Advances

in

Swine

Transcriptomics

The

past

five

years

have

seen

a

tremendous

rise

in

porcine

transcriptomic

data

Available

porcine

Expressed

Sequence

Tags

-LRB-

ESTs

-RRB-

have

expanded

greatly

with

over

ESTs

deposited

in

Genbank

ESTs

have

been

used

to

expand

the

pig-human

comparative

maps

but

such

data

has

also

been

used

in

many

ways

to

understand

pig

gene

expression

Several

methods

have

been

used

to

identify

genes

differentially

expressed

-LRB-

DE

-RRB-

in

specific

tissues

or

cell

types

under

different

treatments

These

include

open

screening

methods

such

as

suppression

subtractive

hybridization

differential

display

serial

analysis

of

gene

expression

and

EST

sequence

frequency

as

well

as

closed

methods

that

measure

expression

of

a

defined

set

of

sequences

such

as

hybridization

to

membrane

arrays

and

microarrays

The

use

of

microarrays

to

begin

large-scale

transcriptome

analysis

has

been

recently

reported

using

either

specialized

or

broad-coverage

arrays

This

review

covers

published

results

using

the

above

techniques

in

the

pig

as

well

as

unpublished

data

provided

by

the

research

community

and

reports

on

unpublished

Affymetrix

data

from

our

group

Published

and

unpublished

bioinformatics

efforts

are

discussed

including

recent

work

by

our

group

to

integrate

two

broad-coverage

microarray

platforms

We

conclude

by

predicting

experiments

that

will

become

possible

with

new

anticipated

tools

and

data

including

the

porcine

genome

sequence

We

emphasize

that

the

need

for

bioinformatics

infrastructure

to

efficiently

store

and

analyze

the

expanding

amounts

of

gene

expression

data

is

critical

and

that

this

deficit

has

emerged

as

a

limiting

factor

for

acceleration

of

genomic

understanding

in

the

pig

Overview

Dramatic

advances

in

our

understanding

of

the

porcine

transcriptome

have

occurred

over

the

past

decade

and

especially

in

the

past

few

years

The

pig

transcriptome

has

been

analyzed

to

address

biomedical

agricultural

and

fundamental

biological

questions

using

more

and

more

sensitive

and

comprehensive

tools

Few

reviews

of

porcine

transcriptional

profiling

have

been

published

Blomberg

and

Zuelke

recently

outlined

several

techniques

that

have

been

used

for

porcine

profiling

although

their

focus

was

on

serial

analysis

of

gene

expression

-LRB-

SAGE

-RRB-

This

review

will

specifically

discuss

results

in

pigs

using

the

major

technologies

of

EST

sequencing

PCR-centric

screening

analysis

and

assay

approaches

and

array

hybridization

methods

Due

to

space

limitations

in

this

review

we

will

not

describe

the

technical

aspects

of

each

technique

in

detail

there

are

many

reviews

and

specialized

resources

for

cDNA

library

and

EST

production

differential

display

PCR

SAGE

suppression

subtractive

hybridization

-LRB-

SSH

-RRB-

real-time

quantitative

PCR

and

of

course

microarray

based

techniques

Further

many

reports

have

been

made

using

techniques

such

as

differential

display

or

microarrays

to

identify

genes

differentially

expressed

in

biological

states

of

interest

The

majority

of

these

reports

use

a

porcine

tissue

or

cell

line

to

ask

questions

of

biomedical

interest

and

the

use

of

porcine-derived

biological

material

is

not

directly

relevant

to

the

study

Space

limitations

require

us

to

describe

in

detail

only

those

efforts

with

broad

interest

to

the

pig

genomics

community

All

papers

found

that

differential

display

screening

or

the

use

of

microarrays

in

assaying

expression

in

porcine

tissues

report

are

listed

in

Supplementary

Tables

and

respectively

Reports

on

EST

sequencing

will

be

discussed

but

we

will

not

discuss

publications

that

focus

on

physical

and/or

genetic

mapping

of

such

ESTs

Finally

while

still

in

its

infancy

we

will

discuss

published

and

other

publicly

reported

work

on

the

development

and

use

of

bioinformatics

and

databases

to

analyze

porcine

gene

expression

data

Tools

Techniques

and

Results

for

Porcine

Transcriptome

Analysis

Porcine

Expressed

Sequence

Tag

Projects

describe

Significant

Portions

of

the

Swine

Transcriptome

Soon

after

Adams

and

co-workers

suggested

that

the

sequencing

of

random

clones

from

cDNA

libraries

would

be

an

effective

means

to

obtain

human

gene

sequence

data

rapidly

researchers

have

been

reporting

porcine

ESTs

Many

groups

have

now

submitted

EST

sequence

data

Table

shows

the

projects

with

major

contributions

to

global

EST

sequencing

efforts

-LRB-

totaling

over

entries

-RRB-

The

NCBI

UniGene

website

for

pig

-LRB-

-RRB-

shows

over

libraries

have

more

than

EST

sequences

deposited

-LRB-

over

additional

libraries

with

less

than

sequences/library

have

been

reported

-RRB-

These

sequences

come

from

thirteen

categories

of

tissues

ranging

from

a

low

of

libraries

found

for

the

adipose

brain

and

conceptus

categories

to

libraries

in

the

genito-urinary

category

In

NCBI

Build

-LRB-

as

of

July

-RRB-

the

mRNAs

-LRB-

-RRB-

high-throughput

cDNAs

-LRB-

-RRB-

and

ESTs

-LRB-

-RRB-

have

been

clustered

into

UniGene

sets

On

the

other

hand

a

slightly

earlier

build

of

the

Porcine

Gene

Index

-LRB-

SsGI

Release

June

-LRB-

recently

moved

from

TIGR

to

Dana

Farber

Cancer

Institute

-RRB-

shows

ESTs

and

expressed

transcripts

from

a

total

of

cDNA

libraries

This

release

identifies

tentative

clusters

-LRB-

TCs

-RRB-

and

singleton

ESTs

and

ETs

Many

of

these

ESTs

have

been

submitted

within

the

past

three

years

showing

the

great

strides

taken

recently

since

January

-LRB-

Release

-RRB-

the

number

of

TCs

in

the

Pig

Gene

Index

has

nearly

tripled

Additional

information

on

these

databases

and

others

is

discussed

in

the

section

on

bioinformatics

In

addition

to

the

many

uses

for

such

sequencing

data

that

can

be

made

in

structural

biology

and

in

mapping

genes

this

large

amount

of

data

has

also

been

used

to

estimate

the

level

of

expression

of

a

gene

by

calculating

the

number

of

instances

when

the

transcript

has

been

randomly

sequenced

in

a

library

While

care

must

be

taken

in

such

comparisons

to

use

non-normalized

libraries

and

EST

data

of

sufficient

size

several

authors

have

discussed

such

estimates

Davoli

and

co-workers

used

EST

sequence

frequencies

to

compare

to

equivalent

data

for

human

transcripts

to

characterize

their

skeletal

muscle

library

similar

estimates

were

performed

by

Smith

and

others

to

identify

highly

expressed

genes

in

early

embryo

Several

groups

have

used

data

from

non-normalized

libraries

to

estimate

such

virtual

expression

patterns

across

multiple

tissues

or

developmental

stages

Using

sequence

frequencies

we

were

able

to

identify

genes

that

are

expressed

highly

selectively

in

one

tissue

as

well

as

genes

changing

expression

during

embryonic

development

through

calculating

frequencies

in

libraries

created

from

different

embryonic

stages

Jiang

and

colleagues

identified

sequence

clusters

that

were

over-represented

across

specific

stages

of

ovarian

follicle

development

and

between

growing

follicles

and

corpora

lutea

Whitworth

and

others

recognized

genes

showing

differential

frequency

in

very

early

embryogenesis

finding

many

transcripts

with

different

frequency

in

comparisons

between

unfertilized

oocytes

and

embryos

and

between

these

embryos

and

the

more

differentiated

blastocysts

Interestingly

they

found

transcripts

with

different

frequency

between

in

vivo

and

in

vitro

produced

four

cell

embryos

as

well

as

between

in

vivo

and

in

vitro

blastocysts

Differential

frequency

has

also

been

used

by

several

groups

to

determine

the

efficacy

of

normalization

of

cDNA

libraries

which

is

performed

to

remove

the

highly

expressed

-LRB-

and

therefore

high

frequency

-RRB-

transcripts

allowing

for

increased

efficiency

in

finding

new

gene

transcripts

through

random

EST

sequencing

Finally

both

UniGene

and

SsGI

-LRB-

now

the

Dana

Farber

Cancer

Institute

Pig

Gene

Index

-RRB-

provide

global

views

of

gene

expression

levels

based

on

EST

frequency

-LRB-

see

later

section

-RRB-

Through

comparison

of

frequencies

of

ESTs

across

species

it

is

possible

to

identify

species-specific

differences

in

expression

Zhao

et

al.

identified

a

highly

expressed

transcript

in

porcine

placenta

-LRB-

of

placenta

and

early

conceptus

sequences

available

-RRB-

which

had

no

ortholog

in

the

human

EST

database

although

hundreds

of

thousands

of

placenta

sequences

had

been

deposited

A

highly

similar

sequence

was

present

in

the

human

genome

with

a

conserved

open

reading

frame

Further

cDNA

sequencing

and

RACE-based

transcript

mapping

analysis

of

this

gene

-LRB-

-RRB-

in

human

mouse

and

pig

placenta

was

performed

and

it

was

determined

that

the

human

gene

is

expressed

but

not

spliced

due

to

mutations

in

splicing

signals

thus

very

few

transcripts

for

human

appear

in

cDNA

libraries

This

study

is

one

of

the

first

examples

of

the

use

of

porcine

EST

frequency

data

to

identify

a

splicing-defective

gene

in

the

human

genome

Serial

Analysis

of

Gene

Expression

in

Porcine

Tissues

Another

sequencing-based

method

to

estimate

transcript

abundance

is

serial

analysis

of

gene

expression

-LRB-

SAGE

-RRB-

This

is

a

powerful

approach

whose

sole

purpose

is

developing

a

statistically

robust

estimate

of

the

relative

amounts

of

expressed

sequences

in

the

genome

of

interest

no

cDNA

clones

or

libraries

are

created

Double-stranded

cDNA

is

digested

with

specific

restriction

enzymes

adapters

are

ligated

to

cDNA

fragments

and

the

resulting

fragments

are

concatenated

and

sequenced

extensively

to

obtain

sequences

for

tens

to

hundreds

of

thousands

of

bp

sequence

tags

These

tags

can

be

mapped

back

to

known

cDNA

sequence

and

the

resulting

data

is

analyzed

for

relative

abundance

Blomberg

and

colleagues

have

applied

SAGE

to

determine

the

content

and

expression

pattern

of

developing

porcine

conceptus

at

the

critical

stage

of

peri-implantation

where

the

developing

conceptus

goes

through

a

remarkable

morphological

elongation

stage

just

prior

to

implantation

They

identified

over

putative

transcripts

with

differential

expression

between

ovoid

-LRB-

before

elongation

-RRB-

and

filamentous

concepti

and

identified

several

pathways

involved

in

this

process

including

steroidogenesis

and

oxidative

stress

response

In

a

follow-up

paper

they

describe

the

production

of

SAGE

libraries

for

tubular

conceptus

and

a

comparison

of

non-amplified

and

amplified

SAGE

libraries

which

showed

that

amplification

a

useful

procedure

when

tissue

is

limiting

can

be

used

to

generate

SAGE

data

accurately

reflecting

transcript

levels

similar

to

non-amplified

libraries

They

then

compared

expression

patterns

between

this

intermediate

conceptus

form

and

the

ovoid

and

filamentous

expression

patterns

and

identified

over

genes

with

putative

differentially

expression

between

at

least

two

stages

Genes

differentially

expressed

at

all

stages

had

GO

annotations

for

involvement

in

cell

cycle

cellular

organization

cell-cell

interaction

and

general

metabolism

Specific

differentially

expressed

or

constitutively

expressed

genes

involved

in

tissue

remodeling

glycolysis

cell

cycle

and

tissue/cell

type

differentiation

were

further

studied

many

patterns

but

not

all

were

confirmed

by

QPCR

In

most

cases

of

dissimilar

results

between

SAGE

and

QPCR

the

QPCR

results

was

in

agreement

with

one

but

not

both

stage-differences

-LRB-

ovoid

versus

tubular

but

not

tubular

to

filamentous

etc.

