lots

of

GOTO

statements

zipping

in

and

out

of

loops

and

other

constructs

The

importance

of

gene

models

for

interpreting

the

high-throughput

experiment

in

ENCODE

Given

the

provocative

findings

of

the

ENCODE

project

one

wonders

to

what

degree

the

interpretation

of

the

highthroughput

experiments

can

be

pushed

This

interpretation

is

in

fact

very

contingent

on

using

gene

models

Aspects

of

interpreting

tiling

array

data

A

large

part

of

the

transcription

data

was

generated

using

highdensity

tiling

microarrays

-LRB-

Emanuelsson

et

al.

Rozowsky

et

al.

The

ENCODE

Project

Consortium

-RRB-

The

advantage

of

such

arrays

is

that

they

probe

the

transcription

in

an

unbiased

and

detailed

way

with

no

preconceptions

as

to

where

to

look

for

activity

On

the

other

hand

the

output

from

a

tiling

array

experiment

can

be

noisy

and

needs

careful

interpretation

in

order

to

allow

the

collection

of

a

reliable

set

of

transcribed

regions

The

amount

of

detected

transcription

depends

heavily

on

the

thresholds

used

when

calling

transcribed

regions

and

to

some

extent

also

on

the

segmentation

algorithms

used

to

delineate

transcribed

regions

from

nontranscribed

regions

Furthermore

since

the

ENCODE

transcription

mapping

-LRB-

and

other

-RRB-

experiments

were

carried

out

on

many

different

tissues

and

cell

lines

direct

comparison

between

experiments

is

not

trivial

and

the

overlap

between

different

transcription

maps

is

sometimes

quite

low

partly

due

to

the

variable

biological

features

of

the

samples

used

in

the

experiments

The

exact

expected

outcome

of

a

transcription

mapping

experiment

the

true

transcription

map

is

of

course

unknown

Thus

a

crucial

part

of

interpreting

transcription

mapping

tiling

array

data

is

to

understand

how

the

signal

is

different

from

various

random

expectations

-LRB-

models

-RRB-

A

naive

way

to

achieve

this

goal

is

to

randomize

the

raw

data

and

then

apply

all

the

normalizing

scoring

and

segmentation

schemes

-LRB-

with

unchanged

parameters

-RRB-

to

get

a

baseline

of

transcription

that

is

picked

up

using

supposedly

meaningless

data

But

it

is

not

clear

that

this

is

the

best

way

to

do

it

GC-content

length

distribution

of

the

-LRB-

actual

or

expected

-RRB-

transcribed

regions

dinucleotide

composition

and

other

characteristics

should

also

be

factored

into

the

baseline

transcription

distribution

The

expected

outcome

also

depends

on

the

biological

sample

used

tissue

or

cell

line

developmental

stage

external

stimuli

etc.

