Behavioral

genomics

of

honeybee

foraging

and

nest

defense

The

honeybee

has

been

the

most

important

insect

species

for

study

of

social

behavior

The

recently

released

draft

genomic

sequence

for

the

bee

will

accelerate

honeybee

behavioral

genetics

Although

we

lack

sufficient

tools

to

manipulate

this

genome

easily

quantitative

trait

loci

-LRB-

QTLs

-RRB-

that

influence

natural

variation

in

behavior

have

been

identified

and

tested

for

their

effects

on

correlated

behavioral

traits

We

review

what

is

known

about

the

genetics

and

physiology

of

two

behavioral

traits

in

honeybees

foraging

specialization

-LRB-

pollen

versus

nectar

-RRB-

and

defensive

behavior

and

present

evidence

that

map-based

cloning

of

genes

is

more

feasible

in

the

bee

than

in

other

metazoans

We

also

present

bioinformatic

analyses

of

candidate

genes

within

QTL

confidence

intervals

-LRB-

CIs

-RRB-

The

high

recombination

rate

of

the

bee

made

it

possible

to

narrow

the

search

to

regions

containing

only

predicted

peptides

for

each

QTL

although

CIs

covered

large

genetic

distances

Knowledge

of

correlated

behavioral

traits

comparative

bioinformatics

and

expression

assays

facilitated

evaluation

of

candidate

genes

An

overrepresentation

of

genes

involved

in

ovarian

development

and

insulin-like

signaling

components

within

pollen

foraging

QTL

regions

suggests

that

an

ancestral

reproductive

gene

network

was

co-opted

during

the

evolution

of

foraging

specialization

The

major

QTL

influencing

defensive/aggressive

behavior

contains

orthologs

of

genes

involved

in

central

nervous

system

activity

and

neurogenesis

Candidates

at

the

other

two

defensive-behavior

QTLs

include

modulators

of

sensory

signaling

-LRB-

serotonin

receptor

arrestin

and

receptor

-RRB-

These

studies

are

the

first

step

in

linking

natural

variation

in

honeybee

social

behavior

to

the

identification

of

underlying

genes

Introduction

Mapping

genes

for

natural

variation

in

behavior

The

need

to

understand

within

and

between-population

variation

in

behavior

especially

social

behavior

and

its

evolution

remains

a

central

theme

in

biology

Honeybee

societies

have

facultatively

sterile

female

workers

and

a

specialized

workforce

Honeybee

social

behavior

is

dramatically

demonstrated

by

the

efforts

of

worker

bees

collecting

and

hoarding

pollen

and

nectar

and

mass

stinging

responses

in

defense

of

the

nest

Division

of

labor

within

a

honeybee

nest

is

a

consequence

of

age-related

changes

in

physiology

plus

genetic

variation

within

the

colony

for

tendency

to

perform

specific

tasks

-LRB-

Page

and

Robinson

-RRB-

A

number

of

studies

have

demonstrated

genetic

variation

within

and

between

honeybee

populations

in

specialization

for

water

nectar

and

pollen

collecting

-LRB-

reviewed

in

Page

et

al.

-RRB-

and

variation

in

defensive

responses

-LRB-

reviewed

in

Breed

et

al.

-RRB-

The

genetic

architectures

of

these

two

task

sets

are

more

thoroughly

characterized

than

other

behavioral

traits

in

the

honeybee

For

these

reasons

we

sought

to

determine

whether

it

is

possible

to

define

within

a

manageable

number

of

candidate

genes

regions

influencing

these

behaviors

Quantitative

trait

locus

-LRB-

QTL

-RRB-

mapping

studies

provide

information

about

the

genetic

architecture

of

a

trait

that

can

not

be

determined

by

other

methods

This

information

includes

estimates

for

the

number

and

location

of

loci

influencing

population

variation

in

the

trait

the

mode

of

inheritance

of

these

loci

-LRB-

dominance

epistasis

or

imprinting

effects

-RRB-

and

amount

of

phenotypic

variance

each

locus

accounts

for

-LRB-

Lander

and

Botstein

-RRB-

But

QTL

studies

do

not

have

a

good

track

record

for

isolation

of

causal

genes

For

example

genes

for

only

of

QTLs

have

been

cloned

-LRB-

Flint

et

al.

-RRB-

Identifying

genes

responsible

for

naturally

occurring

phenotypic

variation

is

especially

challenging

for

behavioral

traits

where

complex

interactions

of

genes

and

the

environment

are

expected

-LRB-

Flint

Plomin

and

McGuffin

Arnholdt

and

Mackay

Goldman

et

al.

-RRB-

The

endgame

in

determining

nucleotide

sequence

variation

responsible

for

natural

variation

in

honeybee

behavior

will

require

identification

of

QTLs

confirmation

in

independent

crosses

fine-scale

mapping

expression

assays

and

finally

experimental

modulation

of

gene

expression

or

complementation

tests

-LRB-

Mackay

-RRB-

The

biggest

problem

in

taking

a

map-based

approach

to

isolation

of

genes

is

that

confidence

intervals

-LRB-

CIs

-RRB-

for

QTL

location

are

usually

quite

large

The

size

of

the

CI

primarily

depends

on

the

number

of

individuals

in

the

mapping

population

the

number

of

genetic

markers

scored

the

magnitude

of

effect

that

the

QTL

has

on

the

phenotype

and

the

recombination

rate

-LRB-

numbers

of

crossovers

per

unit

of

chromosomal

distance

-RRB-

The

first

two

factors

sample

size

and

marker

density

are

important

for

reducing

CIs

but

they

are

subject

to

diminishing

returns

as

more

individuals

or

more

markers

are

added

to

the

experiment

The

effect

of

the

QTL

is

a

major

concern

because

QTLs

often

account

for

only

a

small

proportion

-LRB-

often

-RRB-

of

phenotypic

variance

The

QTL

effect

can

only

be

increased

up

to

a

certain

level

by

improving

the

phenotypic

assay

and

using

the

most

appropriate

cross

-LRB-

Darvasi

Arnholdt

and

Mackay

-RRB-

On

the

other

hand

recombination

rate

can

have

a

large

effect

on

the

size

of

chromosomal

regions

covered

by

CIs

because

the

physical

size

scales

inversely

with

recombination

rate

For

this

reason

fine-scale

mapping

studies

are

often

designed

to

effectively

increase

recombination

by

taking

advantage

of

historical

recombination

events

through

linkage-association

studies

in

populations

or

by

developing

multigeneration

recombinant

inbred

lines

-LRB-

Darvasi

-RRB-

In

the

honeybee

map

resolution

is

enhanced

by

a

meiotic

recombination

rate

that

currently

ranks

highest

among

metazoans

-LRB-

Hunt

and

Page

Solignac

et

al.