-RRB-

and

the

authors

remark

that

these

differences

may

be

due

to

unknown

splicing

variants

which

may

be

resolved

once

further

information

on

the

porcine

genome

sequence

becomes

available

Screening

for

Differentially

Expressed

Genes

using

Differential

Display

and

Suppression

Subtractive

Hybridization

Technology

Open-ended

techniques

such

as

differential

display

-LRB-

DD

-RRB-

and

suppression

subtractive

hybridization

-LRB-

SSH

-RRB-

have

been

used

to

profile

the

transcriptional

response

to

various

treatments

or

to

contrast

tissues

or

other

variables

Such

screening

techniques

are

complementary

to

closed

profiling

technologies

such

as

microarrays

as

they

allow

the

discovery

of

novel

heretofore

un-sequenced

transcripts

The

DD

technique

uses

specific

primers

to

amplify

specific

subsets

-LRB-

reduced

representations

-RRB-

of

the

total

mRNA

pool

of

a

cell

or

tissue

allowing

resolution

of

a

limited

number

of

PCR

products

for

each

specific

primer

pair

on

a

sequencing

gel

These

PCR

products

can

be

compared

by

side-by-side

electrophoresis

of

PCR

products

amplified

from

RNAs

representing

different

tissues

or

treatments

to

be

compared/screened

Research

using

DD

to

screen

porcine

transcripts

have

been

published

starting

in

and

reported

from

differentially

expressed

products/genes

The

majority

of

these

reports

-LRB-

over

-RRB-

focused

on

biomedical

research

question

using

porcine

cells

or

tissues

Due

to

space

limitations

these

papers

will

not

be

discussed

here

although

all

papers

are

listed

in

Supplementary

Table

On

the

other

hand

papers

reporting

the

characterization

of

larger

sets

of

genes

from

about

to

or

more

genes

began

appearing

in

These

reports

describe

the

use

of

DD

to

study

response

to

viral

infection

liver-specific

expression

and

hepatic

response

to

dietary

changes

and

gene

expression

changes

in

response

to

selection

for

improved

reproductive

traits

These

six

papers

will

be

summarized

here

Wang

and

colleagues

identified

total

ESTs

that

increased

-LRB-

-RRB-

or

decreased

-LRB-

-RRB-

their

expression

in

alveolar

macrophage

cells

as

a

result

of

porcine

reproductive

and

respiratory

syndrome

virus

-LRB-

PRRSV

-RRB-

infection

Differential

expression

for

seven

genes

was

tested

and

all

confirmed

by

Northern

blot

analysis

of

infected

or

mock-infected

macrophages

Of

interest

was

the

finding

that

the

majority

of

the

annotated

genes

in

this

group

were

mapped

to

metabolic

and

physiological

pathways

only

one

EST

was

clearly

annotated

as

an

immune

response

gene

-LRB-

inflammatory

mediator

gene

chemotactic

factor

II

-RRB-

and

this

gene

was

down-regulated

by

PRRSV

In

a

recent

report

also

investigating

host

response

to

viral

infection

Bratanich

and

Blanchetot

used

DD

to

study

genes

differentially

expressed

in

lymph

nodes

between

healthy

piglets

and

those

suffering

from

porcine

multi-systemic

wasting

syndrome

-LRB-

PMWS

-RRB-

These

authors

sequenced

and

confirmed

nine

DD

products

that

were

found

only

in

the

affected

animals

or

showed

an

increase

in

PMWS

animals

as

compared

to

controls

Northern

analysis

of

two

genes

hyaluronan-mediated

motility

receptor

-LRB-

RHAMM

-RRB-

and

RNA

splicing

factor

further

confirmed

the

expression

response

for

these

two

genes

Two

groups

have

successfully

applied

DD

to

study

liver

gene

expression

Ponsuksili

and

co-workers

used

DD

to

screen

for

genes

selectively

expressed

in

liver

in

order

to

identify

candidate

genes

for

metabolic

traits

In

a

comparison

of

normal

liver

and

nine

other

tissues

they

found

candidate

EST

fragments

that

were

expressed

only

in

liver

or

predominately

in

liver

with

up

to

tissues

showing

expression

These

fragments

represented

known

-LRB-

-RRB-

or

unknown

-LRB-

-RRB-

transcripts

Most

of

the

genes

represented

by

multiple

clones

were

known

to

encode

proteins

that

are

secreted

by

the

liver

into

the

bloodstream

Multi-tissue

Northern

blot

analysis

confirmed

the

expression

pattern

for

complement

component

-LRB-

-RRB-

while

semi-quantitative

PCR

confirmed

and

an

additional

genes

A

second

group

exploited

the

DD

technique

to

find

genes

whose

hepatic

expression

was

altered

by

feeding

pigs

on

a

restricted

protein

diet

formulated

using

either

casein

-LRB-

CAS

-RRB-

or

soy

protein

isolate

-LRB-

SPI

-RRB-

This

group

identified

and

confirmed

differentially

displayed

PCR

products

of

which

has

similarity

to

known

genes

Nearly

all

of

the

known

genes

were

annotated

to

pathways

expected

to

be

involved

in

the

restricted

diet

including

protein

and

amino

acid

metabolism

oxidative

stress

regulation

of

gene

expression

fat

and

energy

metabolism

and

others

Schwerin

and

collaborators

further

showed

that

six

genes

involved

in

stress

response

were

differentially

expressed

between

pigs

fed

the

two

diets

with

five

of

six

genes

showing

higher

liver

expression

in

the

SPI-fed

pigs

over

the

CAS-fed

pigs

The

authors

proposed

that

one

reason

for

this

stress

response

in

the

SPI-fed

animals

is

the

amino

acid

imbalance

in

this

diet

as

compared

to

the

CAS-based

diet

Finally

two

reports

looking

at

gene

expression

changes

due

to

selection

for

improved

reproductive

traits

were

published

recently

Gladney

and

colleagues

used

DD

of

ovarian

follicles

to

identify

genes

differentially

expressed

in

control

animals

as

compared

to

animals

in

a

population

selected

for

improved

litter

size

based

on

ovulation

rate

and

embryo

survival

Tissue

was

collected

at

or

days

post

prostaglandin

injection

which

was

used

to

synchronize

follicular

development

Overall

DD

products

were

identified

and

sequenced

the

majority

of

which

were

predicted

to

differentially

expressed

although

several

equally

expressed

transcripts

were

also

characterized

Four

genes

were

confirmed

as

DE

by

Northern

blot

Of

interest

was

the

finding

that

calpain

I

light

subunit

-LRB-

-RRB-

expression

was

lower

in

the

select

line

as

compared

to

controls

As

the

similar

small

subunit

calpain

gene

has

been

linked

to

apoptosis

the

authors

speculate

that

a

decrease

in

expression

in

the

select

line

could

lead

to

decreased

apoptosis

and

to

a

larger

number

of

follicles

available

for

ovulation

The

same

group

published

a

companion

paper

using

DD

to

look

at

changes

in

anterior

pituitary

expression

in

the

same

selection

line

and

controls

Anterior

pituitary

tissue

was

collected

similarly

to

the

follicles

above

and

DD

analysis

was

performed

on

tissue

pooled

across

treatment

days

A

total

of

bands

were

successfully

sequenced

representing

distinct

sequences

a

majority

of

which

-LRB-

-RRB-

had

sequence

similarity

to

annotated

genes

Three

genes

were

validated

by

Northern

blot

demonstrating

that

follicle

stimulating

hormone

beta

-LRB-

FSHB

-RRB-

increased

expression

in

the

selection

line

while

both

ferritin

heavy

chain

and

G-beta-like

protein

genes

decreased

expression

relative

to

controls

The

former

finding

is

interesting

as

FSHB

has

a

direct

role

in

increasing

the

development

of

mature

ovarian

follicles

and

this

clearly

indicates

FSHB

may

have

been

a

direct

target

of

the

selection

applied

to

this

population

Another

useful

approach

to

gene

discovery

is

SSH

This

approach

uses

hybridization

of

an

excess

of

driver

cDNA

-LRB-

from

one

state/treatment

-RRB-

to

remove

sequences

in

the

tester

cDNA

-LRB-

from

the

other

state/treatment

-RRB-

that

are

present

in

both

populations

in

similar

amounts

Highly

differentially

expressed

sequences

can

be

enriched

for

by

preferential

recovery

of

the

resulting

set

of

un-hybridized

tester

cDNAs

The

tester

and

driver

cDNA

populations

can

be

reversed

to

allow

screening

for

both

up

and

down-regulated

genes

This

technique

was

used

by

Narayanan

and

co-workers

to

identify

genes

with

altered

abundance

at

different

stages

of

the

conversion

of

hepatocyte

cells

in

culture

into

spheroids

an

aggregate

of

cells

that

is

functionally

similar

to

liver

tissue

This

group

identified

genes

and

novel

sequences

and

deposited

ESTs

demonstrating

the

down-regulation

of

cytochrome

family

members

as

well

as

genes

involved

in

heme

biosynthesis

and

the

up-regulation

of

acute

phase

proteins

and

genes

encoding

proteins

involved

in

Ca-dependent

vesicle

trafficking

Ross

and

co-workers

have

used

SSH

to

screen

for

genes

differentially

expressed

during

porcine

conceptus

elongation

a

process

important

for

efficient

implantation

in

the

pig

This

group

reported

sequences

that

changed

expression

levels

during

elongation

they

deposited

distinct

sequences

to

GenBank

Decreased

expression

during

elongation

was

observed

for

several

ribosomal

RNAs

and

an

increase

was

seen

for

thymosin

beta

mitochondrial

proteins

and

S-adenosyl

homocysteine

hydrolase

-LRB-

SAHH

-RRB-

The

latter

two

genes

as

well

as

an

un-annotated

transcript

were

verified

by

QPCR

SAHH

is

part

of

the

pathway

to

generate

folate

an

essential

metabolite

for

embryogenesis

which

is

known

to

increase

in

the

uterine

lumen

at

the

elongation

stage

of

conceptus

development

Other

studies

of

reproductive

biology

have

used

SSH

as

well

Bonnet

and

colleagues

isolated

transcripts

responding

to

follicle

stimulating

hormone

-LRB-

FSH

-RRB-

treatment

of

granulose

cells

in

culture

Sixty-four

independent

sequences

predicted

to

respond

to

FSH

were

further

analyzed

and

transcripts

were

confirmed

by

Northern

or

QPCR

to

be

regulated

by

FSH

Annotation

of

these

genes

shows

FSH

may

alter

pathways

controlling

peroxidase

activity

and

chromatin

remodeling

To

study

the

mechanism

of

heterosis

Xu

and

collaborators

exploited

SSH

to

identify

genes

expressed

differently

in

Longissimus

dorsi

tissue

between

Yorkshire

dams

and

their

Landrace

x

Yorkshire

offspring

The

gene

was

identified

and

confirmed

by

semi-quantitative

PCR

methods

to

be

higher

in

the

dam

compared

to

her

cross-bred

offspring

The

gene

was

expressed

equally

throughout

muscle

development

-LRB-

fetal

to

month

old

samples

were

tested

-RRB-

and

expression

was

found

primarily

in

skeletal

muscle

tissue

As

has

been

implicated

in

Ca

dependent

signaling

pathways

and

a

down-regulation

was

seen

in

the

hybrid

offspring

these

results

may

indicate

Ca

signaling

influences

porcine

heterosis

traits

Finally

researchers

screening

for

genes

responding

to

Salmonella

enterica

serotype

Choleraesuis

-LRB-

SC

-RRB-

inoculation

have

reported

the

use

of

SSH

to

identify

sequences

that

change

expression

at

hours

post-inoculation

in

mesenteric

lymph

nodes

Seven

SSH-identified

and

two

related

genes

were

selected

for

further

study

and

all

were

verified

by

quantitative

real-time

PCR

The

differential

expression

of

these

genes

indicate

that

modulation

of

cytoskeletal

components

and

heat

shock

pathways

are

involved

in

the

host

immune

response

to

SC

in

the

porcine

mesenteric

lymph

tissues

Quantitative

PCR

Methods

as

the

Gold

Standard

in

Confirming

Differential

Expression

Results

There

have

been

many

reports

of

quantitative

real-time

PCR

-LRB-

QPCR

-RRB-

being

used

to

measure

the

abundance

of

porcine

transcripts

Many

recent

publications

focus

on

a

small

number

of

genes

in

the

context

of

verifying

differential

display

results

as

well

as

microarray

or

other

profiling

data

-LRB-

see

specific

results

in

the

following

microarray

section

-RRB-

as

QPCR

has

been

the

standard

technique

used

to

validate

such

results

This

comparison

is

not

as

direct

as

one

might

wish

as

properly

run

QPCR

measures

the

abundance

of

a

single

transcript

or

transcript

segment

Thus

microarray

data

which

may

result

form

hybridization

of

multiple

transcript

isoforms

to

a

probe

or

probes

on

an

array

may

not

be

confirmed

by

a

QPCR

assay

even

though

the

microarray

data

is

not

necessarily

incorrect

In

fact

some

microarray-based

technologies

such

as

the

Affymetrix

platform

have

multiple

oligonucleotides

that

interrogate

multiple

locations

along

a

gene

transcript

Thus

data

may

be

available

to

identify

differential

abundance

of

different

segments

of

transcripts

allowing

measurement

of

differential

expression

of

splice

variants

On

the

other

hand

QPCR

is

clearly

more

sensitive

and

often

shows

an

increase

in

the

level

of

difference

-LRB-

fold

change

-RRB-

between

the

class

or

treatments

being

compared

than

seen

in

microarray

data

It

is

therefore

important

to

recognize

both

the

strengths

and

weaknesses

of

each

of

these

techniques

in

such

confirmation

studies

QPCR

is

traditionally

not

viewed

as

a

high-throughput

screening

tool

due

to

lack

of

a

large

sets

of

specific

assays

available

for

porcine

transcripts

as

well

as

the

relatively

high

cost

per

gene

and

biological

sample

assayed

Recently

however

a

large

number

of

validated

QPCR

assays

have

become

publicly

available

-LRB-

-RRB-

through

the

efforts

of

a

collaborative

group

headed

by

Harry

Dawson

and

Joan

Lunney

at

USDA-ARS-Beltsville

This

group

has

developed

and

tested

QPCR

assays

based

on

the

Taqman

fluorescent

dual-labeled

probe

technology

-LRB-

PIN

database

v.

as

of

October

H.