Integration

of

transcription

maps

from

different

biological

sources

-LRB-

tissues

cell

lines

-RRB-

provides

greater

confidence

in

the

result

Constrained

elements

The

noncoding

intergenic

regions

contain

a

large

fraction

of

functional

elements

identified

by

examining

evolutionary

changes

across

multiple

species

and

within

the

human

population

The

ENCODE

project

observed

that

only

of

the

evolutionarily

constrained

bases

were

within

protein-coding

exons

or

their

associated

untranslated

regions

-LRB-

The

ENCODE

Project

Consortium

-RRB-

The

resolution

of

constrained

elements

identified

by

multispecies

analysis

in

the

ENCODE

project

is

very

high

identifying

sequences

as

small

as

bases

-LRB-

with

a

median

of

bases

-RRB-

-LRB-

The

ENCODE

Project

Consortium

-RRB-

This

suggests

that

protein-coding

loci

can

be

viewed

as

a

cluster

of

small

constrained

elements

dispersed

in

a

sea

of

unconstrained

sequences

Approximately

another

of

the

constrained

elements

overlap

with

experimentally

annotated

regulatory

regions

Therefore

a

similar

fraction

of

constrained

elements

-LRB-

in

terms

of

bases

-RRB-

is

located

in

protein-coding

regions

as

unannotated

noncoding

regions

-LRB-

coding

regulatory

regions

-RRB-

suggesting

that

the

latter

may

be

as

functionally

important

as

the

former

The

ENCODE

computational

metaphor

Genes

as

loosely

coded

routines

The

new

ENCODE

perspective

does

not

of

course

fit

with

the

metaphor

of

the

gene

as

a

simple

callable

routine

in

a

huge

operating

system

In

this

new

perspective

one

enters

a

gene

routine

in

many

different

ways

in

the

framework

of

alternative

splicing

and

lattices

of

long

transcripts

The

execution

of

the

genomic

OS

does

not

have

as

neat

a

quality

as

this

idea

of

repeti

Genes

as

statistical

models

summarizing

many

experiments

In

the

context

of

interpreting

high-throughput

experiments

such

as

tiling

arrays

the

concept

of

a

gene

has

an

added

practical

importance

as

a

statistical

model

to

help

interpret

and

provide

concise

summarization

to

potentially

noisy

experimental

data

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Gerstein

et

al.

lyze

the

remainder

of

the

tiling

array

data

In

a

specific

case

when

analyzing

tiling

array

data

using

a

hidden

Markov

model

-LRB-

Du

et

al.

-RRB-

if

the

validation

regions

are

selected

to

achieve

maximum

signal

entropy

the

MaxEntropy

selection

scheme

the

resulting

gene

segmentation

model

outperforms

others

For

transcriptional

tiling

arrays

MaxEntropy

will

generally

select

regions

containing

both

exons

and

introns

Toward

an

updated

definition

of

a

gene

As

we

have

described

above

our

knowledge

of

genes

has

evolved

greatly

over

the

past

century

While

our

understandFigure

Training

statistical

gene

models

based

on

high-density

oligonucleotide

tiling

microarray

ing

has

grown

we

have

also

uncovered

data

-LRB-

A

-RRB-

Large-scale

signal

data

from

tiling

array

experiments

can

be

used

to

train

statistical

models

to

an

increasing

number

of

problematic

asscore

the

hits

and

a

small/medium

proportion

of

these

results

can

be

further

validated

by

experiments

pects

with

simple

definitions

of

a

gene

or

other

biological

knowledge

via

runs

of

iterations

and

optimizations

-LRB-

B

-RRB-

Different

strategies

can

be

-LRB-

Table

-RRB-

Splicing

-LRB-

including

alternative

used

to

select

genomic

regions

for

validation

e.g.

-LRB-

-RRB-

select

only

the

regions

with

high

signals

-LRB-

-RRB-

splicing

-RRB-

and

intergenic

transcription

select

regions

randomly

or

-LRB-

-RRB-

select

those

that

have

the

maximum

signal

entropies

which

usually

contain

borders

of

high

and

low

signals

One

question

worth

asking

is

whether

an

optimal

way

of

are

obviously

some

of

the

most

problemselection

exists

to

best

help

in

training

the

statistical

model

atic

aspects

As

shown

in

Figure

the

frequency

of

mention

of

these

terms

in

For

example

the

transcriptional

tiling

array

experiments

ultithe

biological

literature

has

been

increasing

considerably

Thus

mately

identify

TARs/transfrags

which

usually

correspond

to

the

the

stage

was

set

for

the

ENCODE

project

and

the

great

complexexons

in

genes

Therefore

the

most

appropriate

gene

models

to

ity

in

transcriptional

and

regulatory

apparatus

that

it

highbe

considered

can

be

splicing

graphs

-LRB-

Heber

et

al.