-RRB-

so

that

large

genetic

distances

correspond

to

relatively

small

physical

regions

containing

few

genes

In

this

study

we

review

what

is

currently

known

about

the

genetics

of

honeybee

foraging

and

defensive

behaviors

and

how

a

map-based

approach

leads

us

to

a

manageable

number

of

candidate

genes

that

seem

to

fit

what

is

known

of

the

behavioral

patterns

Information

from

the

draft

honeybee

genome

sequence

-LRB-

Honeybee

Genome

Sequencing

Consortium

HGSC

-RRB-

was

used

to

delimit

sets

of

candidate

genes

flanked

by

marker

sequences

that

were

identified

in

prior

QTL

studies

and

expression

data

from

candidate

genes

provided

additional

information

on

likely

candidates

Behavioral

genetics

of

foraging

Foraging

specialization

involves

two

components

the

onset

of

foraging

that

establishes

division

of

labor

between

foragers

and

bees

that

perform

tasks

inside

the

hive

and

the

subsequent

bias

in

foraging

for

either

pollen

or

nectar

These

components

are

related

Bees

from

lines

selected

for

storing

more

surplus

pollen

-LRB-

hoarding

-RRB-

are

more

likely

to

initiate

foraging

earlier

in

life

and

to

specialize

in

pollen

collection

than

bees

from

lines

selected

for

low

pollen

hoarding

These

associations

are

also

linked

to

sensory

response

in

that

bees

selected

for

higher

levels

of

pollen

hoarding

are

more

responsive

to

low

concentrations

of

sugar

-LRB-

less

discriminatory

-RRB-

when

tested

with

the

proboscis

extension

assay

-LRB-

Fig.

and

Page

et

al.

-RRB-

This

link

between

sucrose

responsiveness

and

the

task

of

pollen

foraging

is

also

present

in

wild-type

bees

that

have

not

been

selected

for

pollen

hoarding

-LRB-

Scheiner

et

al.

-RRB-

Fig.

and

phenotypic

associations

involved

in

foraging

division

of

labor

Arrows

indicate

significant

correlations

between

phenotypic

traits

at

the

levels

of

behavior

hormonal

signaling

and

development

and

associations

between

traits

and

genotypes

at

specific

QTLs

-LRB-

pln

-RRB-

Colored

lines

indicate

relative

titers

of

specific

hormones

The

picture

illustrates

a

method

for

determining

the

threshold

concentration

of

sugar

that

a

bee

will

respond

to

by

extending

its

proboscis

or

tongue

QTLs

were

mapped

based

on

whole-colony

behavioral

traits

and

QTL

effects

were

subsequently

confirmed

based

on

the

behavior

of

individual

bees

Three

pollen

QTLs

designated

as

and

were

detected

-LRB-

Hunt

et

al.

Page

et

al.

-RRB-

based

on

the

quantity

of

pollen

in

colonies

from

a

backcross

population

derived

from

high

and

low

pollen-hoarding

strains

Association

of

marker

alleles

near

the

QTLs

with

individual

foraging

traits

within

single

backcross

families

of

bees

confirmed

the

effects

of

and

on

behavior

and

were

associated

with

the

size

of

the

pollen

loads

collected

by

workers

-LRB-

Fig.

and

b

-RRB-

and

were

shown

to

influence

the

discrimination

for

the

sugar

concentration

of

the

nectar

collected

-LRB-

Hunt

et

al.

Page

et

al.

Fig.

c

-RRB-

Subsequent

association

studies

using

a

candidate

gene

AmFor

as

a

marker

have

mapped

and

confirmed

an

additional

QTL

region

designated

as

-LRB-

Rueppell

et

al.

-RRB-

This

QTL

maps

to

about

cM

from

Allelic

variation

and

pleiotropic

effects

of

these

QTLs

have

been

associated

with

sucrose

responsiveness

and

age

at

onset

of

foraging

-LRB-

Fig.

and

Rueppell

et

al.

-RRB-

Fig.

were

mapped

based

on

the

amount

of

pollen

stored

in

combs

of

colonies

and

confirmed

based

on

individual

behavior

Solid

bars

represent

linkage

groups

with

markers

Markers

used

in

confirmation

studies

are

shown

Orthologs

of

fly

genes

are

indicated

with

arrows

Dashed

lines

indicate

CIs

Sequenced

markers

are

underlined

No

figure

is

shown

for

because

it

was

mapped

by

association

to

one

marker

-LRB-

AmFOR

-RRB-

rather

than

by

interval

mapping

Map

on

the

left

is

the

localization

of

the

QTL

based

on

colony

pollen

stores

Map

on

the

right

is

based

on

response

thresholds

to

sucrose

of

individual

worker

bees

map

on

the

left

is

based

on

colony

pollen

stores

in

a

cross

between

European

strains

and

the

map

on

the

right

is

based

on

a

European

by

African

strain

cross

map

is

based

on

colony

pollen

stores

Preferential

foraging

for

either

a

nectar

or

protein

source

such

as

pollen

are

sequential

parts

of

the

gonotrophic

cycle

of

many

insect

females

When

nonreproductive

females

tend

to

forage

for

nectar

as

a

carbohydrate

source

for

maintenance

When

reproductively

active

insects

such

as

solitary

bees

and

mosquitoes

seek

protein

that

is

incorporated

into

eggs

-LRB-

Amdam

et

al.

-RRB-

Although

worker

honeybees

are

facultatively

sterile

they

can

produce

eggs

if

their

ovaries

develop

sufficiently

as

happens

in

the

absence

of

a

queen

Amdam

et

al.

-LRB-

-RRB-

hypothesized

that

remnants

of

the

ancestral

gonotrophic

cycle

and

the

correlated

foraging

behavior

remain

and

drive

foraging

behavior

-LRB-

Fig.

-RRB-

In

support

of

this

hypothesis

it

was

established

that

workers

from

the

high

pollen-hoarding

strain

are

characterized

by

elevated

titers

of

the

conserved

yolk

precursor

vitellogenin

and

have

larger

and

more

active

ovaries

than

low

strain

bees

It

was

also

found

that

bees

that

were

unselected

for

pollen

hoarding

but

had

enlarged

ovaries

foraged

earlier

in

life

showed

a

preference

for

pollen

foraging

and

collected

nectar

of

lower

concentration

than

bees

with

fewer

ovarioles

Thereby

wild

type

bees

show

the

same

correlated

phenotypes

that

differ

between

high

and

low

pollen-hoarding

strains

-LRB-

Amdam

et

al.

-RRB-

In

honeybees

ovariole

number

is

determined

during

the

third

larval

instar

through

a

nutrient-dependent

endocrine

signaling

cascade

The

endocrine

factors

juvenile

hormone

and

ecdysteroids

are

involved

in

the

initiation

of

vitellogenin

expression

at

adult

emergence

and

vitellogenin

and

juvenile

hormone

interact

during

adult

life

to

affect

sensory

responsiveness

and

onset

of

foraging

behavior

-LRB-

Guidugli

et

al.

-RRB-

In

solitary

insects

endocrine

cascades

involving

juvenile

hormone

and

ecdysteroids

have

pleiotropic

effects

on

sensory

tuning

yolk

protein

production

ovarian

physiology

and

life

span

-LRB-

Amdam

et

al.

Flatt

et

al.

Guidugli

et

al.

-RRB-

This

hormonal

pleiotropy

appears

to

be

regulated

by

upstream

signaling

through

the

insulin/insulin-like

signaling

-LRB-

IIS

-RRB-

pathway

-LRB-

Claeys

et

al.

Flatt

et

al.

Tu

et

al.