Dawson

personal

communication

-RRB-

These

assays

focus

on

genes

in

immune

and

nutrition/metabolic

pathways

but

include

assays

for

many

signaling

molecule

of

general

interest

Dawson

Lunney

and

co-workers

have

used

such

high-throughput

QPCR

to

assay

expression

of

many

genes

responding

to

pathogenic

parasites

PRRSV

vaccination

and

have

contributed

nearly

QPCR

assays

to

recent

microarray

confirmation

studies

by

our

group

-LSB-

Wang

et

al.

submitted

-RSB-

described

below

Other

groups

have

used

a

significant

number

of

QPCR

assays

to

validate

microarray

data

including

Passerini

et

al.

-LRB-

genes

-RRB-

Ponsuksili

et

al.

-LRB-

genes

-RRB-

and

Okomo-Adhiambo

et

al.

-LRB-

genes

-RRB-

these

papers

are

discussed

in

the

microarray

section

The

QPCR

technique

can

of

course

be

used

to

measure

gene

expression

independently

of

microarray

confirmation

Examples

where

or

more

genes

were

quantitatively

assayed

with

or

without

microarray

data

include

measurement

of

response

to

LPS

to

infection

or

to

islet

graft

rejection

measurement

of

promoter

activity

in

vitro

assessing

expression

of

gene

family

transcript

isoforms

measuring

responses

during

parthenogenesis

or

oocyte/conceptus

development

brain

response

to

early

weaning/isolation

multi-tissue

response

to

carnitine

treatment

or

liver

response

to

dietary

treatments

differences

across

specific

muscle

types

and

differences

between

stented

and

unstented

arteries

Microarray

Hybridization

Studies

have

Dramatically

Expanded

our

Knowledge

of

the

Porcine

Transcriptome

The

use

of

miniaturized

arrays

of

individual

gene

sequences

to

survey

or

profile

the

expression

levels

of

hundreds

-LRB-

later

thousands

-RRB-

of

transcripts

within

a

cell

or

tissue

was

first

published

by

Schena

et

al.

although

reports

of

larger

dimension

element

arrays

-LRB-

dot

blots

etc.

-RRB-

had

already

been

published

including

early

work

on

porcine

muscle

EST

expression

patterns

The

main

technological

advances

by

Schena

and

colleagues

were

-RRB-

the

use

of

robotics

to

place

very

small

amounts

of

gene

sequences

very

closely

together

minimizing

reagent

use

and

allowing

the

use

of

standard

size

glass

microscope

slides

as

the

solid

substrate

and

-RRB-

the

independent

labeling

by

fluorescent

substrates

of

the

of

the

RNA

samples

to

be

compared

allowing

for

simultaneous

measurement

of

hybridization

of

labeled

cDNA

to

each

probe

on

the

array

Initially

the

criteria

for

finding

DE

genes

in

the

comparison

at

hand

was

limited

to

an

intuitive

but

statistically

unsupported

two-fold

difference

in

fluorescence

levels

Later

additional

experimental

designs

and

data

analyses

became

statistically

rigorous

Such

analytical

methods

have

become

a

significant

field

unto

themselves

Much

of

the

data

and

publications

described

below

are

in

the

very

early

stages

of

understanding

RNA

expression

profiles

as

the

field

of

transcriptional

profiling

is

relatively

new

and

especially

so

for

work

in

the

livestock

species

Many

early

papers

were

limited

in

scope

with

relatively

few

elements

and

scarce

biological

replication

which

is

critical

for

adequate

statistical

rigor

Initial

insights

as

to

new

aspects

of

tissue

and

cellular

function

have

been

gleaned

from

pig

microarray

data

and

connections

between

datasets

are

made

where

possible

and

appropriate

However

an

increased

depth

of

data

as

well

as

more

comprehensive

tools

will

be

required

to

fully

comprehend

and

integrate

the

massive

amounts

of

data

already

collected

across

many

different

tissues

systems

and

perturbations

Different

platforms

for

porcine

expression

profiling

have

been

used

these

are

listed

in

Supplementary

Table

and

briefly

described

below

Most

of

this

work

used

two-color

analyses

labeling

RNA

samples

using

fluorescent

or

conjugated

nucleotides

and

performing

a

dye-swap

in

which

samples

are

labeled

with

each

dye

and

used

in

separate

hybridizations

to

eliminate

dye

effects

and

have

different

excitation/emission

wavelengths

allowing

for

independent

collection

of

hybridization

data

from

each

sample

on

the

same

array

element

Further

most

work

described

below

used

a

normalization

method

called

LOWESS

-LRB-

Locally

Weighted

Scatterplot

Smoothing

-RRB-

which

corrects

for

intensity-dependent

variation

in

data

These

methods

will

serve

as

the

default

in

the

discussions

below

and

are

not

described

however

if

some

other

system

and

analysis

is

used

it

is

mentioned

below

Statistical

methods

to

identify

DE

genes

across

treatments

vary

although

ANOVA

methods

and

corrections

for

multiple

testing

using

false

discovery

rate

calculations

appear

to

becoming

the

standard

As

these

methods

greatly

affect

the

results

they

are

noted

in

the

descriptions

of

experiments

Finally

annotations

of

DNA

elements

on

the

array

are

an

important

and

growing

area

of

research

Such

annotations

are

most

often

based

on

sequence

similarity

to

genes

whose

function

is

known

or

has

been

inferred

in

turn

from

other

gene

with

similar

sequence

in

another

species

Functional

annotations

can

also

be

obtained

from

curation

of

available

biological

data

as

complied

for

genes

and

pathways

at

NCBI

-LRB-

-RRB-

or

at

Mouse

Genome

Informatics

-RRB-

At

the

Gene

Ontology

-LRB-

GO

-RRB-

Consortium

site

-LRB-

geneontology.org

-RRB-

annotation

of

a

gene

's

function

where

in

the

cell

it

performs

this

function

and

its

involvement

in

specific

biological

processes

can

be

found

Software

to

assign

GO

annotation

to

gene

sequences

such

as

the

DAVID

software

at

NIH

-LRB-

-RRB-

are

very

useful

and

many

are

freely

available

Such

functional

annotation

can

be

especially

helpful

in

annotating

a

set

of

gene

sequences

that

respond

similarly

to

specific

treatments

such

sequence

groups

or

clusters

can

be

identified

using

a

number

of

clustering

algorithms

see

the

review

by

Quackenbush

for

a

discussion

of

current

work

in

this

area

In

the

database

section

below

we

discuss

some

of

the

methods

being

used

to

evaluate

the

biological

knowledge

available

on

specific

genes

and

groups

of

genes

that

are

found

to

be

co-expressed

Specific

methods

used

by

investigators

are

also

noted

in

the

descriptions

below

Every

effort

was

made

to

include

work

published

that

used

microarrays

to

determine

porcine

expression

profiles

Seven

different

groups

also

graciously

provided

summary

details

of

fourteen

different

unpublished

microarray

projects

-LRB-

see

Supplementary

Table

-RRB-

These

unpublished

projects

include

studies

on

reproduction

-LRB-

-RRB-

muscle

traits

-LRB-

-RRB-

genetic

effects

on

expression

-LRB-

-RRB-

and

host

response

to

infection

-LRB-

-RRB-

antibody

treatment

-LRB-

-RRB-

or

stress

-LRB-

-RRB-

Current

Expression

Profiling

Results

in

Porcine

Tissues

and

Cells

using

Microarrays

Muscle

Expression

Profiling

Microarray

studies

have

been

used

in

several

species

to

better

understand

the

changes

in

gene

expression

during

livestock

muscle

growth

and

development

and

the

pig

is

no

exception

One

of

the

first

large-scale

profiles

of

porcine

skeletal

muscle

was

published

by

Moody

and

colleagues

They

used

a

nylon

membrane

spotted

with

human

cDNA

fragments

and

hybridized

this

membrane

with

human

and

porcine

skeletal

muscle

cDNA

They

found

that

approximately

of

the

spots

provided

no

signal

however

they

also

established

that

the

hybridization

signals

were

reproducible

within

sample

for

both

human

and

pig

RNA

and

that

concordance

of

results

between

species

high

As

this

was

a

test

of

cross-hybridization

no

expression

contrasts

were

reported

but

the

authors

concluded

that

cross-hybridization

appeared

promising

Another

group

has

used

a

cross-species

approach

to

investigate

porcine

skeletal

muscle

gene

expression

Lin

and

Hsu

used

a

human

cDNA

microarray

to

identify

genes

differentially

expressed

-LRB-

DE

-RRB-

between

Duroc

and

Taoyuan

Longissimus

dorsi

-LRB-

LD

-RRB-

tissue

They

identified

DE

genes

with

signal

fold

higher

that

background

for

both

breeds

They

used

correlation

analysis

to

show

a

high

level

of

reproducibility

as

had

been

found

by

Moody

et

al.