-RRB-

reprelighted

At

this

point

it

is

not

clear

what

to

do

In

the

extreme

senting

exons

as

nodes

and

splicing

events

as

directed

edges

we

could

declare

the

concept

of

the

gene

dead

and

try

to

come

up

In

order

to

build

and

adjust

statistical

models

for

experimenwith

something

completely

new

that

fits

all

the

data

However

it

tal

interpretation

other

related

biological

knowledge

-LRB-

e.g.

gene

would

be

hard

to

do

this

with

consistency

Here

we

made

a

annotation

and

experimental

validation

data

-RRB-

needs

to

be

comtentative

attempt

at

a

compromise

devising

updates

and

patches

bined

with

the

high-throughput

array

data

For

instance

the

for

the

existing

definition

of

a

gene

transcriptional

array

data

can

identify

isolated

transcribed

reCriteria

to

consider

in

updating

the

definition

gions

and

experimental

validation

such

as

RACE

can

provide

connectivity

information

Using

these

data

together

the

statisFirst

we

consider

several

criteria

to

be

important

while

coming

tical

models

can

be

better

trained

and

can

then

be

used

to

anaup

with

an

updated

definition

for

a

gene

-LRB-

-RRB-

A

new

definition

lyze

the

rest

of

the

high-throughput

data

that

are

not

covered

by

must

attempt

to

be

backward

compatible

in

the

sense

that

somethe

validation

experiments

thing

that

used

to

be

called

a

gene

should

remain

a

gene

-LRB-

-RRB-

It

Different

statistical

models

-LRB-

Karplus

et

al.

Bertone

et

must

be

organism-independent

i.e.

be

as

valid

for

bacteria

as

for

a

al.

Schadt

et

al.

Gibbons

et

al.

Ji

and

Wong

virus

or

a

higher

eukaryote

-LRB-

-RRB-

It

should

be

a

statement

of

a

Li

et

al.

Du

et

al.

Marioni

et

al.

-RRB-

have

been

simple

idea

rather

than

listing

various

mechanisms

and

excepproposed

to

explain

the

generation

of

the

tiling

array

data

As

tions

-LRB-

-RRB-

It

should

be

practical

enough

so

that

one

can

readily

shown

in

Figure

these

models

can

be

trained

using

the

tiling

enumerate

genes

and

answer

a

question

like

How

many

genes

are

array

data

and

other

biological

knowledge

and

then

extrapolated

there

in

the

human

genome

-LRB-

-RRB-

It

should

be

compatible

with

to

the

whole

genome

sequence

to

best

segment

it

into

functional

other

biological

nomenclature

that

makes

use

of

the

idea

of

a

digital

elements

As

more

and

more

biological

knowledge

is

accumugene

For

instance

it

should

be

consistent

with

term

regulome

lated

especially

via

the

experimental

validation

of

predicted

which

represents

the

complete

set

of

regulatory

interactions

in

functional

regions

generated

by

the

analysis

procedure

we

can

an

organism

expect

that

the

models

will

be

better

trained

thus

leading

to

refined

analysis

results

of

these

experiments

However

it

will

be

A

proposed

updated

definition

impractical

to

validate

every

single

functional

element

identified

There

are

three

aspects

to

the

definition

that

we

will

list

below

by

tiling

experiments

using

RT-PCR

or

RACE

For

each

tiling

array

before

providing

the

succinct

definition

experiment

perhaps

only

a

medium-sized

set

of

predicted

functional

regions

will

be

validated

experimentally

A

gene

is

a

genomic

sequence

-LRB-

DNA

or

RNA

-RRB-

directly

encoding

As

shown

in

Figure

the

regions

for

experimental

validafunctional

product

molecules

either

RNA

or

protein

tion

can

be

picked

using

different

strategies

It

is

obviously

In

the

case

that

there

are

several

functional

products

sharing

eficial

to

pick

these

regions

in

an

optimal

way

so

that

the

model

overlapping

regions

one

takes

the

union

of

all

overlapping

trained

based

on

these

validation

results

can

most

accurately

anagenomic

sequences

coding

for

them

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

What

is

a

gene

quences

coding

for

them

reside

in

separate

locations

in

the

genome

and

so

they

would

not

constitute

one

gene

Frameshifted

exons

There

are

cases

such

as

that

of

the

-LRB-

formerly

-RRB-

tumor

suppressor

gene

-LRB-

e.g.

Quelle

et

al.