-RRB-

The

association

between

traits

in

high

and

low

pollen-hoarding

bees

therefore

suggests

that

honeybee

foraging

division

of

labor

has

evolved

from

an

ancestral

reproductive

regulatory

network

involving

IIS

With

knowledge

of

the

association

between

components

of

physiology

and

foraging

behavior

we

expected

an

overrepresentation

of

genes

involved

in

IIS

and

ovarian

development

within

the

CIs

for

pollen

QTLs

Behavioral

genetics

of

defensive

behavior

Honeybee

defensive

behavior

is

not

as

thoroughly

characterized

as

foraging

behavior

in

terms

of

correlated

physiological

and

sensory

traits

Honeybees

exhibit

defensive

behavior

near

the

nest

but

highly

defensive

bees

may

pursue

for

considerable

distances

away

from

the

nest

Defensive

behavior

involves

at

least

two

tasks

guarding

behavior

at

the

hive

entrance

and

flying

out

and

stinging

Guards

specialize

in

exploratory

behavior

in

the

nest

entrance

They

learn

to

recognize

the

hydrocarbon

blend

in

the

cuticles

of

their

nestmates

by

olfaction

and

they

reject

non-nestmates

by

biting

or

stinging

Only

of

workers

have

been

observed

to

guard

the

entrance

during

their

lifetime

-LRB-

Moore

et

al.

-RRB-

Both

the

number

of

days

that

individuals

in

a

colony

persist

at

guarding

and

the

number

of

bees

guarding

the

nest

entrance

correlate

with

the

intensity

of

the

stinging

response

-LRB-

Arechavaleta-Velasco

and

Hunt

Breed

et

al.

-RRB-

Multiple

sensory

modalities

influence

stinging

behavior

A

moving

visual

stimulus

usually

is

necessary

to

release

stinging

behavior

-LRB-

Free

-RRB-

Substrate

vibrations

also

increase

the

chance

of

a

mass

stinging

response

Alarm

pheromone

also

is

an

important

component

of

colony

defense

This

pheromone

blend

is

released

from

the

sting

apparatus

during

the

act

of

stinging

and

as

guards

extrude

their

stings

at

the

colony

entrance

in

response

to

relevant

stimuli

A

transient

increase

in

metabolic

rate

occurs

after

exposure

of

bees

to

alarm

pheromone

and

this

increased

rate

genetically

correlates

with

the

defensiveness

of

colonies

-LRB-

Southwick

and

Moritz

Moritz

and

Southwick

Andere

et

al.

-RRB-

Although

the

alarm

pheromone

components

vary

with

strains

of

bees

QTLs

influencing

this

variation

were

distinct

from

QTLs

influencing

stinging

behavior

-LRB-

Hunt

et

al.

-RRB-

Defensive

strains

of

bees

respond

more

quickly

to

all

of

these

stimuli

Crosses

involving

highly

defensive

African-derived

honeybees

and

low-defensive

European

races

were

used

to

map

putative

sting

QTLs

based

on

colony-level

stinging

assays

at

hive

entrances

-LRB-

Hunt

et

al.

-RRB-

Subsequent

crosses

with

stocks

unrelated

to

the

first

studies

confirmed

that

three

sting

QTLs

affect

individual

guarding

behavior

because

guards

from

a

backcross

family

were

more

likely

to

have

the

allele

from

the

defensive

parent

of

the

queen

mother

than

were

sisters

chosen

at

random

-LRB-

Fig.

Arechavaleta-Velasco

et

al.

-RRB-

These

sting

QTLs

also

were

associated

with

higher

activity

levels

of

colonies

which

was

assessed

as

their

tendency

to

fly

up

or

to

sting

when

colonies

were

opened

-LRB-

Hunt

et

al.

-RRB-

The

QTL

that

had

the

largest

effect

on

the

phenotypic

variance

of

colony

stinging

responses

was

shown

to

influence

individual

stinging

behavior

in

two

independent

studies

-LRB-

Guzmán-Novoa

et

al.

Arechavaleta-Velasco

et

al.

-RRB-

Higher

activity

levels

faster

stinging

responses

and

greater

sensitivity

to

stimuli

exhibited

by

high-defensive

strains

suggest

that

sensory

signaling

pathways

and

heightened

neuronal

activity

in

the

central

nervous

system

-LRB-

CNS

-RRB-

are

involved

in

the

defensive

response

so

we

searched

the

QTL

CIs

for

conserved

genes

with

neuronal

functions

Fig.

and

phenotypic

correlations

in

defensive

responses

and

specific

QTLs

Arrows

indicate

significant

associations

between

QTL

genotypes

and

behavioral

traits

and

between

individual

guarding

behavior

and

colony

stinging

response

Materials

and

methods

QTL

mapping

and

confirmation

QTLs

influencing

traits

related

to

foraging

behavior

or

defensive

behavior

were

mapped

and

confirmed

previously

-LRB-

Hunt

et

al.

Page

et

al.

Rueppell

et

al.

-RRB-

but

new

analyses

were

performed

on

the

data

to

include

additional

markers

and

in

addition

sting

QTLs

were

reanalyzed

by

combining

two

traits

as

stated

below

Maps

were

based

on

crosses

that

are

appropriate

for

a

haplodiploid

colonial

species

For

QTL

detection

haploid

drone

progeny

of

an

queen

were

each

backcrossed

to

sister

queens

-LRB-

that

were

daughters

of

a

single

haploid

drone

-RRB-

Colony

phenotypes

were

correlated

with

inheritance

of

paternal

marker

alleles

Whole-colony

phenotypes

resulted

from

the

behavior

of

many

individuals

such

as

the

number

of

stings

in

a

leather

patch

in

min

or

the

area

of

wax

combs

containing

stored

pollen

Confirmation

studies

all

involved

the

use

of

queens

backcrossed

to

single

drones

and

analyses

of

worker

progeny

for

individual

behavior

and

genotypes

Linkage

maps

that

were

used

to

identify

candidate

genes

were

constructed

with

JoinMap

-LRB-

-RRB-

and

MapManager

QTX

software

using

the

Kosambi

mapping

function

-LRB-

Van

Ooijen

and

Voorrips

Manly

et

al.

-RRB-

and

interval

mapping

was

performed

with

MapQTL

-LRB-

v.

Van

Ooijen

et

al.

-RRB-

Interval

mapping

was

performed

as

previously

described

except

that

new

analyses

were

used

to

map

defensive-behavior

QTL

that

combined

two

sets

of

phenotypic

data

Individual

z

scores

for

the

two

correlated

traits

the

number

of

stings

in

min

and

ratings

for

the

degree

to

which

bees

flew

up

at

the

beekeeper

during

colony

manipulations

were

averaged

to

produce

composite

z

scores

used

for

interval

mapping

The

z

scores

were

calculated

using

the

formula

z

-LRB-

y

μ

-RRB-

δ

in

which

y

is

the

phenotypic

value

μ

is

the

mean

and

δ

is

the

standard

deviation

This

provides

a

new

trait

value

with

a

mean

of

zero

and

standard

deviation

of

one

The

colonies

were

rated

on

a

relative

scale

of

one

to

five

based

on

the

researchers

experience

for

the

tendency

of

bees

to

fly

up

during

colony

manipulations

Ratings

from

two

observation

periods

were

averaged

This

analysis

resulted

in

somewhat

reduced

CIs

and

higher

LOD

scores

for

the

three

QTLs

-LRB-

and

respectively

for

and

-RRB-

A

map

with

markers

was

used

to

locate

candidate

genes

for

sting

QTLs

and

two

maps

each

with

about

markers

were

used

to

locate

pln

QTLs

Markers

in

common

between

the

dense

map

and

other

maps

were

used

to

interpolate

the

location

of

pln

QTL

and

align

QTL

CIs

with

the

physical

map

because

more

cloned

markers

were

available

from

the

dense-map

population

Simple

interval

mapping

was

used

rather

than

multiple

factor

interval

mapping

to

determine

CIs

to

have

a

more

conservative

-LRB-

inclusive

-RRB-

search

for

candidate

genes

The

genomic

region

within

LOD

value

of

the

LOD-score

peak

was

used

to

define

each

CI

for

QTL

location

This

corresponds

to

an

approximate

CI

for

QTL

location

in

a

dense-marker

map

-LRB-

Dupuis

and

Siegmund

-RRB-

The

LOD

score

is

a

log-likelihood

estimator

for

the

probability

that

a

QTL

influencing

the

trait

is

present

at

a

given

map

position

-LRB-

Lander

and

Botstein

-RRB-

The

honeybee

genome

assembly

-LRB-

v.