Among

these

expressed

genes

were

found

to

differ

between

breeds

-LRB-

p

-RRB-

less

that

one

would

find

by

chance

-LRB-

genes

-RRB-

Nevertheless

of

the

eight

genes

selected

for

verification

by

QPCR

all

were

confirmed

The

majority

of

DE

genes

had

higher

expression

in

Duroc

pigs

including

genes

for

ribosomal

proteins

heat

shock

proteins

and

myofibrillar

proteins

and

genes

involved

in

transcription/translation

and

metabolism-related

genes

The

authors

indicated

that

the

higher

proportion

of

proteins

involved

in

myofibrillar

structure

in

DE

genes

in

Duroc

over

Taoyuan

could

explain

Duroc

higher

muscle

growth

They

further

showed

that

a

known

myogenesis

control

factor

was

over-expressed

in

Duroc

providing

further

clues

as

to

the

increased

muscle

growth

rate

in

Duroc

A

different

pioneering

approach

for

skeletal

muscle

profiling

was

reported

by

Bai

and

others

where

a

porcine

microarray

consisting

of

un-sequenced

cDNA

clones

from

fetal

and

neonatal

LD

tissue

libraries

was

used

for

expression

profiling

of

LD

-LRB-

as

a

white

muscle

type

-RRB-

as

compared

to

psoas

muscle

-LRB-

as

a

red

muscle

type

-RRB-

Genes

identified

as

having

muscle-type

specific

expression

were

defined

as

those

having

a

normalized

psoas/LD

ratio

of

or

and

these

cDNAs

were

then

sequenced

and

annotated

Genes

with

a

high

psoas/LD

ration

-LRB-

clones

-RRB-

included

and

ribosomal

RNAs

and

NADH

dehydrogenase

subunits

and

bisphosphatase

and

members

of

the

casein

kinase

complex

or

targets

of

that

pathway

Many

genes

highly

expressed

in

LD

-LRB-

-RRB-

included

many

of

the

fast

isoforms

of

muscle

fiber

proteins

and

about

included

genes

involved

in

glycolysis

such

as

GAPDH

In

the

last

the

authors

highlighted

the

tumor

suppressor

gene

as

it

has

been

linked

to

myoblast

differentiation

in

culture

Four

genes

predicted

to

be

DE

-LRB-

GAPDH

and

one

novel

gene

-RRB-

were

tested

by

QPCR

and

all

were

confirmed

although

was

higher

in

LD

in

only

or

pigs

tested

The

authors

propose

that

this

method

of

arraying

non-sequenced

clones

is

useful

in

finding

genes

DE

in

species

with

little

genome

characterization

However

as

this

lack

of

information

eases

this

advantage

becomes

less

important

and

the

inefficiencies

on

spotting

duplicate

unknown

cDNAs

become

significant

Members

of

this

group

used

the

same

array

to

investigate

the

molecular

changes

in

response

to

dietary

restriction

-LRB-

less

protein

less

energy

termed

the

LPE

diet

-RRB-

in

porcine

LD

and

psoas

muscles

In

both

muscle

types

the

LPE

diet

resulted

in

higher

intra-muscular

fat

and

caused

twice

as

many

genes

to

show

higher

expression

as

compared

to

the

control

diet

treatment

The

authors

sequenced

these

DE

genes

and

identified

genes

involved

in

turnover

of

protein

fat

and

carbohydrate

as

well

as

genes

involved

in

growth

mitochondrial

function

translation

and

glycolysis

QPCR

analysis

verified

the

microarray

data

for

several

genes

and

indicated

several

systems

were

involved

the

increase

in

intramuscular

lipid

-LRB-

phytanoyl-CoA

hydroxylase

and

delta

desaturase

-RRB-

energy

-LRB-

creatinine

kinase

-RRB-

fiber

type

specificity

-LRB-

-RRB-

and

muscle

growth

-LRB-

cbl-b

-RRB-

The

gene

increased

by

LPE

diet

in

both

muscle

types

is

interesting

as

the

authors

further

showed

that

was

increased

during

myoblast

differentiation

The

use

of

sequenced

porcine

ESTs

to

create

an

expression

profiling

tool

was

first

published

by

Zhao

and

others

This

group

initially

arrayed

known

ESTs

and

tested

for

detectable

hybridization

signal

using

muscle

RNA

from

two

fetal

ages

-LSB-

day

-LRB-

d

-RRB-

and

-RSB-

and

two

postnatal

ages

-LRB-

week

and

week

-RRB-

as

targets

The

ESTs

that

provided

a

clear

signal

were

re-arrayed

to

generate

the

test

array

which

was

then

used

to

profile

the

fetal

-LRB-

-RRB-

and

postnatal

-LRB-

week

-RRB-

targets

A

mixed

linear

model

was

employed

to

identify

genes

with

stage-specific

expression

-LRB-

defined

as

two

fold

difference

in

expression

between

stages

with

P

-RRB-

Of

these

genes

matched

known

human

genes

and

included

elongation

factor

alpha

a

number

of

ribosomal

proteins

-LRB-

-RRB-

GAPDH

and

structural

proteins

such

as

vimentin

and

tubulin

Five

of

these

genes

were

tested

and

confirmed

by

Northern

blot

analysis

of

RNA

representing

seven

stages

of

muscle

development

from

to

week

postnatal

The

results

with

intermediate

filament

-LRB-

IF

-RRB-

protein

family

members

vimentin

and

desmin

-LRB-

tested

as

an

additional

control

-RRB-

confirmed

protein-level

data

that

vimentin

expression

dramatically

decreases

during

prenatal

muscle

development

while

muscle-specific

IF

protein

desmin

increases

The

authors

conclude

their

membrane

and

radioactive-labeling

approach

is

a

low

cost

and

accurate

expression

profiling

method

to

find

DE

genes

of

biological

interest

Two

papers

that

appeared

recently

studied

myogenesis

by

using

an

array

containing

cDNAs

selected

for

their

roles

in

myogenesis

energy

metabolism

and

myofibrillar

structure

as

well

as

additional

skeletal

muscle

ESTs

The

first

paper

reported

the

expression

pattern

for

these

genes

during

seven

stages

of

gestation

to

covering

the

two

stages

of

myogenesis

in

the

pig

-LRB-

and

-RRB-

Taking

advantage

of

known

annotations

genes

were

divided

into

functional

groups

for

analysis

Genes

both

stimulating

and

inhibiting

muscle

differentiation

as

well

as

muscle

structural

genes

had

a

peak

of

expression

at

and

declined

thereafter

Genes

in

the

glycolysis

pathway

decreased

early

then

had

a

peak

of

expression

at

The

number

of

genes

showing

expression

from

to

increased

for

the

myofibrillar

group

while

the

number

of

expressing

myogenesis-affecting

genes

and

differentiation-stimulating

genes

decreased

from

to

then

increased

from

to

The

expression

pattern

of

five

genes

presenting

the

major

annotation

groups

-LRB-

myogenesis

EPO-receptor

beta-catenin

and

TGF

energy

metabolism

GAPDH

and

structural

-RRB-

was

tested

and

confirmed

by

QPCR

although

statistical

analysis

of

these

data

was

not

described

In

a

second

paper

Cagnazzo

and

collaborators

used

the

same

microarray

and

tissue

sampling

to

compare

expression

between

the

Duroc

and

Pietrain

breeds

The

authors

found

that

energy

metabolism

genes

were

consistently

higher

in

Pietrain

over

Duroc

for

all

ages

except

in

which

this

ratio

was

reversed

On

the

other

hand

fatty

acid

metabolism

genes

had

the

opposite

profile

higher

levels

in

Duroc

from

to

then

higher

in

Pietrain

at

later

ages

They

found

myogenesis

apparently

initiated

earlier

in

Duroc

pigs

as

the

expression

of

proliferation

and

differentiation

genes

was

higher

at

and

in

this

breed

this

was

reversed

at

later

stages

Muscle

structural

genes

also

showed

higher

expression

in

early

Duroc

embryos

and

after

expression

was

higher

in

Pietrain

samples

The

same

five

genes

as

assayed

in

te

Pas

et

al.

were

tested

by

QPCR

and

all

results

were

consistent

with

the

microarray

data

although

as

for

the

te

Pas

paper

no

statistical

analysis

was

discussed

The

authors

conclude

that

as

a

delay

in

fiber

formation

has

been

associated

with

higher

fiber

numbers

in

other

species

their

finding

that

Pietrain

myogenesis

is

delayed

relative

to

Duroc

may

explain

the

Pietrain

higher

adult

muscle

mass

Two

reports

have

been

published

looking

at

porcine

heart

gene

expression

as

a

model

for

human

disease

Lahmers

and

co-workers

used

a

novel

array

consisting

of

mer

oligonucleotides

representing

each

of

the

exons

of

the

enormous

human

titin

gene

They

investigated

rabbit

mouse

rat

and

pig

myocardial

gene

and

protein

expression

from

adult

left

ventricular

tissue

In

preliminary

validation

using

pig

soleus

adult

tissue

they

found

that

of

the

exons

expressed

in

human

soleus

were

also

expressed

in

the

corresponding

pig

muscle

For

pig

myocardium

the

authors

reported

exons

were

fetal-specific

and

these

were

very

similar

to

human

fetal-specific

exons

In

the

second

report

Lai

et

al.

used

a

human

cDNA

microarray

to

determine

genes

whose

expression

changes

during

atrial

fibrillation

Nearly

genes

showed

DE

with

genes

annotated

in

cell

signaling

and

cell

communication

over-represented

while

the

second

largest

group

were

genes

involved

in

gene

regulation

A

single

gene

was

tested

and

confirmed

by

QPCR

The

authors

indicate

that

many

of

these

genes

had

not

previously

been

associated

with

atrial

fibrillation

and

thus

further

study

on

these

genes

is

warranted

Reproductive

Tissue

Expression

Profiling

A

number

of

papers

have

been

published

in

the

past

two

years

on

the

use

of

microarray

to

study

reproductive

tissues

primarily

the

ovary

-LRB-

-RRB-

uterus

-LRB-

-RRB-

and

testis

-LRB-

-RRB-

but

also

on

the

developing

embryo/conceptus

-LRB-

-RRB-

As

described

above

in

the

DD

section

Gladney

and

colleagues

have

studied

the

expression

profile

in

ovarian

follicles

collected

from

animals

selected

for

improved

litter

size

and

in

a

random-bred

control

population

In

addition

to

DD

microarray

analysis

of

pooled

follicles

from

these

two

populations

was

performed

by

using

two

different

Incyte

UniGEM

human

cDNA

microarrays

Based

on

two-fold

differences

only

they

identified

and

DE

genes

using

these

microarray

platforms

and

found

little

overlap

in

the

two

lists

of

genes

Northern

blot

analyses

of

three

genes

-LRB-

follistatin

-LRB-

FST

-RRB-

early

growth

response

nuclear

family

receptor

-LRB-

-RRB-

-RRB-

confirmed

the

microarray

results

for

FST

and

This

group

has

built

on

this

early

work

using

a

porcine

cDNA

microarray

to

profile

the

expression

pattern

of

ovary

and

follicle

tissue

from

the

select

and

control

lines

of

pigs

A

mixed-model

analysis

identified

ovary

and

follicle

genes

DE

between

these

two

lines

In

contrast

to

the

data

obtained

with

the

human

microarrays

genes

-LRB-

about

half

of

the

total

-RRB-

were

found

DE

in

both

tissues

providing

a

measure

of

confidence

in

these

results

Northern

hybridization

using

probes

for

calpain

light

subunit

I

and

cytochrome

-LRB-

-RRB-

genes

were

used

to

confirm

the

microarray

data

for

both

genes

Overall

the

lists

of

DE

genes

contained

both

genes

known

to

be

expressed

during

folliculogenesis

as

well

as

genes

not

previously

associated

with

this

process

The

authors

highlighted

DE

genes

involved

in

steroid

biosynthesis

-LRB-

Collagen

type

I

receptor

STAR

and

-RRB-

and

tissue

remodeling

-LRB-

-RRB-

that

could

provide

mechanistic

clues

for

the

difference

in

ovulation

rate

seen

between

these

lines

and

they

indicate

further

ontogenic

studies

of

these

candidates

would

be

helpful

in

such

interpretations

Gene

profiling

was

used

successfully

to

study

the

process

of

luteinization

by

comparing

pre-estrous

preovulatory

ovarian

follicles

to

luteinized

follicles

on

day

of

estrous

prior

to

ovulation

A

custom

porcine

cDNA

microarray

was

created

from

clones

selected

from

the

ovary

EST

library

project

described

above

Microarray

data

collected

on

these

two

types

of

follicle

was

produced

using

a

reference

design

the

reference

was

an

RNA

mixture

from

all

follicular

stages

and

data

normalization

and

the

Welsh

t-test

were

used

to

identify

DE

genes

-LRB-

P

-RRB-

between

follicle

stages

The

authors

reported

the

major

classifications

for

the

genes

decreased

from

pre-estrous

to

luteinized

post-estrous

follicles

were

cytoskeletal

structural

and

regulatory

proteins

chromatin

component

and

nucleic

acid-binding

proteins

metabolic

enzymes

oxidative

response

proteins

cAMP

receptor

pathways

proteins

and

cell

proliferation/differentiation

pathways

proteins

For

the

genes

increased

in

the

same

comparison

the

major

annotation

groups

were

cell

adhesion

migration

growth

inhibition

and

angiogenesis

Some

functional

categories

were

observed

in

both

lists

including

different

genes

involved

in

steroidogenesis

proteolysis

and

metabolism

In

validation

work

four

genes

-LRB-

LHCGR

and

-RRB-

were

tested

by

QPCR

and

results

showed

similar

patterns

to

the

microarray

data

although

statistical

evidence

was

not

discussed

The

authors

note

that

many

genes

whose

function

and

expression

patterns

were

known

previously

to

be

involved

in

folliculogenesis

were

identified

in

this

analysis

and

this

further

validates

their

results

Many

of

the

identified

genes

were

novel

with

respect

to

luteinization

however

and

are

interesting

candidates

for

future

study

of

this

process

Two

manuscripts

have

been

published

on

expression

profiling

in

the

developing

porcine

embryo

Lee

et

al.

used

a

custom

cDNA

membrane

array

to

initiate

microarray

studies

on

the

elongating

peri-implantation

embryo

a

morphological

transition

critical

for

successful

implantation

Concepti

from

four

stages

of

this

transition

-LRB-

small

spherical

large

spherical

tubular

and

filamentous

forms

-RRB-

were

collected

and

profiled

using

the

above

array

The

minimal

quantities

of

embryo

tissue

available

required

an

amplification

step

preliminary

hybridizations

with

un-amplified

and

amplified

material

indicated

amplification

did

not

introduce

bias

Nine

genes

were

declared

as

DE

using

three

criteria

Two

genes

met

the

stringent

Bonferonni

test

for

multiple

testing

four

genes

were

DE

at

p

while

the

remaining

three

genes

had

p

and

at

least

a

two-fold

difference

in

expression

between

stages

Four

genes

covering

these

three

categories

-LRB-

STAR

interleukin

beta

-LRB-

-RRB-

and

thymosin

beta

-RRB-

were

selected

for

QPCR

confirmation

and

all

four

showed

statistically

significant

differential

expression

in

both

QPCR

and

hybridization

data

The

results

confirm

reported

SSH

and

EST

frequency

data

and

the

thymosin

beta

results

agreed

with

data

reported

by

Smith

et

al.