-RRB-

when

a

pre-mRNA

can

be

alternatively

spliced

to

generate

an

mRNA

with

a

frameshift

in

the

protein

sequence

Thus

although

the

two

mRNAs

have

coding

sequences

in

common

the

protein

products

may

be

completely

different

This

rather

unusual

case

brings

up

the

question

of

how

exactly

sequence

identity

is

to

be

handled

when

taking

the

union

of

sequence

segments

that

are

shared

among

protein

products

If

one

considers

the

sequence

of

the

protein

Figure

Keyword

analysis

and

complexity

of

genes

Using

Google

Scholar

a

full-text

search

of

products

there

are

two

unrelated

proscientific

articles

was

performed

for

the

keywords

intron

alternative

splicing

and

intergenic

teins

so

there

must

be

two

genes

with

transcription

Slopes

of

curves

indicate

that

in

recent

years

the

frequency

of

mentioning

of

terms

relating

to

the

complexity

of

a

gene

has

increased

-LRB-

The

Google

Scholar

search

was

limited

to

articles

overlapping

sequence

sets

If

one

in

the

following

subject

areas

Biology

Life

Sciences

and

Environmental

Science

Chemistry

and

projects

the

sequence

of

the

protein

Materials

Science

Medicine

Pharmacology

and

Veterinary

Science

-RRB-

products

back

to

the

DNA

sequence

that

encoded

them

-LRB-

as

described

above

-RRB-

then

there

are

two

sequence

sets

with

common

elements

so

there

is

This

union

must

be

coherent

i.e.

done

separately

for

final

one

gene

The

fact

that

these

two

proteins

sequences

are

simulprotein

and

RNA

products

but

does

not

require

that

all

prodtaneously

constrained

such

that

a

mutation

in

one

of

them

ucts

necessarily

share

a

common

subsequence

would

simultaneously

affect

the

other

one

suggests

that

this

This

can

be

concisely

summarized

as

situation

is

not

akin

to

that

of

two

unrelated

protein-coding

genes

For

this

reason

generalizing

from

this

special

case

we

The

gene

is

a

union

of

genomic

sequences

encoding

a

coherent

favor

the

method

of

taking

the

union

of

the

sequence

segments

set

of

potentially

overlapping

functional

products

not

of

the

products

but

of

the

DNA

sequences

that

code

for

the

Figure

provides

an

example

to

illustrate

the

application

of

this

product

sequences

definition

Aspects

and

implications

of

the

definition

There

are

important

implications

of

this

definition

Regulatory

regions

not

included

Although

regulatory

regions

are

important

for

gene

expression

we

suggest

that

they

should

not

be

considered

in

deciding

whether

multiple

products

belong

to

the

same

gene

This

aspect

of

the

definition

results

from

our

concept

of

the

bacterial

operon

The

fact

that

genes

in

an

operon

share

an

operator

and

promoter

region

has

traditionally

not

been

considered

to

imply

that

their

protein

products

are

alternative

products

of

a

single

gene

Consequently

in

higher

eukaryotes

two

transcripts

that

originate

from

the

same

transcription

start

site

-LRB-

sharing

the

same

promoter

and

regulatory

elements

-RRB-

but

do

not

share

any

sequence

elements

in

their

final

products

-LRB-

e.g.