-RRB-

and

positions

of

sequenced

markers

were

used

to

identify

predicted

peptides

that

were

evaluated

for

likely

gene

function

Cloning

and

sequencing

marker

fragments

Sequences

derived

from

DNA

markers

were

obtained

to

integrate

physical

and

genetic

maps

More

than

marker

fragments

not

only

from

-LRB-

primarily

-RRB-

amplified

fragment

length

polymorphic

markers

-LRB-

AFLPs

-RRB-

but

also

from

random

amplified

polymorphic

DNAs

-LRB-

RAPDs

-RRB-

and

microsatellites

linked

to

behavioral

QTLs

and

throughout

the

genome

were

cloned

and

sequenced

The

first

step

in

cloning

was

the

excision

of

fragments

from

gels

For

AFLPs

from

polyacrylamide

gels

products

were

re-amplified

and

resolved

on

agarose

gels

to

verify

correct

size

before

cloning

with

the

TOPO-TA

cloning

kit

and

the

vector

-LRB-

Invitrogen

Carlsbad

CA

-RRB-

RAPD

marker

fragments

were

excised

from

agarose

gels

and

cloned

into

the

same

vector

Multiple

sequences

were

obtained

from

each

clone

and

the

consensus

sequence

was

aligned

with

the

genomic

sequence

scaffolds

-LRB-

HGSC

-RRB-

using

the

nucleotide

nucleotide

basic

local

alignment

search

tool

-LRB-

blastn

-RRB-

algorithm

with

Pymood

BLAST

software

-LRB-

Allometra

Davis

CA

-RRB-

RACE

and

cDNA

cloning

Before

expression

analyses

by

quantitative

real-time

polymerase

chain

reaction

-LRB-

qRT-PCR

-RRB-

cDNA

cloning

was

performed

to

confirm

sequences

and

the

gene

prediction

-LRB-

location

of

introns

and

exons

-RRB-

and

to

provide

information

on

sequence

variation

within

some

of

the

candidate

genes

In

the

case

of

the

serotonin

receptor

this

process

provided

complete

sequence

of

the

gene

by

making

primers

based

on

sequence

of

a

putative

G

protein-coupled

receptor

-LRB-

GPCR

-RRB-

Rapid

amplification

of

cDNA

ends

-LRB-

RACE

-RRB-

and

cloning

was

performed

using

kits

and

manufacturers

instructions

Total

RNA

was

extracted

from

individual

bees

using

the

RNAqueous

kit

-LRB-

Ambion

Austin

TX

-RRB-

The

cDNA

was

synthesized

using

the

SMART

PCR

cDNA

Synthesis

kit

-LRB-

SMART

simple

modular

architecture

research

tool

BD

Biosciences

Palo

Alto

CA

-RRB-

The

cDNA

clones

were

obtained

using

the

TOPO-TA

kit

and

the

vector

-LRB-

Invitrogen

-RRB-

Clones

were

sequenced

from

multiple

worker

bees

Several

sequence

reads

were

obtained

from

each

clone

Comparative

bioinformatics

This

study

is

based

on

predicted

peptides

from

the

draft

sequence

-LRB-

HGSC

-RRB-

However

gene

ontology

-LRB-

GO

-RRB-

terms

and

functional

annotation

of

many

of

the

homologous

genes

are

incomplete

For

this

reason

further

analyses

were

performed

Predicted

peptides

from

the

HGSC

dataset

that

were

found

within

QTL

CIs

by

first

using

blastn

to

determine

which

sequence

scaffolds

from

the

genome

assembly

contained

sequences

corresponding

to

markers

within

the

CI

Then

scaffolds

were

searched

for

presence

of

predicted

peptides

using

protein

nucleotide

translation

-LRB-

tblastn

-RRB-

Predicted

peptides

from

the

QTL

CIs

were

used

to

search

the

nonredundant

database

-LRB-

using

protein

protein

BLAST

-LSB-

blastp

-RSB-

-RRB-

at

the

National

Center

for

Biotechnology

Information

website

-LRB-

-RRB-

Protein

domain

information

gene

similarities

and

GO

terms

of

homologs

or

orthologs

were

recorded

Literature

and

website

searches

were

performed

to

assign

putative

functions

based

on

reports

from

homologous

genes

of

various

species

Quantitative

real-time

PCR

Some

candidate

genes

for

defensive

behavior

QTLs

were

tested

for

differential

expression

to

better

evaluate

their

potential

for

influencing

behavior

These

were

chosen

from

a

list

of

genes

we

were

initially

interested

in

based

on

functional

studies

in

other

species

Two

families

of

worker

bees

were

used

a

low-defensive

source

and

high-defensive

source

each

having

a

queen

naturally

mated

to

about

drones

The

source

families

differed

in

the

number

of

stings

per

minute

deposited

in

a

leather

target

-LRB-

for

low

line

and

more

than

for

the

high-defensive

source

-RRB-

using

a

standard

assay

-LRB-

Hunt

et

al.

-RRB-

Although

it

is

not

known

at

which

life

stage

a

gene

might

exert

its

influence

on

defensive

behavior

bees

that

are

to

old

are

much

more

likely

to

sting

than

younger

bees

Workers

were

collected

within

h

of

emergence

from

brood

combs

placed

in

an

incubator

or

marked

and

co-fostered

in

an

unrelated

hive

and

then

collected

days

later

Co-fostering

was

performed

to

eliminate

potential

environmental

effects

between

hives

All

bees

were

frozen

in

liquid

nitrogen

and

kept

at

°C

before

RNA

extraction

Heads

of

eight

to

nine

bees

from

each

of

the

two

families

were

removed

and

RNA

was

extracted

using

the

RNAqueous

kit

-LRB-

Ambion

-RRB-

RNA

yield

was

quantified

using

Ribogreen

-LRB-

Molecular

Probes

-RRB-

dye

on

a

fluorometer

-LRB-

Turner

Biosystems

Sunnyvale

CA

-RRB-

An

aliquot

of

RNA

was

treated

with

DNAse

-LRB-

DNAfree

kit

from

Ambion

-RRB-

to

remove

any

genomic

DNA

contamination

before

cDNA

synthesis

The

cDNA

template

for

qRT-PCR

was

generated

according

to

Puthoff

et

al.

-LRB-

-RRB-

For

first-strand

cDNA

synthesis

the

SuperScript

First

Strand

cDNA

Synthesis

kit

-LRB-

Invitrogen

-RRB-

was

used

as

per

manufacturers

protocol

The

cDNA

synthesis

was

monitored

in

a

parallel

tracer

reaction

as

follows

A

aliquot

was

removed

from

each

sample

and

mixed

with

μl

of

a

dilution

of

dCTP

-LRB-

dCTP

deoxycytidine

triphosphate

Amersham

Piscataway

NJ

-RRB-

in

water

The

remaining

μl

of

each

reverse

transcriptase

reaction

and

the

corresponding

tracer

reaction

were

incubated

at

°C

for

h.