Further

the

STAR

gene

has

been

shown

to

increase

in

expression

by

SAGE

data

and

by

follow-up

Northern

QPCR

and

protein

level

analysis

by

the

same

group

These

confirmations

verify

the

results

of

the

Lee

et

al.

study

which

contributed

additional

genes

for

understanding

of

the

rapid

transition

spherical

to

filamentous

conceptus

which

is

nearly

unique

to

the

pig

Whitworth

and

others

developed

a

custom

cDNA

array

containing

genes

collected

from

cDNA

libraries

from

ovary

embryo

oocyte

oviduct

uterus

conceptus

and

fetus

to

determine

genes

DE

across

several

stages

and

modes

of

embryogenesis

These

included

in

vivo

produced

germinal

vesicle

oocytes

-LRB-

pgvo

-RRB-

four

cell

embryos

-LRB-

-RRB-

and

blastocysts

-LRB-

pblivv

-RRB-

as

well

as

in

vitro

produced

four

cell

embryos

-LRB-

-RRB-

and

blastocysts

-LRB-

pblivp

-RRB-

An

ontogenic

study

from

oocyte

to

blastocysts

-LRB-

all

in

vivo

samples

-RRB-

showed

to

DE

genes

A

comparison

of

in

vivo

to

in

vitro

embryos

identified

-LRB-

versus

-RRB-

and

-LRB-

pblivv

versus

pblivp

-RRB-

DE

genes

False

discovery

calculations

for

the

latter

two

comparisons

eliminated

nearly

all

of

the

DE

genes

and

a

condition

tree

clustering

did

not

show

evidence

that

in

vitro

expression

patterns

could

be

easily

distinguished

from

the

in

vivo

patterns

In

the

ontogeny

study

results

similar

clustering

showed

each

stage

correctly

clustered

together

and

that

as

expected

the

two

earlier

stages

clustered

more

closely

together

QPCR

validation

of

seven

genes

from

these

comparisons

was

performed

and

of

the

pair-wise

comparisons

available

in

the

microarray

data

for

these

seven

genes

were

confirmed

by

QPCR

The

authors

found

that

genes

induced

in

the

transition

from

germinal

vesicle

to

four

cell

embryo

were

similar

to

those

reported

for

the

same

transition

in

the

mouse

and

included

nuclear

structural

and

functional

proteins

while

genes

decreased

during

this

transition

included

those

involved

in

cell

adhesion

receptor

activity

mitotic

cell

cycle

transporter

activity

and

M-phase

microtubule

activity

Genes

increased

in

blastocyst

as

compared

to

cell

embryos

included

ribosome

hydrogen

ion

transport

and

cation

transport

activities

Many

examples

were

discussed

showing

much

of

this

data

is

similar

to

that

reported

in

the

mouse

although

many

differences

between

pig

and

mouse

profiles

were

observed

The

authors

correctly

note

that

this

analysis

is

just

the

beginning

of

understanding

the

transcriptional

program

during

early

embryogenesis

This

group

has

also

used

this

array

to

investigate

gene

expression

changes

during

the

estrous

cycle

and

pregnancy

in

the

porcine

endometrium

They

collected

RNA

at

seven

times

during

the

estrous

cycle

-LRB-

and

days

post-estrous

-RRB-

and

used

a

reference

design

to

identify

genes

DE

across

the

estrous

cycle

The

reference

RNA

consisted

of

a

mixture

of

RNA

from

the

tissues

used

to

make

the

array

see

above

Genes

were

identified

as

DE

using

ANOVA

with

Benjamini-Hochberg

correction

to

control

for

multiple

testing

with

the

added

criteria

that

the

gene

must

be

at

least

twice

as

abundant

as

seen

in

the

reference

The

number

of

DE

genes

varied

by

day

of

estrous

with

a

minimum

of

genes

on

day

and

a

maximum

of

genes

on

day

Clustering

of

these

genes

using

k-means

methods

identified

six

main

patterns

of

expression

across

the

estrous

cycle

Several

of

these

patterns

-LRB-

i.e.

DE

on

day

DE

on

days

and

DE

on

days

-RRB-

are

coincident

with

specific

known

functions

of

the

endometrium

a

-RRB-

sperm

maturation

b

-RRB-

blastocyst

growth

and

position

c

-RRB-

conceptus

development

and

attachment

respectively

They

also

used

EASE

software

to

connect

GO

terms

to

these

clusters

where

for

example

in

the

day

cluster

immune

cell

markers

and

cytokine

genes

predominated

within

the

day

cluster

many

DE

genes

were

annotated

with

tyrosine

receptor

kinase

activity

function

Using

cluster

and

EASE

results

as

a

guide

seven

genes

were

selected

for

QPCR

based

validation

all

resulting

QPCR

data

was

consistent

with

the

microarray

results

although

statistical

significance

of

the

QPCR

results

was

not

discussed

The

authors

conclude

that

these

data

on

the

global

expression

patterns

with

the

cycling

uterus

will

guide

transgenetic

and

cell

transfer

approaches

to

improve

reproduction

efficiency

Finally

Stewart

and

colleagues

have

reported

the

use

of

a

human

cDNA

microarray

to

assess

testicular

expression

patterns

in

boars

differing

in

steroidogenesis

levels

The

RNA

from

animals

-LRB-

n

-RRB-

with

known

high

plasma

estrone

was

directly

compared

to

RNA

from

low

plasma

estrone

boars

in

paired

hybridizations

Genes

with

statistically

significant

differences

between

the

two

states

were

identified

using

Student

's

t-test

and

Benjamini-Hochberg

correction

for

multiple

testing

Seven

genes

were

found

by

this

method

to

be

more

highly

expressed

in

the

high

estrone

boars

-LRB-

p

-RRB-

Five

of

the

genes

tested

were

verified

as

DE

using

QPCR

and

included

SAT

FTL

and

the

authors

note

that

the

fold

changes

were

much

higher

than

those

observed

in

the

microarray

data

Immune

Response

Expression

Profiling

The

immune

response

is

highly

complex

with

multiple

tissues

and

cell

types

communicating

information

that

is

contextual

and

changes

during

early

inflammatory

stages

as

well

as

during

inflammatory

resolution

and

the

adaptive

immune

response

and

changes

can

also

be

long-term

through

immune

memory

Hammamieh

et

al.

have

developed

useful

data

on

variability

among

pigs

within

peripheral

blood

mononuclear

cells

-LRB-

PBMC

-RRB-

Using

a

human

cDNA

membrane

array

they

measured

the

PBMC

expression

profiles

of

ten

Yorkshire

piglets

They

found

DE

genes

which

were

annotated

as

stress

response

immune

response

and

genes

involved

in

transcription

This

group

then

used

this

same

array

in

a

follow-up

paper

comparing

expression

profiling

of

human

PMBC

exposed

in

vitro

to

staphylococcal

enterotoxin

B

-LRB-

SEB

-RRB-

to

profiling

data

of

PBMC

from

piglets

intoxicated

with

SEB

to

in

vivo

Using

a

supervised

learning

procedure

for

class

prediction

to

compare

these

two

datasets

and

by

using

a

separate

training

dataset

of

gene

expression

profiles

of

human

PBMC

infected

with

eight

separate

pathogens

they

were

able

to

identify

a

set

of

genes

predictive

for

SEB

exposure

A

separate

group

has

also

reported

the

development

of

tools

for

assaying

gene

expression

responses

in

immune

cells

This

group

selected

cytokines

chemokines

and

receptors

relevant

to

immune

response

and

developed

a

cDNA

array

containing

these

genes

They

then

validated

the

resulting

array

by

interrogating

RNAs

isolated

from

control

or

phorbol

ester/ionomycin

stimulated

PBMC

from

pigs

Expression

patterns

obtained

through

hybridization

of

radioactively

labeled

cDNAs

to

the

array

followed

closely

the

expected

expression

patterns

published

previously

for

most

of

these

genes

indicating

this

focused

immune

array

can

be

used

for

profiling

the

porcine

immune

response

Afonso

and

co-workers

have

used

a

cDNA

microarray

constructed

from

a

swine

macrophage

library

to

compare

expression

profiles

from

macrophage

cultures

infected

with

two

forms

of

African

swine

fever

virus

-LRB-

ASFV

-RRB-

One

infection

used

a

parental

ASFV

-LRB-

-RRB-

while

the

alternate

infection

used

a

mutant

virus

-LRB-

-RRB-

deficient

in

two

genes

that

control

growth

of

ASFV

in

macrophages

RNA

was

collected

at

and

hours

post

infection

-LRB-

hpi

-RRB-

and

t-test

analysis

of

the

hpi

hybridization

data

indicated

a

total

of

genes

were

found

to

be

up-regulated

fold

or

more

in

the

infections

as

compared

to

the

infections

while

genes

were

down-regulated

The

up-regulated

genes

responding

only

to

the

gene-deleted

virus

included

many

interferon-regulated

genes

Control

experiments

with

mock-infected

cultures

as

well

as

Northern

blots

and

or

QPCR

of

test

genes

showed

this

data

to

be

reliable

Interferon

regulation

of

response

to

virus

was

further

confirmed

by

the

expression

profile

observed

for

an

inhibitor

of

IFN-induced

antiviral

protein

which

was

decreased

in

infected

cells

Another

analysis

of

blood

cell

response

to

infection

has

been

published

by

Moser

et

al.

This

group

is

interested

in

finding

genes

that

may

control

susceptibility

to

bacterial

disease

A

microarray

containing

cDNAs

from

ten

immune

cell

types

and

tissues

was

used

to

interrogate

expression

in

peripheral

blood

leukocytes

isolated

from

the

two

most

extreme

responders

to

an

Actinobacillis

pleuropneumoniae

-LRB-

A.p.

-RRB-

infection

The

RNA

was

collected

from

all

pigs

in

the

infection

study

just

before

-LRB-

T

-RRB-

and

hpi

-LRB-

T

-RRB-

The

experimental

design

was

a

reference

design

and

used

either

uninfected

leukocyte

RNA

or

a

mixture

of

muscle

and

leukocyte

RNA

A

sophisticated

mixed

model

analysis

was

used

to

identify

DE

genes

from

T

to

T

for

each

pig

The

authors

reported

a

list

of

genes

was

decreased

during

infection

in

the

resistant

animal

and

increased

in

the

susceptible

animal

and

a

second

cluster

of

genes

with

the

reverse

pattern

The

origin

of

the

genes

in

the

first

cluster

was

predominately

a

cDNA

library

created

by

subtraction

of

liver

expressed

genes

from

genes

expressed

in

lymphocytes

indicating

an

immune

system

origin

The

cDNAs

found

in

the

second

cluster

primarily

arose

from

a

library

created

from

A.p.

infected

leukocyte

RNA

subtracted

by

uninfected

leukocytes

No

specific

genes

were

mentioned

however

the

apparent

immune

response

indicated

genes

relevant

to

this

infection

were

identified

Several

papers

have

been

recently

published

that

use

microarray

analysis

to

investigate

the

transcript

profile

of

the

intestine

and

associated

lymph

tissue

Dvorak

and

colleagues

describe

the

generation

of

over

ESTs

from

a

cDNA

library

of

Peyer

's

Patch

a

mucosal

tissue

of

the

intestine

and

the

development

of

a

custom

cDNA

microarray

from

these

clones

The

microarray

was

used

to

assess

expression

across

total

library

cRNA

from

un-stimulated

Peyer

's

Patch

tissue

compared

to

stimulated

Peyer

's

Patch

total

cRNA

The

latter

cRNA

was

a

pool

of

RNAs

from

cell

cultures

stimulated

for

hours

in

tissue

culture

chambers

with

SC

lipopolysaccaride

cholera

toxin

or

Phorbol

ester

homocyclic

AMP

concanavalin

A.

Additional

preliminary

hybridizations

comparing

the

normal

un-stimulated

library

the

stimulated

library

and

the

pooled

and

subtracted

library

were

run

in

duplicate

with

dye

swap

A

number

of

genes

were

found

to

be

differentially

represented

among

these

three

libraries

indicating

the

pooling

and

subtractions

was

successful

This

group

then

used

this

microarray

to

examine

expression

differences

between

juvenile

Peyer

's

Patch

-LRB-

JPP

-RRB-

and

adult

Peyer

's

Patch

tissue

The

hybridization

analyses

used

a

reference

design

with

the

reference

being

pooled

mesenteric

lymph

nodes

-LRB-

MLN

-RRB-

from

young

pigs

The

Student

's

t-test

with

Benjamini-Hochberg

correction

was

used

to

identify

DE

genes

in

JPP

compared

to

reference

Using

as

minimum

fold

change

value

of

-LRB-

based

on

JPP

JPP

self

hybridization

analysis

-RRB-

as

an

additional

criteria

genes

were

identified

as

DE

and

all

but

of

these

were

more

highly

expressed

in

JPP

compared

to

MLN

Hierarchical

clustering

of

these

DR

genes

across

the

four

individual

pig

samples

indicated

significant

variation

among

animals

Seven

of

these

ESTs

and

thirteen

additional

non-differentially

expressed

ESTs

were

tested

by

QPCR

in

JPP

MLN

and

adult

PP

Of

ESTs

with

QPCR

data

for

JPP

there

was

a

positive

correlation

-LRB-

correlation

coefficient

-RRB-

between

the

JPP/MLN

rations

for

QPCR

and

microarray

Several

genes

-LRB-

AECC

SPAI

PSP

-RRB-

had

much

higher

rations

in

the

QPCR

data

-LRB-

to

fold

-RRB-

than

seen

in

the

microarray

data

In

QPCR

comparison

between

JPP

and

adult

PP

several

genes

were

highlighted

Five

genes

MARCKS

CIDE-B

PSP

and

PROLI

were

much

more

highly

expressed

in

JPP

as

compared

to

adult

PP

while

MHCII-DR

was

more

highly

expressed

in

adult

PP

The

genes

CIDE-B

and

PSP

are

interesting

as

these

are

annotated

as

growth

and

apoptosis-regulating

genes

associated

with

responses

to

normal

and/or

abnormal

intestinal

microflora

Additional

microarray-based

analysis

of

the

intestinal

response

to

bacteria

in

this

case

Escherichia

coli

and

S.

enterica

serotype

Typhimurium

-LRB-

ST

-RRB-

has

recently

been

published

by

Niewold

and

collaborators

In

these

reports

this

group

used

a

model

of

in

vivo

infection

called

small

intestinal

segment

perfusion

-LRB-

SISP

-RRB-

They

created

a

cDNA

array

using

jejunal

intestine

ESTs

and

have

used

this

array

to

measure

expression

in

jejunal

tissue

after

infection

with

an

enterotoxigenic

E.

coli

-LRB-

ETEC

-RRB-

strain

or

mock-infected

pigs

Fifteen

genes

were

declared

DE

when

the

fold

change

in

expression

between

uninfected

and

infected

tissue

-LRB-

within

a

SISP

loop

in

the

same

animal

-RRB-

was

or

and

the

false

discovery

rate

as

calculated

by

significance

of

microarray

was

One

of

these

PAP

was

thirty-fold

higher

in

infected

tissue

the

other

genes

were

not

identified

The

PAP

expression

pattern

was

confirmed

by

Northern

blot

analysis

In

a

second

report

using

the

same

array

and

SISP

technique

the

same

group

looked

at

the

response

to

ST.