because

of

alternative

splicing

-RRB-

would

not

be

products

of

the

same

gene

A

similar

logic

would

apply

to

multiple

transcripts

sharing

a

common

but

distant

enhancer

or

insulator

Regulation

is

simply

too

complex

to

be

folded

into

the

definition

of

a

gene

and

there

is

obviously

a

many-to-many

-LRB-

rather

than

one-to-one

-RRB-

relationship

between

regulatory

regions

and

genes

Collapsing

in

simple

cases

In

simple

cases

where

the

gene

is

not

discontinuous

or

there

are

no

overlapping

products

our

definition

collapses

to

the

classical

version

of

being

a

DNA

sequence

that

codes

for

a

protein

or

RNA

product

Projecting

down

in

taking

union

In

our

proposed

definition

of

a

gene

different

functional

products

of

the

same

class

-LRB-

protein

or

RNA

-RRB-

that

overlap

in

their

usage

of

the

primary

DNA

sequence

are

combined

into

the

same

gene

This

overlap

is

done

by

projecting

the

sequence

of

the

final

product

-LRB-

either

amino

acid

or

RNA

sequence

-RRB-

down

onto

the

original

genomic

sequence

from

which

it

was

derived

One

could

in

principle

overlap

the

sequences

of

the

final

products

-LRB-

projecting

up

-RRB-

however

since

annotation

of

genes

is

done

for

genomic

DNA

we

think

our

choice

is

the

most

consistent

with

current

practice

An

obvious

point

that

should

still

be

stated

is

that

when

looking

at

genomic

products

with

common

sequence

segments

mere

sequence

identity

is

not

enough

the

products

have

to

be

encoded

directly

from

the

same

genomic

region

Thus

paralogous

proteins

may

share

sequence

blocks

but

DNA

se

Final

products

not

transcript

clusters

As

the

updated

definition

emphasizes

the

final

products

of

a

gene

it

disregards

intermediate

products

originating

from

a

genomic

region

that

may

happen

to

overlap

For

example

an

intronic

transcript

clearly

shares

sequences

with

an

overlapping

larger

transcript

but

this

fact

is

irrelevant

when

we

conclude

that

Genome

Research

Downloaded

from

on

May

Published

by

Cold

Spring

Harbor

Laboratory

Press

Gerstein

et

al.

When

using

a

strict

definition

of

regions

encoding

the

final

product

of

a

proteincoding

gene

these

regions

would

no

longer

be

considered

part

of

the

gene

as

is

often

the

case

in

current

usage

Moreover

protein-coding

transcripts

that

share

DNA

sequence

only

in

their

untranslated

regions

or

introns

would

not

be

clustered

together

into

a

common

gene

By

removing

UTRs

from

the

definition

of

a

gene

one

can

avoid

the

problem

of

multiple

and

ends

clouding

the

delineation

of

the

gene

and

also

avoid

a

situation

in

which

upstream

or

trans

leader

sequences

are

spliced

onto

a

protein

coding

sequence

Moreover

it

has

been

observed

that

most

of

the

longer

protein-coding

transcripts

identified

by

ENCODE

differ

only

in

their

UTRs

and

thus

our

definition

is

quite

transparent

to

this

degree

of

transcript

complexity

Figure

How

the

proposed

definition

of

the

gene

can

be

applied

to

a

sample

case

A

genomic

region

produces

three

primary

transcripts

After

alternative

splicing

products

of

two

of

these

encode

five

protein

products

while

the

third

encodes

for

a

noncoding

RNA

-LRB-

ncRNA

-RRB-

product

The

protein

products

are

encoded

by

three

clusters

of

DNA

sequence

segments

-LRB-

A

B

and

C

D

and

E

-RRB-

In

the

case

of

the

three-segment

cluster

-LRB-

A

B

C

-RRB-

each

DNA

sequence

segment

is

shared

by

at

least

two

of

the

products

Two

primary

transcripts

share

a

untranslated

region

but

their

translated

regions

D

and

E

do

not

overlap

There

is

also

one

noncoding

RNA

product

and

because

its

sequence

is

of

RNA

not

protein

the

fact

that

it

shares

its

genomic

sequences

-LRB-

X

and

Y

-RRB-

with

the

protein-coding

genomic

segments

A

and

E

does

not

make

it

a

co-product

of

these

protein-coding

genes

In

summary

there

are

four

genes

in

this

region

and

they

are

the

sets

of

sequences

shown

inside

the

orange

dashed

lines

Gene

consists

of

the

sequence

segments

A

B

and

C

gene

consists

of

D

gene

of

E

and

gene

of

X

and

Y

In

the

diagram

for

clarity

the

exonic

and

protein

sequences

A

E

have

been

lined

up

vertically

so

the

dashed

lines

for

the

spliced

transcripts

and

functional

products

indicate

connectivity

between

the

proteins

sequences

-LRB-

ovals

-RRB-

and

RNA

sequences

-LRB-

boxes

-RRB-

-LRB-

Solid

boxes

on

transcripts

-RRB-

Untranslated

sequences

-LRB-

open

boxes

-RRB-

translated

sequences

Gene-associated

regions

the

two

products

share

no

sequence

blocks

This

concept

can

be

generalized

to

other

types

of

discontinuous

genes

such

as

rearranged

genes

-LRB-

e.g.