Reactions

were

terminated

at

°C

for

min

then

chilled

on

ice

The

reactions

were

used

to

quantify

the

amount

of

cDNA

synthesized

in

the

larger

experimental

samples

The

reactions

were

spotted

onto

filters

-LRB-

Fisher

Fairlawn

NJ

-RRB-

dried

for

min

and

then

washed

four

times

for

min

each

in

M

sodium

phosphate

buffer

-LRB-

M

of

monobasic

and

M

of

dibasic

in

l

of

water

-RRB-

After

two

rinses

in

water

filters

were

washed

in

EtOH

and

allowed

to

dry

Each

filter

was

placed

in

a

scintillation

vial

containing

ml

of

ScintiVerse

-LRB-

Fisher

-RRB-

and

radiation

from

the

newly

synthesized

cDNA

was

quantified

in

a

scintillation

counter

Resulting

counts

were

used

to

normalize

the

cDNA

from

the

corresponding

reverse

transcriptase

reactions

to

a

final

concentration

of

ng

per

μl

of

sample

qRT-PCR

was

conducted

on

an

ABI

using

the

following

mixture

μl

of

normalized

cDNA

μl

of

SYBR

Green

Mix

-LRB-

ABI

Foster

City

CA

-RRB-

and

μM

of

each

primer

in

a

reaction

Reactions

were

carried

out

using

the

following

cycling

parameters

°C

for

min

°C

for

min

and

cycles

of

°C

for

s

and

°C

for

min

At

the

end

of

each

run

a

melt

curve

analysis

was

conducted

to

ensure

primer

specificity

and

purity

of

the

PCR

product

Relative

mRNA

levels

were

calculated

by

the

standard

curve

method

-LRB-

User

Bulletin

ABI

PRISM

Sequence

Detection

System

-RRB-

as

described

here

An

aliquot

was

taken

from

each

cDNA

to

construct

a

pooled

sample

This

pooled

sample

was

serially

diluted

and

subjected

to

qRT-PCR

The

threshold

cycle

-LRB-

Ct

-RRB-

for

each

dilution

was

plotted

against

its

cDNA

concentration

-LRB-

with

an

arbitrary

starting

quantity

for

the

undiluted

pooled

sample

assigned

the

value

of

-RRB-

and

used

as

the

standard

curve

regression

equation

to

generate

the

arbitrary

expression

values

-LRB-

AEVs

-RRB-

A

standard

curve

was

generated

for

each

target

gene

on

the

same

PCR

plate

that

held

the

experimental

samples

Linear

standard

curves

with

a

slope

between

and

and

value

of

at

least

were

required

for

all

primers

used

in

this

study

The

AEVs

were

then

normalized

to

the

expression

values

of

the

eukaryotic

initiation

factor

for

each

bee

Two

technical

replicates

for

each

bee

were

used

and

results

averaged

before

obtaining

the

family

average

Normalized

average

AEVs

for

each

bee

were

analyzed

by

two-factor

analysis

of

variance

-LRB-

ANOVA

-RRB-

without

replication

to

compare

transcript

levels

of

the

high-defensive

family

to

the

low-defensive

family

Results

and

discussion

Bioinformatic

analyses

of

putative

gene

functions

and

results

of

qRT-PCR

allowed

us

to

form

hypotheses

concerning

gene

networks

involved

in

either

foraging

or

defensive

behaviors

Results

of

analyses

and

hypotheses

concerning

genes

with

potential

to

influence

behavior

are

presented

in

the

following

two

sections

Candidate

genes

for

honeybee

foraging

behavior

Inspection

of

the

predicted

peptides

-LRB-

HGSC

-RRB-

in

genome

sequence

surrounding

the

mapped

QTLs

lends

support

to

the

hypothesis

of

the

involvement

of

the

IIS

pathway

in

pollen

foraging

-LRB-

Table

Fig.

-RRB-

Within

the

CI

is

the

bee

ortholog

of

the

Drosophila

gene

bazooka

a

gene

involved

in

oocyte

fate

determination

and

influencing

IIS

through

modulation

of

activity

as

discussed

below

Closer

to

the

center

of

the

CI

is

the

honeybee

ortholog

of

the

fly

gene

midway

which

is

involved

in

lipid

metabolism

and

oocyte

development

This

gene

is

particularly

interesting

because

it

encodes

diacylglycerol

acyltransferase

-LRB-

DGAT

-RRB-

and

changes

in

DGAT

activity

have

been

shown

to

alter

sensitivity

to

IIS

-LRB-

Yu

and

Ginsberg

-RRB-

Near

the

center

of

the

CI

of

is

a

gene

encoding

a

protein

with

homology

to

class

W

phosphoinositolglycan-peptide

-LRB-

PIG-P

-RRB-

involved

in

the

production

of

glycosylphosphatidylinositol

-LRB-

GPI

-RRB-

anchors

to

attach

receptors

to

plasma

membrane

in

various

species

Lipids/GPI

anchors

have

insulin

mimetic

properties

in

some

systems

where

they

modulate

the

IIS

pathway

by

stimulating

-LRB-

-RRB-

activity

-LRB-

Müller

and

Frick

Müller

et

al.

-RRB-

Table

of

peptides

within

confidence

intervals

for

foraging-behavior

QTLsFig

regulatory

network

influencing

honeybee

pollen

foraging

behavior

modulated

by

insulin-like

signaling

and

its

effects

on

ovarian

development

Inhibitory

blue

arrows

bridging

IIS

with

the

reproductive

physiology

and

hormonal

dynamics

of

the

honeybee

denote

the

unique

and

mutually

suppressive

feedback

interaction

between

vitellogenin

and

JII

This

interaction

is

mediated

via

the

allatoregulatory

system

-LRB-

Guidugli

et

al.

and

references

therein

-RRB-

which

includes

the

IIS

pathway

-LRB-

Flatt

et

al.

-RRB-

ILPs

Insulin-like

peptides

PI

phosphoinositol

PIP

phosphoinositol

phosphate

IRS

insulin

receptor

substrate

gene

kinase

-LRB-

class

I

or

II

-RRB-

PIG-P

phosphatidylinositolglycan-peptide

kinase

PKB

protein

kinase

B

honeybee

ortholog

of

PTEN

phosphatidylinositol-3,4,5-trisphosphate

JH

juvenile

hormone

The

region

contains

two

LOD-score

peaks

that

were

resolved

into

two

CIs

suggesting

separate

but

linked

QTLs

-LRB-

Fig.

-RRB-

The

CI

with

the

higher

LOD

score

contains

a

bee

ortholog

of

a

nuclear

hormone

receptor

-LRB-

-RRB-

Nuclear

hormone

receptors

bind

ligands

-LRB-

such

as

ecdysteroids

-RRB-

and

enter

the

nucleus

as

transcription

factors

-LRB-

Simonet

et

al.

-RRB-

The

bee

ortholog

of

was

differentially

regulated

in

microarray

experiments

that

compared

bees

with

and

without

application

of

queen

mandibular

pheromone

treatment

which

inhibits

worker

ovarian

development

and

delays

onset

of

foraging

behavior

-LRB-

Grozinger

et

al.

-RRB-

The

region

also

contains

the

tyramine

receptor

which

has

a

higher

expression

level

in

young

bees

selected

for

high

levels

of

pollen

collection

and

storage

-LRB-

M.