Jejunal

RNA

collected

from

several

locations

in

the

jejunum

after

mock-infected

or

ST

infected

jejunum

at

or

hpi

was

used

in

microarray

hybridizations

they

pooled

tissue

samples

from

animals

so

unfortunately

there

was

no

biological

replication

Spotfire

software

was

used

to

find

DE

genes

with

fold

differences

or

and

p

relative

to

mock-infected

jejunal

RNA

Seven

genes

were

found

DE

between

either

the

or

hpi

samples

as

compared

to

mock-infected

tissue

Three

genes

-LRB-

PAP

and

-RRB-

were

DE

at

both

time

points

while

and

were

DE

at

only

the

hpi

time

while

and

an

unknown

EST

were

increased

at

hpi

only

No

down-regulated

genes

were

found

One

gene

-LRB-

PAP

-RRB-

was

tested

using

QPCR

and

was

confirmed

although

the

data

was

not

shown

The

most

interesting

result

was

that

known

to

function

in

an

immunosuppressive

pathway

involving

was

up-regulated

and

thus

could

indicate

resolution

of

inflammation

was

occurring

by

hours

Alternatively

the

authors

suggest

that

immunosuppression

by

ST

may

also

be

occurring

and

that

such

immunosuppression

could

be

a

reason

for

the

very

low

numbers

of

identified

DE

genes

by

this

model

They

also

acknowledge

that

as

they

collected

whole

jejunal

tissue

the

DE

gene

signal

may

be

swamped

by

the

large

number

of

other

cell

types

in

the

tissue

isolated

Another

microarray

was

recently

used

to

study

the

transcriptional

response

to

SC

in

the

gut

Zhao

and

others

used

a

novel

broad-coverage

oligonucleotide

array

-LRB-

further

discussed

below

in

the

Tissue

Expression

Pattern

section

-RRB-

to

investigate

changes

in

lung

expression

at

and

hpi

relative

to

uninfected

pigs

A

loop

design

was

used

in

array

hybridizations

to

identify

DE

genes

across

these

time

points

Fifty-seven

genes

showed

DE

-LRB-

P

maximal

FDR

-RRB-

between

uninfected

and

infected

lung

Cluster

analysis

of

these

genes

showed

that

of

the

genes

with

annotation

-LRB-

-RRB-

were

related

to

immune

response

apoptosis

or

tumorigenesis

clearly

indicating

that

the

array

was

useful

in

identifying

relevant

genes

for

this

infection

Several

genes

showed

dramatic

increases

in

expression

level

relative

to

controls

genes

showed

fold

greater

expression

at

hours

These

included

INDO

-LRB-

known

immune

response

genes

-RRB-

and

and

-LRB-

a

known

interferon-inducible

gene

family

-RRB-

Interestingly

and

members

of

a

transglutaminase

gene

family

with

possible

roles

in

apoptosis

and/or

antigen

processing

increased

fold

and

fold

respectively

This

gene

family

has

not

directly

been

implicated

in

the

immune

response

to

bacteria

in

any

species

but

the

known

role

in

apoptosis

for

TGM

genes

indicates

this

pathway

is

important

in

the

response

of

the

lung

to

infection

A

large

number

of

genes

were

chosen

for

QPCR

for

two

purposes

a

-RRB-

to

validate

microarray

expression

patterns

-LRB-

genes

-RRB-

and

b

-RRB-

to

characterize

more

fully

the

transcript

response

to

SC

-LRB-

genes

-RRB-

The

QPCR

confirmed

of

the

DE

genes

tested

and

identified

six

additional

DE

genes

validating

the

microarray

data

from

this

oligonucleotide

array

Overall

the

QPCR

results

showed

a

strong

T

helper

cell

type

response

in

the

lung

to

Salmonella

-LRB-

exemplified

by

induction

of

IFNG

INDO

TNF

and

WARS

-RRB-

These

results

also

demonstrated

a

strong

apoptotic

response

-LRB-

exemplified

by

and

induction

-RRB-

and

an

antigen

processing

response

-LRB-

exemplified

by

induction

-RRB-

The

classical

complement

pathway

-LRB-

-RRB-

and

type

interferon

pathway

-LRB-

-RRB-

were

were

also

confirmed

as

strongly

induced

while

decrease

of

T

helper

cell

type

response

genes

-LRB-

-RRB-

by

hpi

was

confirmed

These

data

clearly

show

the

value

of

the

microarray

as

well

as

extensive

QPCR

analyses

to

determine

expression

profiles

during

infection

that

inform

us

of

the

conserved

and

potentially

pig-specific

biological

pathways

involved

A

first

generation

Affymetrix

porcine

GeneChip

with

probe

sets

to

assay

over

transcripts

was

recently

used

to

study

host

mesenteric

lymph

nodes

-LRB-

MLN

-RRB-

transcriptional

response

to

ST

-LSB-

Wang

et

al.

submitted

-RSB-

Animals

were

infected

with

ST

and

tissues

collected

after

hpi

hpi

hpi

or

days

post-infection

RNA

was

used

in

standard

Affymetrix

analyses

to

produce

profiling

data

analyzed

by

and

a

mixed

model

ANOVA

with

false

discovery

rate

control

to

identify

genes

DE

across

stages

within

infection

Results

showed

that

genes

changed

their

MLN

expression

level

across

one

or

more

pair-wise

time-point

comparisons

in

the

ST

infection

-LRB-

p

fold

change

q

-RRB-

about

genes

were

found

DE

at

each

time

relative

to

uninfected

pigs

Of

interest

was

the

finding

that

in

contrast

to

the

strong

transcriptional

response

to

SC

seen

in

the

lung

by

hpi

a

limited

induction

of

genes

at

hpi

with

ST

was

observed

In

fact

from

hours

to

hours

post

infection

many

genes

decreased

their

expression

To

study

this

further

cluster

analysis

and

analysis

of

specific

pathways

were

used

to

reveal

common

expression

patterns

for

sets

of

genes

and

identify

specific

features

of

the

host

response

to

ST

infection

In

Figure

the

cluster

analysis

of

all

genes

found

DE

in

the

ST

infection

is

shown

one

particular

cluster

-LRB-

-RRB-

is

highlighted

This

cluster

the

genes

within

which

on

average

rose

in

expression

by

hours

and

then

decreased

by

hours

contains

a

large

number

of

cytokine

genes

and

NFkB-dependent

genes

known

to

be

involved

in

the

inflammatory

response

This

result

indicates

that

in

parallel

to

the

clinical

features

of

ST

infection

where

inflammation

is

mild

and

peaks

at

hpi

the

NFkB

pathways

appears

to

be

activated

between

and

hpi

and

then

suppressed

thereafter

The

expression

profile

of

genes

-LRB-

seven

of

which

are

present

in

cluster

in

Figure

-RRB-

was

analyzed

by

Q-PCR

and

showed

statistically

significant

confirmation

of

the

expression

pattern

observed

in

the

microarray

data

-LSB-

Wang

et

al.

submitted

-RSB-

Toxoplasma

gondii

is

a

protozoan

parasite

that

infects

a

significant

portion

of

the

world-wide

human

population

A

secondary

host

reservoir

for

this

parasite

is

the

pig

and

the

host

interaction

between

T.

gondii

and

porcine

cells

was

recently

investigated

using

cDNA

microarrays

The

ESTs

on

the

array

were

selected

from

immune

libraries

for

likely

involvement

in

immune

response

and

this

selected

set

was

used

to

assay

expression

in

uninfected

kidney

epithelial

cells

-LRB-

-RRB-

or

after

T.

gondii

infection

at

eight

time

points

after

infection

-LRB-

hour

to

hours

-RRB-

Relative

to

uninfected

cells

a

total

of

genes

DE

genes

identified

using

Student

's

t-test

were

found

to

be

induced

and

more

were

decreased

at

one

or

more

times

after

infections

The

majority

of

the

induced

genes

responded

to

infection

within

the

first

hours

and

different

functional

classes

of

DE

genes

responded

including

transcription

and

signaling

metabolism

immune

response

cell

cycle

and

apoptosis

Eleven

DE

genes

were

tested

and

confirmed

by

QPCR

The

authors

concluded

that

this

approach

identified

many

classes

of

genes

that

will

be

useful

candidates

to

study

cell-mediated

responses

especially

apoptosis

and

NFkB-dependent

pathways

to

this

parasitic

infection

Using

Microarrays

to

Determine

Tissue-Selective

Gene

Expression

Patterns

and

Microarray

Applications

in

Other

Research

Areas

Most

of

the

microarrays

discussed

above

were

developed

to

ask

specific

questions

in

biology

When

tools

for

a

specific

tissue

were

not

available

some

researchers

tested

the

utility

of

human

arrays

to

profile

porcine

expression

-LRB-

see

additional

papers

in

Supplementary

Table

-RRB-

While

these

cross-species

tools

can

be

successful

large-scale

porcine-specific

tools

useful

in

studying

a

wide

variety

of

biological

questions

are

available

As

discussed

above

in

the

infection

section

a

first-generation

porcine

oligonucleotide

set

representing

cDNAs

and

ESTs

with

broad

coverage

across

tissues

has

been

designed

by

Qiagen-Operon

in

collaboration

with

researchers

in

the

Swine

Sub-committee

of

the

research

project

Zhao

and

collaborators

validated

the

novel

oligonucleotides

on

the

array

by

hybridized

with

targets

from

porcine

adult

liver

lung

muscle

or

small

intestine

A

loop

design

were

utilized

to

collect

transcriptome

data

for

each

tissue

and

to

identify

DE

genes

across

tissues

Using

available

negative

controls

-LRB-

average

signal

of

five

Arabidopsis

gene

oligonucleotides

-RRB-

to

calculate

a

true

background

level

the

large-scale

transcriptome

for

each

adult

tissue

-LRB-

from

in

muscle

to

in

lung

-RRB-

was

established

as

those

genes

with

greater

than

fold

background

signal

-LRB-

q

-RRB-

Using

a

criteria

of

P

and

q

tissue-selective

gene

lists

were

produced

from

a

low

of

genes

in

small

intestine

to

a

high

of

genes

in

liver

Clustering

results

of

the

expressed

genes

identified

a

number

of

patterns

across

these

four

tissues

that

are

useful

in

annotating

the

array

ESTs

QPCR

analysis

of

selected

genes

across

the

four

tissues

was

used

to

verify

tissue

expression

and

oligonucleotide

specificity

-LRB-

multiple

members

of

gene

families

tested

-RRB-

and

showed

statistically

significant

confirmation

of

all

but

genes

These

results

demonstrated

that

this

porcine

oligonucleotide

array

is

informative

and

the

oligonucleotide

specificity

is

high

thus

the

Qiagen-Operon

porcine

array

can

be

used

for

porcine

functional

genomics

analysis

A

small

number

of

papers

have

been

published

recently

on

explorations

of

porcine

brain

-LRB-

-RRB-

liver

-LRB-

-RRB-

and

adipose

-LRB-

-RRB-

tissues

Nobis

and

coauthors

are

interested

in

the

expression

pattern

of

genes

in

the

porcine

brain

and

have

submitted

ESTs

from

a

brain

cDNA

library

constructed

from

pooled

brain

regions

In

addition

they

constructed

a

brain

cDNA

microarray

and

demonstrated

with

self-hybridizations

of

normal

pooled

brain

cDNA

-LRB-

and

appropriate

statistical

corrections

-RRB-

that

the

microarray

can

provide

quality

data

when

a

fold

cut-off

of

is

used

to

control

false

positives

Members

of

this

group

have

also

used

this

microarray

to

investigate

frontal

cortex

expression

profiles

in

early-weaned

-LRB-

EWC

-RRB-

pigs

compared

to

nonweaned

-LRB-

NWC

-RRB-

pigs

as

well

as

weaned/nonweaned

pigs

isolated

socially

-LRB-

EWI

NWI

-RRB-

in

a

factorial

design

Using

a

replicate

loop

design

to

collect

data

for

all

comparisons

they

found

DE

genes

using

a

modified

t-test

that

accounts

for

multiple

testing

-LRB-

P

fold

change

-RRB-

Of

these

genes

they

found

of

annotated

genes

had

relevant

brain

functions

Six

DE

genes

were

selected

for

QPCR

validation

based

on

DE

in

specific

contrasts

including

social

isolation

-LRB-

NWI

vs.