in

the

immunoglobulin

gene

locus

the

C

segment

is

common

to

all

protein

products

encoded

from

it

-RRB-

or

trans-spliced

transcripts

-LRB-

where

one

pre-mRNA

can

be

spliced

to

a

number

of

other

pre-mRNAs

before

further

processing

and

translation

-RRB-

This

implies

that

the

number

of

genes

in

the

human

genome

is

going

to

increase

significantly

when

the

survey

of

the

human

transcriptome

is

completed

In

light

of

the

large

amount

of

intertwined

transcripts

that

were

identified

by

the

ENCODE

consortium

if

we

tried

to

cluster

entire

transcripts

together

to

form

overlapping

transcript

clusters

-LRB-

a

potential

alternate

definition

of

a

gene

-RRB-

then

we

would

find

that

large

segments

of

chromosomes

would

coalesce

into

these

clusters

This

alternate

definition

of

a

gene

would

result

in

far

fewer

genes

and

would

be

of

limited

utility

As

described

above

regulatory

and

untranslated

regions

that

play

an

important

part

in

gene

expression

would

no

longer

be

considered

part

of

the

gene

However

we

would

like

to

create

a

special

category

for

them

by

saying

that

they

would

be

gene-associated

In

this

way

these

regions

still

retain

their

important

role

in

contributing

to

gene

function

Moreover

their

ability

to

contribute

to

the

expression

of

several

genes

can

be

recognized

This

is

particularly

true

for

long-range

elements

such

as

the

betaglobin

LCR

which

contributes

to

the

expression

of

several

genes

and

will

likely

be

the

case

for

many

other

enhancers

as

their

true

gene

targets

are

mapped

It

can

also

be

applied

to

untranslated

regions

that

contribute

to

multiple

gene

loci

such

as

the

long

spliced

transcripts

observed

in

the

ENCODE

region

and

transspliced

exons

Disjointed

sets

of

genomic

sequence

For

clarity

in

the

discussion

we

refer

to

DNA

when

meaning

genomic

sequences

in

general

Our

proposed

definition

is

applicable

to

all

genomes

including

that

of

RNA

viruses

In

complex

cases

the

gene

turns

out

not

to

correspond

to

a

discrete

single

genetic

locus

as

sequences

coding

for

its

product

-LRB-

s

-RRB-

may

be

widely

separated

in

the

genome

In

particular

because

the

gene

is

a

set

of

sequences

shared

among

the

products

there

is

no

requirement

of

connectivity

between

these

sequences

and

the

sequences

that

happen

to

connect

them

need

not

be

part

of

the

gene

Thus

members

of

a

sequence

can

be

on

different

strands

of

a

chromosome

or

even

on

separate

chromosomes

This

means

that

trans-spliced

transcripts

belong

to

one

gene

Alternative

splicing

In

relation

to

alternatively

spliced

gene

products

there

is

the

possibility

that

no

one

coding

exon

is

shared

among

all

protein

products

In

this

case

it

is

understood

that

the

union

of

these

sequence

segments

defines

the

gene

as

long

as

each

exon

is

shared

among

at

least

two

members

of

this

group

of

products

UTRs

and

untranslated

regions

-LRB-

UTRs

-RRB-

play

important

roles

in

translation

regulation

stability

and/or

localization

of

mRNAs

Conclusion

What

is

function

The

classical

view

of

a

gene

as

a

unit

of

hereditary

information

aligned

along

a

chromosome

each

coding

for

one

protein

has

Genome

Research

Downloaded

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Published

by

Cold

Spring

Harbor

Laboratory

Press

What

is

a

gene

changed

dramatically

over

the

past

century

For

Morgan

genes

on

chromosomes

were

like

beads

on

a

string

The

molecular

biology

revolution

changed

this

idea

considerably

To

quote

Falk

-LRB-

-RRB-

the

gene

is

-LSB-

-RSB-

neither

discrete

-LSB-

-RSB-

nor

continuous

-LSB-

-RSB-

nor

does

it

have

a

constant

location

-LSB-

-RSB-

nor

a