H.

Humphries

unpublished

data

-RRB-

A

Drosophila

mutant

for

the

tyramine

receptor

-LRB-

hono

-RRB-

is

deficient

in

its

behavioral

response

to

olfactory

stimuli

an

observation

that

is

relevant

because

honeybee

foragers

respond

to

floral

scents

and

brood

pheromone

In

addition

tyramine

increases

responsiveness

to

sucrose

and

is

found

at

elevated

levels

in

the

brains

of

egg-laying

worker

bees

a

pattern

that

fits

the

behavioral

and

reproductive

state

of

pollen

foragers

-LRB-

Scheiner

et

al.

-RRB-

The

second

CI

associated

with

contains

an

ortholog

of

Dmel/skittles

encoding

-LRB-

-RRB-

one

of

two

phospholipid

kinases

known

to

produce

phosphoinositol

phosphate

-LRB-

-RRB-

which

is

a

key

metabolite

involved

in

IIS

and

the

substrate

of

class

I

activity

-LRB-

Fig.

Carricaburu

et

al.

-RRB-

The

Drosophila

skittles

mutant

is

deficient

in

oocyte

polarity

and

nurse

cell

development

and

the

gene

is

essential

for

germ

line

development

-LRB-

Hassan

et

al.

Table

-RRB-

At

the

most

likely

position

for

is

the

honeybee

ortholog

of

the

fly

gene

for

a

class

II

-LRB-

-RRB-

Class

II

have

been

shown

to

respond

to

insulin

signals

in

mammals

and

use

phosphoinositol

to

produce

phosphoinositol

phosphate

which

influences

glucose

transport

a

common

effect

of

IIS

-LRB-

MacDougall

et

al.

Shepherd

-RRB-

In

addition

three

predicted

peptides

with

glucose

transport

domains

were

found

in

the

CI

It

is

unknown

whether

class

II

can

act

directly

on

to

produce

thereby

stimulating

the

primary

downstream

kinase

in

the

IIS

pathway

kinase

-LRB-

-RRB-

However

the

honeybee

gene

encoding

also

lies

within

the

CI

is

a

positive

regulator

of

cell

growth

and

size

through

its

action

on

downstream

protein

kinase

B

-LRB-

PKB

Fig.

Rintelen

et

al.

-RRB-

which

in

Drosophila

is

required

for

egg

chamber

development

and

influences

egg

follicle

cell

size

-LRB-

Cavaleire

et

al.

-RRB-

The

presence

of

these

genes

at

pln

QTLs

suggests

a

possible

network

of

genes

influencing

ovarian

development

and

foraging

-LRB-

Fig.

-RRB-

Linkage

of

a

and

at

is

intriguing

especially

given

the

presence

of

PIG-P

and

the

bazooka

ortholog

at

and

the

ortholog

near

PIG-P

has

the

potential

to

activate

and

thus

whereas

bazooka

has

been

shown

to

bind

the

protein

tyrosine

phosphatase

PTEN

This

phosphatase

is

a

negative

regulator

of

because

it

dephosphorylates

and

binding

of

dPTEN

by

the

product

of

the

bazooka

modulates

this

process

-LRB-

Von

Stein

et

al.

-RRB-

The

convergence

of

these

pathways

also

suggests

the

potential

for

interaction

between

and

both

the

and

regions

which

has

been

observed

experimentally

-LRB-

Rueppell

et

al.

-RRB-

A

search

of

the

cM

window

surrounding

AmFOR

-LRB-

-RRB-

revealed

only

three

predicted

peptides

one

of

which

was

the

insulin

receptor

substrate

-LRB-

IRS

-RRB-

Although

AmFOR

was

chosen

as

a

candidate

because

of

its

influence

on

foraging

behavior

in

Drosophila

and

association

with

foraging-related

behavioral

states

in

bees

-LRB-

Ben-Shahar

-RRB-

the

IRS

could

be

partly

or

wholly

responsible

for

the

behavioral

effects

of

this

QTL

In

Drosophila

ovarian

expression

of

this

gene

is

necessary

for

vitellogenesis

independent

of

the

action

of

juvenile

hormone

and

ecdysteroids

-LRB-

Richard

et

al.

-RRB-

When

the

phenotypic

architecture

of

foraging

behavior

is

taken

into

consideration

-LRB-

Fig.

-RRB-

the

identification

of

genes

encoding

class

II

and

at

and

other

key

components

of

IIS

at

and

supports

the

hypothesis

that

IIS

is

the

upstream

mediator

of

foraging

division

of

labor

-LRB-

Fig.

-RRB-

These

IIS

components

do

not

constitute

random

distributions

of

genes

We

obtained

a

rough

estimate

of

the

likelihood

that

a

gene

lies

within

the

CIs

for

foraging

behavior

QTLs

by

comparing

the

genetic

size

of

these

four

QTL

regions

relative

to

the

genome

-LRB-

about

cM

or

-RRB-

There

are

Drosophila

genes

in

Flybase

with

the

GO

term

for

insulin

receptor

signaling

pathway

-LRB-

GO

-RRB-

so

the

expected

number

of

these

genes

within

the

CIs

is

However

bee

orthologs

for

two

of

these

genes

occur

within

foraging

behavior

QTL

CIs

at

least

times

the

expected

number

assuming

independence

of

gene

distributions

In

addition

orthologs

of

four

of

these

genes

were

not

in

genome

sequence

assigned

to

chromosomes

and

so

could

not

be

sampled

in

our

analyses

We

also

found

at

least

four

other

genes

known

to

interact

with

IIS

but

not

annotated

as

such

with

GO

terms

and

one

nuclear

hormone

receptor

within

the

QTL

regions

which

are

characterized

by

epistatic

interactions

suggesting

the

presence

of

components

of

a

common

pathway

In

contrast

we

could

not

find

any

genes

influencing

IIS

within

CIs

for

QTLs

that

influence

defensive

behavior

although

they

represent

a

region

of

comparable

size

Candidate

genes

for

defensive

behavior

had

the

highest

LOD

score

for

colony

stinging

response

and

was

also

the

only

QTL

associated

with

initiation

of

stinging

at

the

individual-bee

level

-LRB-

Guzmán-Novoa

et

al.

Arechavaleta-Velasco

et

al.

Fig.

-RRB-

Among

the

predicted

peptides

in

this

region

at

least

nine

are

orthologs

or

homologs

of

genes

reportedly

involved

in

neuronal

development

and

CNS

activity

-LRB-

Table

-RRB-

The

interval

includes

the

gene

encoding

epsilon

a

protein

abundantly

expressed

in

the

CNS

that

modulates

the

activity

of

a

number

of

kinases

and

ion

channels

-LRB-

Berg

et

al.