NWC

CPE

and

-RRB-

or

social

isolation

in

early

weaned

pigs

-LRB-

EWI

vs.

EWC

DBI

and

-RRB-

and

early

weaning

in

the

presence

of

social

isolation

-LRB-

EWI

vs.

NWI

-RRB-

The

QPCR

results

confirmed

the

first

five

genes

and

indicated

that

social

isolation

in

either

weaned

or

nonweaned

pigs

has

effects

on

neuronal

gene

expression

but

that

they

did

not

detect

gene

expression

differences

due

to

weaning

alone

The

authors

postulate

this

latter

result

is

potentially

due

to

the

small

study

size

A

custom

oligonucleotide

microarray

was

used

to

study

porcine

adipose

tissue

and

stromal/vascular

-LRB-

SV

-RRB-

gene

expression

The

SV

cultures

were

collected

from

three

stages

of

growth

and

development

-LRB-

and

fetal

stages

and

day

neonatal

stage

-RRB-

and

adipose

tissue

was

collected

from

day

fetal

and

day

neonatal

stages

They

identified

expression

above

background

for

genes

in

SV

cultured

cells

and

genes

in

the

adipose

tissue

samples

Many

of

the

these

genes

have

been

reported

to

be

expressed

in

adipose

cells

previously

however

the

authors

highlighted

eleven

genes

not

previously

so

reported

including

relaxin

chromogranins

A

and

B

BDNF

and

APOR

-RRB-

Three

genes

were

reported

as

more

highly

expressed

in

fetal

SV

cells

as

compared

to

neonatal

adipose

tissue

-LRB-

IFNG

and

-RRB-

using

a

t-test

of

normalized

spot

intensities

Several

papers

have

reported

changes

in

liver

gene

expression

under

a

number

of

treatments

To

profile

the

response

to

fasting

and

to

treatment

with

a

peroxisome

proliferator-activated

receptor

alpha

-LRB-

PPARG

-RRB-

ligand

-LRB-

Clofibric

acid

CA

-RRB-

Cheon

and

collaborators

used

a

pig

skeletal

muscle

EST

array

to

measure

the

liver

transcriptional

profile

in

normal

fed

pigs

compared

to

fasted

or

CA-treated

pigs

Liver

RNA

was

pooled

within

treatment

thus

no

biological

replication

was

available

Genes

DE

between

treatments

were

identified

by

as

criteria

a

-RRB-

P

b

-RRB-

minimum

fluorescent

intensity

of

units

and

c

-RRB-

fold

or

greater

difference

between

treatments

In

contrast

to

results

from

rodents

there

was

little

evidence

from

the

microarray

data

that

fatty

acid

oxidation

related

genes

were

highly

induced

by

either

CA

treatment

or

fasting

QPCR

assays

showed

statistically

significant

increased

expression

for

CAT

and

EHHADH

by

CA

treatment

and

all

but

the

last

two

genes

were

also

up-regulated

by

fasting

The

QPCR

data

showed

glucokinase

was

decreased

only

in

the

fasting

treatment

while

glycogen

synthase

was

increased

by

both

treatments

In

fatty

acid

metabolic

pathways

both

QPCR

and

microarray

data

showed

that

steroyl-CoA

desaturase

and

fatty

acid

desaturase

were

decreased

by

fasting

but

these

two

genes

as

well

as

fatty

acid

desaturase

were

increased

by

CA

treatment

The

authors

conclude

that

there

are

major

species

differences

in

the

liver

RNA

response

to

peroxisome

proliferator

ligands

like

CA

although

they

provide

additional

evidence

that

the

response

to

fasting

especially

for

mitochondrial

fatty

acid

oxidation

and

ketogenic

pathways

is

more

similar

across

species

A

recently

published

study

combined

microarray

analysis

SNP

detection

within

expression

candidates

and

association

and

physical

mapping

analyses

to

find

liver

genes

affecting

carcass

traits

These

authors

intended

to

capture

expression

differences

related

to

phenotypic

traits

-LRB-

and

minimize

other

genetic

differences

-RRB-

by

using

discordant

sib

pair

analyses

They

identified

sibs

within

an

population

from

a

Duroc

x

German

miniature

pig

cross

that

were

distinctly

different

for

eye

muscle

area

and

backfat

thickness

To

profile

the

liver

expression

in

these

sib

pairs

the

microarray

contained

well-annotated

genes

including

liver

genes

from

earlier

work

described

above

as

well

as

genes

known

to

be

important

in

hepatic

metabolism

The

liver

mRNA

from

sib

pairs

-LRB-

high

performing

-LRB-

HP

-RRB-

and

low

performing

-LRB-

LP

-RRB-

-RRB-

was

pooled

by

trait

and

hybridized

to

this

array

Overall

nine

genes

were

identified

by

t-test

as

DE

at

least

two

fold

between

HP

and

LP

groups

four

were

higher

in

HP

-LRB-

TBG

PIGSPI

DBI

and

-RRB-

and

five

were

lower

-LRB-

PTN

and

-RRB-

Ten

genes

including

six

DE

genes

were

tested

by

QPCR

on

liver

RNA

from

the

eight

individual

pigs

from

the

pooled

samples

Although

good

agreement

with

the

microarray

data

was

seen

for

most

genes

only

four

-LRB-

TBG

PEDF

and

APOH

-RRB-

were

statistically

different

between

HP

and

LP

individuals

Two

confirmed

genes

TBG

-LRB-

higher

in

HP

-RRB-

and

APO

-LRB-

higher

in

LP

-RRB-

were

screened

for

SNPs

by

re-sequencing

of

cDNAs

for

all

eight

HP/LP

animals

Of

three

SNPs

found

in

the

TBG

cDNA

sequence

one

-LRB-

A

C

at

nt

-RRB-

was

found

associated

-LRB-

P

-RRB-

with

variation

in

three

fat

traits

with

the

C

allele

associated

with

higher

fat

As

the

SNP

at

nt

changes

the

amino

acid

at

this

position

the

authors

also

checked

TBG

protein

expression

and

function

Available

serum

data

on

TBG

and

TBG

bound

metabolite

levels

showed

an

association

of

TBG

concentration

-LRB-

P

-RRB-

and

function

-LRB-

P

to

-RRB-

with

TBG

genotype

Thus

this

group

was

able

to

use

discordant

sib

pair

microarray

expression

analysis

to

identify

expression

candidates

identify

SNPs

in

one

candidate

that

was

associated

with

quantitative

phenotypes

for

fatness

and

with

relevant

biochemical

differences

in

serum

The

combination

of

evidence

at

the

genetic

expression

and

functional

levels

makes

a

strong

case

that

TBG

variation

directly

controls

part

of

the

variation

in

fatness

in

this

population

But

What

Does

It

All

Mean

Pig

Expression

Bioinformatics

and

Databases

At

this

juncture

available

swine

transcriptomic

data

especially

for

microarray

projects

is

somewhat

fragmented

and

sparse

Many

different

platforms

are

being

used

and

the

data

is

not

always

being

submitted

to

a

common

repository

The

recent

public

disclosure

of

nearly

a

million

additional

ESTs

from

different

non-normalized

libraries

by

the

Sino-Danish

consortium

-LRB-

Gorodkin

et

al.

submitted

-RRB-

will

certainly

improve

the

accuracy

of

EST

frequency

data

as

an

estimate

of

expression

level

To

become

more

efficient

at

drawing

biological

meaning

out

of

such

data

more

attention

needs

to

be

paid

to

public

sharing

of

data

and

integration

of

that

data

so

that

an

increase

in

power

is

possible

In

this

section

we

discuss

the

available

public

resources

for

pig

microarray

and

other

transcriptomic

data

and

discuss

some

of

our

efforts

to

integrate

these

platforms

and

data

sources

The

following

information

does

not

include

several

storage/analysis

efforts

on

genomic

data

that

includes

Sus

scrofa

as

one

of

the

species

These

include

mapping

databases

such

as

ArkDB

and

databases

that

link

traits

to

phenotypes

without

expression

data

such

as

OMIA

Links

to

these

and

other

sites

of

interest

to

pig

genomics

researchers

can

be

found

at

the

U.S.

Pig

Genome

Coordination

website

-LRB-

-RRB-

Two

groups

have

databases

available

for

both

expression

and

sequence

information

The

National

Center

for

Biotechnology

Information

-LRB-

NCBI

-RRB-

and

the

European

Bioinformatics

Institute

-LRB-

EBI

-RRB-

have

multiple

databases

each

designed

for

a

specific

purpose

At

NCBI

UniGene

takes

the

sequence

data

in

the

general

EST

and

nr

databases

and

clusters

them

into

single

gene

units

by

species

-LRB-

-RRB-

The

expression

database

at

NCBI

is

Gene

Expression

Omnibus

-LRB-

GEO

-RRB-

which

uses

a

specific

format

for

loading

and

exporting

data

As

of

October

GEO

currently

includes

porcine

experiments

and

the

platform

designs

for

platforms

including

the

two

large

commercial

platforms

Affymetrix

Porcine

GeneChip

and

several

versions

of

spotted

platforms

using

the

oligonucleotide

set

Of

the

experiments

the

majority

were

performed

on

microarrays

though

three

used

SAGE

The

user

interface

at

NCBI

for

text

or

BLAST-based

searches

is

advanced

allowing

searches

to

be

refined

to

search

specific

sub-databases

or

with

other

limits

In

contrast

at

EBI

all

the

sequences

are

in

a

central

repository

and

there

is

no

species-specific

clustering

database

as

at

NCBI/UniGene

The

expression

database

at

EBI

is

called

ArrayExpress

-LRB-

-RRB-

and

uses

the

Minimal

Information

About

Microarray

Experiments

-LRB-

MIAME

-RRB-

standards

created

by

the

Microarray

Gene

Expression

Data

Society

-LRB-

MGED

-RRB-

ArrayExpress

as

of

October

has

a

single

porcine

expression

study

the

main

bulk

of

the

data

being

human

and

mouse

Another

comprehensive

EST

database

is

the

Dana

Farber

Cancer

Institute

Computational

Biology

and

Functional

Genomics

Laboratory

's

Pig

Gene

Index

-LRB-

PGI

-RRB-

The

PGI

database

is

the

TIGR

Gene

Indices

information

that

was

brought

to

Dana

Farber

by

John

Quackenbush

The

PGI

database

is

similar

to

UniGene

in

that

it

clusters

ESTs

together

but

goes

a

step

further

and

provides

a

tentative

consensus

sequence

for

each

cluster

Also

unlike

UniGene

which

tries

to

group

alternative

spliced

genes

together

PGI

attempts

to

separate

them

into

their

own

unique

clusters

However

it

does

provide

a

link

that

clusters

the

tentative

alternatively

spliced

sequences

together

The

DF

database

also

provides

Gene

Ontology

-LRB-

GO

-RRB-

annotations

metabolic

pathway

information

and

predicted

oligonucleotide

sequences

and

SNP

information

for

each

of

their

TCs

Both

UniGene

and

DFGIP

data

collections

can

be

searched

using

BLAST

and

an

expression

summary

of

each

of

the

EST

's

based

on

the

libraries

and

EST

count

within

the

libraries

is

provided

Both

data

collections

can

also

be

downloaded

for

local

investigator

use

Recently

the

Sino-Danish

group

has

begun

to

release

their

EST

sequence

information

including

alignments

into

clusters

which

is

based

on

over

one

million

ESTs

-LRB-

-RRB-

They

have

submitted

their

sequences

to

the

Trace

Archive

at

NCBI

but

these

data

have

not

as

of

October

been

integrated

into

dbEST

They

have

made

their

clusters

available

online

and

have

provided

a

bulk

download

website

for

both

the

ESTs

and

the

consensus

sequences

of

their

clusters

Expression

profiles

for

all

the

genes

are

also

provided

based

on

EST

frequency

within

the

non-normalized

libraries

They

predict

SNPs

based

on

sequence

discrepancies

within

alignments

as

the

libraries

were

created

from

tissues

from

multiple

breeds

They

provide

some

online

tools

including

viewing

the

aligned

and

clustered

sequences

as

well

as

searches

against

the

database

using

BLAST

The

website

indicates

these

data

have

been

submitted

for

publication

-LRB-

Gorodkin

et

al.