clearcut

function

-LSB-

-RSB-

not

even

constant

sequences

-LSB-

-RSB-

nor

definite

borderlines

And

now

the

ENCODE

project

has

increased

the

complexity

still

further

What

has

not

changed

is

that

genotype

determines

phenotype

and

at

the

molecular

level

this

means

that

DNA

sequences

determine

the

sequences

of

functional

molecules

In

the

simplest

case

one

DNA

sequence

still

codes

for

one

protein

or

RNA

But

in

the

most

general

case

we

can

have

genes

consisting

of

sequence

modules

that

combine

in

multiple

ways

to

generate

products

By

focusing

on

the

functional

products

of

the

genome

this

definition

sets

a

concrete

standard

in

enumerating

unambiguously

the

number

of

genes

it

contains

An

important

aspect

of

our

proposed

definition

is

the

requirement

that

the

protein

or

RNA

products

must

be

functional

for

the

purpose

of

assigning

them

to

a

particular

gene

We

believe

this

connects

to

the

basic

principle

of

genetics

that

genotype

determines

phenotype

At

the

molecular

level

we

assume

that

phenotype

relates

to

biochemical

function

Our

intention

is

to

make

our

definition

backwardly

compatible

with

earlier

concepts

of

the

gene

This

emphasis

on

functional

products

of

course

highlights

the

issue

of

what

biological

function

actually

is

With

this

we

move

the

hard

question

from

what

is

a

gene

to

what

is

a

function

High-throughput

biochemical

and

mutational

assays

will

be

needed

to

define

function

on

a

large

scale

-LRB-

Lan

et

al.

-RRB-

Hopefully

in

most

cases

it

will

just

be

a

matter

of

time

until

we

acquire

the

experimental

evidence

that

will

establish

what

most

RNAs

or

proteins

do

Until

then

we

will

have

to

use

placeholder

terms

like

TAR

or

indicate

our

degree

of

confidence

in

assuming

function

for

a

genomic

product

We

may

also

be

able

to

infer

functionality

from

the

statistical

properties

of

the

sequence

-LRB-

e.g.

Ponjavic

et

al.

-RRB-

However

we

probably

will

not

be

able

to

ever

know

the

function

of

all

molecules

in

the

genome

It

is

conceivable

that

some

genomic

products

are

just

noise

i.e.

results

of

evolutionarily

neutral

events

that

are

tolerated

by

the

organism

-LRB-

e.g.

Tress

et

al.

-RRB-

Or

there

may

be

a

function

that

is

shared

by

so

many

other

genomic

products

that

identifying

function

by

mutational

approaches

may

be

very

difficult

While

determining

biological

function

may

be

difficult

proving

lack

of

function

is

even

harder

-LRB-

almost

impossible

-RRB-

Some

sequence

blocks

in

the

genome

are

likely

to

keep

their

labels

of

TAR

of

unknown

function

indefinitely

If

such

regions

happen

to

share

sequences

with

functional

genes

their

boundaries

-LRB-

or

rather

the

membership

of

their

sequence

set

-RRB-

will

remain

uncertain

Given

that

our

definition

of

a

gene

relies

so

heavily

on

functional

products

finalizing

the

number

of

genes

in

our

genome

may

take

a

long

time

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We

thank

the

ENCODE

consortium

and

acknowledge

the

following

funding

sources

ENCODE

grant

from

the

National

Human

Genome

Research

Institute

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NHGRI

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National

Institutes

of

Health

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NIH

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NIH

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from

the

National

Library

of

Medicine

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C.B.

Z.D.Z.

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and

a

Marie

Curie

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J.O.K

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