-RRB-

A

Drosophila

mutant

for

the

ortholog

-LRB-

-RRB-

shows

a

failure

to

habituate

to

stimuli

during

nonassociative

-LRB-

unrewarded

-RRB-

learning

trials

-LRB-

Skoulakis

and

Acevedo

-RRB-

which

is

the

type

of

learning

that

guard

bees

engage

in

when

distinguishing

nestmates

from

non-nestmates

The

CI

contains

six

orthologs

of

Drosophila

genes

involved

in

CNS

or

antennal

development

Of

particular

interest

is

the

ortholog

of

the

Dmel/tango

gene

which

is

an

aryl

hydrocarbon

receptor

nuclear

transporter

-LRB-

ARNT

-RRB-

like

transcription

factor

Tango

is

a

basic

helix-loop-helix-PER-ARNT-SIM

-LRB-

bHLH-PAS

-RRB-

transcription

factor

that

responds

to

hypoxia

and

is

critical

for

the

development

of

the

fly

neural

midline

and

antennae

Other

bHLH-PAS

transcription

factors

act

as

heterodimers

to

sense

light

temperature

oxygen

or

endogenous

hormones

and

some

have

roles

in

regulating

circadian

rhythm

-LRB-

Roenneberg

and

Merrow

-RRB-

The

honeybee

ortholog

shares

just

amino

acid

identity

with

tango

and

is

diverged

in

the

region

important

for

activation

of

target

genes

making

it

impossible

to

infer

function

-LRB-

Sonnenfeld

et

al.

-RRB-

The

region

also

contains

the

gene

for

Huntingtin

protein

-LRB-

htt

-RRB-

a

large

and

unique

protein

with

a

complex

structure

that

is

conserved

among

metazoans

Expansions

in

htt

cause

Huntington

's

chorea

Htt

interacts

with

many

proteins

and

has

roles

in

modulating

neuronal

transcription

intracellular

neuronal

transport

synaptic

transmission

and

morphology

of

dendrites

-LRB-

Harjes

and

Wanker

Li

and

Li

-RRB-

Finally

mRNA

for

a

carboxylesterase

of

unknown

function

was

more

abundant

in

high-defensive

bees

compared

to

low-defensive

bees

-LRB-

see

Table

-RRB-

and

RACE

sequences

from

seven

workers

revealed

six

amino

acid

substitutions

and

five

alleles

Allelic

variation

for

this

gene

was

found

in

the

population

used

to

map

which

is

a

necessary

condition

for

a

gene

conferring

variability

in

the

behavior

Fig.

QTLs

were

mapped

based

on

the

stinging

response

of

colonies

derived

from

crosses

involving

haploid

drones

of

a

queen

-LRB-

European

African

-RRB-

each

backcrossed

to

a

European

queen

Markers

used

for

confirmation

studies

are

indicated

Letters

and

numbers

next

to

vertical

bar

represent

linked

markers

Sequenced

markers

are

underlined

Dashed

lines

indicate

approximate

CIs

Approximate

positions

of

honeybee

orthologs

to

Drosophila

genes

are

indicated

a

b

c

of

peptides

within

confidence

intervals

for

defensive-behavior

QTLsTable

of

candidate

genes

in

high-defensive

bees

relative

to

low-defensive

worker

bees

The

primary

stimuli

that

elicit

stinging

behavior

are

moving

visual

targets

and

alarm

pheromone

The

region

contains

two

obvious

candidates

for

modulation

of

response

to

these

stimuli

At

the

most-likely

position

of

the

QTL

is

the

bee

ortholog

of

Drosophila

-LRB-

Fig.

-RRB-

an

arrestin

that

binds

metarhodopsin

the

light-activated

form

of

rhodopsin

in

the

eye

Arrestins

are

involved

in

the

desensitization

of

specific

GPCRs

and

their

recycling

through

clathrin-mediated

endocytosis

But

the

so-called

visual

arrestins

are

also

expressed

in

the

antennae

of

Drosophila

and

are

involved

in

olfaction

Fly

mutants

are

insensitive

to

classes

I

and

II

odorants

-LRB-

Merrill

et

al.

-RRB-

Near

the

edge

of

the

CI

is

an

ortholog

of

the

fly

gene

encoding

the

metabotropic

gamma-aminobutyric

acid

receptor

-LRB-

-RRB-

GABA

serves

as

the

primary

inhibitor

of

neuronal

excitability

in

the

CNS

of

both

insects

and

mammals

-LRB-

Bettler

et

al.

-RRB-

The

CI

contains

only

predicted

peptides

in

Mb

of

DNA

Like

it

has

genes

with

the

potential

to

modulate

sensitivity

to

visual

and

olfactory

stimuli

Results

of

cDNA

sequencing

of

a

putative

GPCR

revealed

a

serotonin

receptor

-LRB-

Fig.

-RRB-

Serotonin

influences

associative

learning

and

circadian

rhythm

in

mollusks

and

insects

and

both

serotonin

and

GABA

influence

mood

disorders

in

mammals

-LRB-

Hayley

et

al.

-RRB-

Application

of

serotonin

to

the

optic

lobe

of

the

bee

brain

reduced

behavioral

and

neural

responses

to

moving

visual

stimuli

-LRB-

Erber

and

Kloppenburg

-RRB-

However

pharmacological

experiments

likely

target

all

types

of

serotonergic

neurons

The

receptor

is

just

one

of

four

serotonin

receptor

types

known

in

insects

and

is

unique

in

that

it

activates

adenylate

cyclase

resulting

in

increased

levels

of

cyclic

adenosine

monophosphate

-LRB-

AMP

-RRB-

and

activation

of

PKA

Therefore

activation

of

receptors

would

likely

cause

a

stimulatory

response

Total

serotonin

levels

have

sometimes

been

reported

to

influence

mammalian

insect

and

crustacean

aggressive

interactions

-LRB-

Nelson

and

Chiavegatto

Panksepp

et

al.

-RRB-

Recent

evidence

suggests

that

receptors

modulate

exploratory

behavior

and

anxiety

in

mice

-LRB-

Takeda

et

al.

-RRB-

The

region

also

contains

one

of

the

three

catalytic

subunits

of

cyclic

AMP-dependent

PKA

a

gene

known

to

affect

behavior

in

flies

and

mammals

including

behavioral

responses

to

alcohol

learning

and

locomotor

rhythm

-LRB-

Eisenhardt

et

al.

-RRB-

Finally

the

ortholog

of

homer

a

dendritic

gene

involved

in

calcium

signaling

and

synaptic

plasticity

is

closely

linked

to

-LRB-

Diagana

et

al.

Szumlinski

et

al.

-RRB-

Measurement

of

gene

expression

by

qRT-PCR

for

defensive-behavior

candidate

genes

showed

several

interesting

trends

There

were

few

statistically

significant

differences

because

in

this

first

screen

families

were

chosen

that

had

divergent

behavior

but

were

genotypically

diverse

Variation

in

expression

between

individuals

was

high

but

numerical

differences

indicated

a

trend

towards

higher

gene

expression

in

older

defensive

bees

Only

Epsilon

showed

significantly

higher

transcript

levels

in

the

defensive

family

of

bees

In

contrast

the

ortholog

a

putative

jumonji-domain

transcription

factor

had

numerically

higher

levels

in

newly

emerged

defensive

adults

yet

significantly

lower

levels

in

older

defensive

bees

-LRB-

Table

-RRB-

This

suggests

an

earlier

peak

in

expression

of

this

transcription

factor

in

defensive

bees

It

was

interesting

that

the

mRNA

levels

of

the

receptor

part

of

the

major

inhibitory

pathway

of

neural

signaling

were

significantly

lower

in

newly

emerged

defensive

bees

Transcript

levels

of

seven

other

genes

showed

trends

for

higher

expression

in

defensive

bees

at

the

level

At

an

unknown

carboxylesterase

showed

the

greatest

numerical

expression

difference

of

all

but

its

levels

also

showed

the

highest

interindividual

variability

resulting

in

no

significant

difference

between

families

As

previously

stated

this

gene

also

showed

the

highest

allelic

variability

in

cDNA

sequence

At

both

the

ortholog

of

Dmel/discs

lost

and

-LRB-

arrestin

-RRB-

trended

towards

higher

expression

in

defensive

bees

Three

other

genes

showed

high

numerical

but

not

significantly

different

levels

in

defensive

bees

oxysterol

binding

protein

the

Dmel/tango

ortholog

and

the

serotonin

receptor

-LRB-

higher

-RRB-

Eight

of

the

genes

tested

appear

to

be

more

highly

expressed

in

older

defensive

bees

at

or

higher

although

only

one

is

significantly

so

The

fact

that

so

many

of

these

linked

genes

trended

towards

higher

mRNA

levels

in

defensive

bees

may

mean

that

they

are

regionally

regulated

More

sampling

of

other

bees

and

genomic

regions

is

necessary

Some

genes

may

be

expressed

at

higher

levels

in

high-defensive

bees

because

of

elevated

metabolic

rates

-LRB-

Harrison

et

al.