submitted

-RRB-

There

are

non-comprehensive

EST

databases

which

focus

on

a

select

number

of

tissues

Among

these

is

the

Michigan

State

Center

for

Animal

Functional

Genomics

-LRB-

CAFG

-RRB-

This

database

contains

tissue

specific

porcine

EST

libraries

brain

adipose

and

skeletal

muscle

the

use

of

which

was

discussed

above

in

the

microarray

section

It

also

contains

a

mixed

tissue

porcine

library

To

annotate

the

ESTs

the

database

uses

homology

searches

to

various

NCBI

databases

including

RefSeq

and

Gene

To

search

the

libraries

keywords

based

on

this

information

transferred

from

GenBank

can

be

searched

there

is

also

an

option

to

use

BLAST

to

search

the

different

libraries

Clones

and

clusters

can

be

viewed

to

determine

which

libraries

have

sequences

donating

to

the

clusters

and

clones

are

available

for

order

In

addition

to

the

EST

information

there

is

a

private

internal

section

for

microarrays

Another

focused

database

is

the

Pig

Expression

Data

Explorer

-LRB-

PEDE

-RRB-

PEDE

also

uses

homologues

in

RefSeq

and

UniGene

to

annotate

the

EST

sequences

that

primarily

are

derived

from

tissues

of

interest

to

porcine

immunology

research

-LRB-

and

references

therein

-RRB-

They

identified

the

full-length

cDNAs

within

the

ESTs

Their

online

interface

allows

a

user

to

search

their

EST/cDNA

clusters

using

keywords

library

their

accession

numbers

and

the

corresponding

human

chromosome

It

allows

filtering

the

results

based

on

evidence

of

SNP

in

a

specific

breed

and

provides

suggested

primers

for

detection

of

the

SNP

Like

the

Sino-Danish

EST

database

and

the

PGI

database

it

provides

a

visual

alignment

of

the

ESTs

to

each

other

and

to

the

cluster

consensus

sequence

A

unique

feature

of

this

database

is

a

more

in-depth

analysis

of

artiodactyl-specific

antigens

for

furthering

the

development

of

xenotransplantation

Several

databases

are

also

in

production

at

the

moment

and

at

various

stages

of

development

One

of

these

is

under

development

at

the

University

of

Minnesota

-LRB-

-RRB-

Their

database

focuses

on

sequence

data

currently

though

they

indicate

they

plan

on

integrating

expression

data

in

the

future

and

currently

have

annotation

provided

for

the

array

Most

recently

a

new

database

annotating

the

new

Swine

Protein

Annotated

oligonucleotide

Microarray

-LRB-

SPAM

-RRB-

has

become

available

-LRB-

-RRB-

The

database

describes

the

set

of

oligonucleotide

sequences

in

the

SPAM

and

provided

the

best

Ensembl

protein

matches

and

Gene

Ontology

-LRB-

GO

-RRB-

annotations

for

each

sequence

Another

database

is

being

developed

at

the

Advanced

Food

and

Materials

in

Canada

-LRB-

-RRB-

Their

aim

is

to

integrate

various

types

of

expression

data

including

microarray

proteomics

and

metabolomics

to

compare

genetically

modified

foods

Their

first

goal

is

to

compare

the

EnviroPig

to

the

Yorkshire

A

fourth

database

currently

under

construction

is

at

Iowa

State

University

-LRB-

URL

pending

-RRB-

Our

focus

is

storage

and

analysis

of

data

from

the

Affymetrix

platform

although

platform

data

is

also

curated

One

specific

interest

is

using

expression

data

to

help

identify

tissue-selective

genes

and

across-species

expression

comparison

of

such

genes

to

recognize

evolutionarily

conserved

regulatory

modules

of

interest

to

pig

genome

scientists

Here

we

describe

some

of

our

efforts

in

this

area

integration

and

comparison

of

data

from

the

two

broad-coverage

platforms

that

currently

exist

for

the

pig

the

oligonucleotide

array

-LRB-

hereafter

abbreviated

the

Operon

array

-RRB-

and

the

Affymetrix

Porcine

GeneChip

-LRB-

abbreviated

the

Affymetrix

chip

-RRB-

both

of

which

were

discussed

above

To

integrate

the

expression

data

for

these

two

platforms

we

need

first

to

determine

which

Operon

oligonucleotide

probes

have

a

sufficient

sequence

similarity

to

the

consensus

sequences

used

to

create

the

probesets

on

the

Affymetrix

chip

so

that

the

two

elements

will

recognize

the

same

transcript

-LRB-

s

-RRB-

The

Operon

probe

sequences

were

used

as

a

BLAST

query

against

the

Affymetrix

porcine

consensus

sequences

-LRB-

Figure

-RRB-

We

set

a

cutoff

criterion

of

an

alignment

length

nucleotides

with

an

alignment

identity

of

for

pairings

between

the

probes

and

the

consensus

sequences

This

resulted

in

a

total

of

cross

platform

mappings

-LRB-

Table

-RRB-

which

fall

on

six

different

match

classes

-LRB-

-RRB-

an

Operon

probe

not

matching

any

Affymetrix

consensus

sequence

-LRB-

-RRB-

an

Affymetrix

consensus

sequences

without

an

Operon

probe

match

-LRB-

-RRB-

the

ideal

case

when

a

single

Operon

probe

matches

a

single

Affymetrix

consensus

sequences

-LRB-

-RRB-

two

or

more

Operon

probes

map

to

a

single

Affymetrix

consensus

sequence

-LRB-

-RRB-

a

single

Operon

probe

maps

to

multiple

Affymetrix

consensus

sequences

and

-LRB-

-RRB-

multiples

of

each

match

creating

a

cluster

of

probes

and

probe

sets

-LRB-

Figure

Table

-RRB-

The

different

classes

most

likely

result

from

the

difference

in

the

known

amount

of

porcine

sequence

during

the

development

of

the

probes/probe

sets

the

Operon

probes

being

designed

in

while

the

Affymetrix

probe

sets

were

designed

in

This

helps

explains

the

different

classes

Class

from

the

merging

of

old

clusters

Class

from

Affymetrix

designing

separate

probe

sets

for

alternative

transcripts

-LRB-

which

might

not

have

been

known

in

-RRB-

or

that

the

Operon

probe

is

no

longer

unique

-LRB-

for

example

now

targeting

multiple

genes

in

the

same

family

-RRB-

and

Class

from

the

joining

of

different

consensus

sequences

into

single

genes

but

then

having

alternative

splicing

Now

that

we

had

the

ability

to

directly

compare

platform

elements

we

determined

the

extent

to

which

the

two

platforms

agree

on

assaying

for

the

presence

or

absence

of

expression

for

these

genes

in

a

common

tissue

Two

Affymetrix

experiments

and

one

Operon

experiment

were

used

to

calculate

the

agreement

of

the

presence/absence

calls

of

the

platform

pairings

created

by

BLAST

All

three

experiments

were

performed

on

normal

liver

tissue

the

first

Affymetrix

experiment

-LRB-

-RRB-

collected

data

from

the

same

RNA

on

six

different

chips

the

second

Affymetrix

experiment

-LRB-

-RRB-

data

was

collected

using

four

separate

RNA

samples

on

four

different

arrays

The

Operon

-LRB-

O

-RRB-

experimental

data

on

an

additional

six

RNA

samples

was

available

from

our

previous

study

provides

the

present/absent

calls

for

the

Affymetrix

GeneChip

and

for

the

Operon

array

we

used

presence/absence

as

calculated

by

Zhao

et

al.

To

take

a

step

beyond

simple

agreement

of

presence/absence

we

also

calculated

the

correlation

of

expression

level

for

each

gene

as

estimated

by

each

platform

We

ranked

each

gene

by

expression

level

and

used

the

Spearman

's

Rank

correlation

to

determine

the

extent

of

agreement

for

relative

expression

of

each

gene

within

the

common

set

of

genes

Across

the

two

platforms

we

saw

a

significant

amount

of

agreement

in

declaring

a

gene

expressed

-LRB-

Table

-RRB-

Of

the

different

classes

Class

had

both

the

highest

agreement

-LRB-

-RRB-

and

highest

correlation

-LRB-

for

Operon

to

either

array

and

between

Affymetrix

experiments

-RRB-

The

other

three

classes

had

similar

correlations

for

the

Operon

to

experiment

to

for

the

Operon

to

experiment

and

to

for

the

to

comparison

However

they

differed

in

their

agreement

for

Class

for

Class

and

for

Class

When

all

pairs

are

considered

we

found

an

to

for

the

cross-platform

comparisons

and

for

the

within

platform

comparison

with

an

present/absent

agreement

of

Since

Class

has

the

lowest

agreement

and

correlations

-LRB-

equal

to

Class

for

cross

platform

correlations

but

with

a

lower

within

platform

correlation

-RRB-

this

result

indicates

that

the

Operon

probes

could

cross-hybridize

to

either

alternative

splice

variants

or

gene

family

members

with

close

sequence

homology

that

the

Affymetrix

platform

was

designed

to

assay

separately

Further

investigation

is

needed

to

see

if

the

Operon

probe

is

present

while

the

Affymetrix

probe

sets

are

absent

or

if

there

are

multiple

Affymetrix

probe

sets

present

while

the

single

Operon

is

absent

The

results

for

Class

which

have

the

highest

agreement

and

the

best

correlation

lends

support

to

the

proposal

that

multiple

Operon

probes

target

the

same

gene

product

likely

by

the

clustering

of

sequences

from

the

time

the

Operon

chip

was

developed

to

the

time

the

Affymetrix

chip

was

developed

While

these

results

already

show

good

agreement

between

platforms

it

will

be

important

to

update

the

sequence

comparisons

on

a

regular

basis

especially

with

the

Sino-Danish

data

as

well

as

the

genome

sequence

coming

online

As

part

of

our

database

we

plan

to

develop

the

means

to

regularly

develop

a

consensus

sequence

for

each

gene

from

all

available

sequences

to

map

the

various

probes

and

probe

sets

to

each

other

Beyond

EST

and

microarray

databases

as

noted

above

the

USDA

Beltsville

group

has

set

up

a

database

for

quantitative

real-time

PCR

assays

for

genes

related

to

nutrition

and

immunity

-LRB-

-RRB-

All

assays

are

based

on

the

Taqman

technology

so

sequences

for

both

a

primer

pair

as

well

as

the

dual-labeled

probe

are

presented

Of

the

almost

genes

identified

they

have

validated

assays

for

available

of

which

are

known

to

be

cross-reactive

in

humans

and

another

candidate

assays

are

being

validated

Many

of

these

assays

have

been

published

by

this

group

and

their

collaborators

In

addition

to

creating

databases

for

porcine

transcriptomics

groups

are

using

available

stored

information

for

addressing

biological

information

and

additional

annotation

In

a

purely

bioinformatic

analyses

of

porcine

expressed

sequences

Jiang

and

collaborators

used

human

gene

sequences

and

mapped

by

using

BLAST

against

the

database

at

NCBI

nearly

of

them

to

a

porcine

EST

in

either

embryonic

or

reproductive

tissue

Of

these

were

found

only

in

the

embryo

and

were

only

in

reproductive

tissues

while

were

found

in

both

tissues

Therefore

they

found

a

total

of

ESTs

present

in

embryos

and

in

reproductive

tissues

Conclusions

Functional

genomics

data

primarily

at

the

RNA

level

currently

is

accumulating

rapidly

for

the

pig

species

Excellent

sensitive

and

broadly

useful

tools

are

already

available

and

more

will

be

become

available

within

the

next

year

Annotation

of

the

draft

porcine

genome

sequence

expected

in

late

and

into

will

allow

rapid

integration

of

the

gene

expression

data

discussed

above

with

gene

sequences

potential

splice

sites

and

gene

families

within

the

draft

sequence

Advances

in

other

areas

of

investigation

in

pig

genetics

and

genomics

can

be

anticipated

One

such

area

would

be

the

ability

to

find

common

regulatory

sites

within

flanking

DNA

of

co-expressed/co-regulated

genes

leading

to

the

identification

of

critical

regulatory

proteins

in

common

with

or

distinct

from

those

found

in

other

species

Such

information

will

reinforce

the

discovery

of

pathways

through

gene

list

annotations

improve

pathway

understanding

through

differentiation

of

direct

targets

from

indirect

targets

of

transcriptional

signals

and

would

identify

targets

for

manipulation

of

complete

pathways

and

systems

We

can

also

anticipate

the

comprehensive

integration

of

linkage

mapping

and

expression

profiling

of

the

same

population

termed

eQTL

studies

Such

integration

of

functional

and

structural

genomic

data

will

dramatically

improve

our

understanding

of

the

genetic

architecture

controlling

quantitative

traits

in

pigs

eQTL

analyses

may

lead

to

the

first

application

of

systems

biology

to

genetic

improvement

in

the

pig

through

the

identification

of

cis-regulatory

variation

controlling

an

economically

important

phenotype

As

we

move

toward

such

a

systems

biology

approach

in

animal

genomics

access

to

and

integration

of

these

data

sources

will

become

critical

Thus

a

continuing

need

is

for

bioinformatics

to

integrate

the

structural

and

functional

data

we

are

generating

to

inform

our

investigations

It

is

unfortunate

that

many

datasets

are

not

being

submitted

to

public

repositories

it

is

our

hope

and

expectation

that

journals

will

both

facilitate

and

require

such

public

submissions

as

is

more

the

norm

in

the

biomedical

fields

Many

groups

are

working

on

this

bioinformatics

effort

and

therefore

the

near

future

in

pig

genomics

is

especially

exciting

The

long-term

goal

of

the

application

of

genome

data

to

improve

pig

genetics

will

be

reached

when

we

can

apply

a

more

robust

understanding

of

pig

genetic

pathways

to

identify

variation

at

genes

controlling

important

traits

of

interest

in

the

pig

Supplementary

Material

Supplementary

Table

Click

here

for

additional

data

file

Supplementary

Table

Click

here

for

additional

data

file

transcriptomics
microarray
porcine
quantitative pcr
bioinformatics