-RRB-

Presumably

genes

that

influence

behavior

will

show

differences

in

expression

levels

of

protein

at

some

stage

between

low

and

high-defensive

alleles

However

demonstration

of

differences

in

transcript

levels

does

not

prove

a

causal

connection

to

the

phenotype

Conversely

failure

to

find

a

difference

in

transcript

level

does

not

disprove

a

causal

connection

to

behavior

and

could

be

a

consequence

of

not

sampling

the

most

relevant

developmental

stage

or

that

small

differences

in

expression

are

still

relevant

to

the

phenotype

The

advantage

of

high

recombination

rates

By

use

of

genome

sequence

and

linkage

maps

we

reduced

the

list

of

candidate

genes

for

honeybee

foraging

and

defensive

behavior

from

-LRB-

the

current

number

of

predicted

peptides

-RRB-

to

just

to

per

QTL

As

a

consequence

of

high

recombination

rates

this

level

of

resolution

within

CIs

was

achieved

in

relatively

large

genetic

distances

averaging

cM

per

CI

Table

shows

a

comparison

of

our

results

to

a

study

in

which

QTLs

for

ovariole

number

were

mapped

in

Drosophila

Because

of

the

low

recombination

rate

in

Drosophila

CIs

totaling

cM

represented

half

the

genome

in

this

cross

and

contained

genes

-LRB-

Orgogozo

et

al.

-RRB-

But

regions

of

similar

size

influencing

foraging

and

defensive

specialization

in

the

bee

contained

only

and

genes

respectively

Other

model

organisms

would

provide

less

drastic

comparisons

For

example

a

window

in

mouse

would

be

expected

to

contain

about

ten

times

as

many

genes

compared

to

the

bee

or

about

genes

-LRB-

assuming

a

total

of

genes

evenly

distributed

over

Mb

and

a

recombination

rate

of

cm/Mb

-RRB-

Of

course

results

will

depend

on

local

gene

distributions

and

recombination

rates

In

practice

it

is

usually

necessary

to

map

a

QTL

to

within

cM

in

mammalian

species

to

reduce

the

list

to

five

to

ten

candidate

genes

-LRB-

e.g.

Talbot

et

al.

Flint

et

al.

-RRB-

The

genetic

size

of

our

QTL

intervals

compared

to

the

size

of

the

bee

linkage

map

suggests

that

we

should

find

and

genes

for

the

pln

QTL

and

sting

QTL

respectively

but

instead

we

found

less

than

half

this

number

-LRB-

Table

-RRB-

The

expected

number

of

genes

based

on

physical

distance

is

closer

to

the

observed

value

The

discrepancy

between

these

predictions

can

be

explained

by

higher

than

average

recombination

rates

in

the

QTL

regions

The

average

recombination

rates

for

the

pln

and

sting

QTL

intervals

are

and

cM/Mb

respectively

but

the

genome

average

is

cM/Mb

Consequently

there

is

a

little

less

than

one

gene

per

centimorgan

in

the

QTL

regions

Our

analyses

do

involve

some

degree

of

uncertainty

First

of

all

the

estimate

of

recombination

rate

in

QTL

regions

does

not

take

into

account

sequence

groups

that

have

not

yet

been

assigned

to

chromosomes

-LRB-

of

the

genome

HGSC

-RRB-

that

may

lie

between

assigned

groups

Therefore

recombination

rates

actually

may

be

somewhat

higher

in

QTL

regions

than

we

estimated

Sequence

groups

missing

within

CIs

also

may

contain

additional

genes

In

addition

the

annotated

set

of

genes

is

a

high-confidence

set

and

eventually

may

increase

by

several

thousands

as

genes

that

are

more

novel

in

sequence

are

added

-LRB-

e.g.

Drosophila

has

a

gene

count

of

about

-RRB-

Finally

our

analyses

focus

on

conserved

genes

of

known

function

A

previous

study

of

Kb

of

sequence

linked

to

revealed

expressed

transcripts

of

which

showed

homology

to

known

genes

-LRB-

Lobo

et

al.

-RRB-

It

can

not

be

ruled

out

that

these

behaviors

may

be

at

least

partly

influenced

by

completely

novel

genes

Table

of

number

of

candidate

genes

in

QTL

confidence

intervals

from

Apis

and

DrosophilaaInterval

Size

-LRB-

cM

-RRB-

bGenusTraitNumber

of

QTLPredicted

no

of

genes

based

on

genetic

or

physical

sizecActual

no

of

aData

for

Drosophila

are

derived

from

a

study

of

QTL

for

ovariole

number

in

an

interspecific

cross

between

D.

simulans

and

D.

sechellia

-LRB-

Orgogozo

et

al.

-RRB-

Data

for

Apis

are

from

this

report.bCumulative

size

of

all

confidence

intervals.cCalculation

of

number

of

genes

expected

based

on

genetic

distance

was

done

by

multiplying

the

proportion

of

total

genetic

distance

that

an

interval

contains

by

the

number

of

predicted

genes

An

estimate

based

on

physical

distance

in

the

honeybee

is

based

on

the

current

amount

of

genome

sequence

assembly

-LRB-

Mb

-RRB-

Conclusions

Our

findings

lead

us

to

propose

that

foraging

division

of

labor

-LRB-

Fig.

-RRB-

is

influenced

by

a

gene

network

involving

IIS

-LRB-

Fig.

-RRB-

This

is

just

a

hypothesis

but

a

testable

one

We

also

suggest

that

the

genetically

variable

defensive

responses

of

bees

may

be

explained

by

allelic

differences

in

neuronal

transcription

factors

and

genes

involved

in

G

protein-coupled

signaling

pathways

The

potential

involvement

of

the

serotonin

receptor

in

defensive/aggressive

behavior

implies

that

the

bee

may

be

used

to

elucidate

a

role

of

serotonin

in

novelty-seeking

-LRB-

guarding

-RRB-

behavior

and

that

this

behavior

could

be

modified

by

specific

agonists

and

antagonists

of

this

receptor

subtype

Linkage

mapping

at

a

finer

scale

using

many

single

nucleotide

polymorphisms

combined

with

genome-wide

expression

assays

could

be

the

next

step

in

finding

the

sequences

responsible

for

behavioral

variation

The

bee

is

likely

to

become

an

important

species

in

this

process

and

may

become

the

first

invertebrate

model

for

understanding

how

gene-regulation

of

life

histories

are

remodeled

by

social

evolution

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

recombination rate
foraging behavior
candidate genes

apis mellifera
insulin-like signaling
aggressive behavior
behavior genetics