U G & UNEP/GRID-E

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N
ICOLAS

R
AY




U
NIVERSITY

OF

G
ENEVA

& UNEP/GRID
-
E
UROPE


Swiss

Grid

Day, Bern,
November

26
th

2009

Human migrations

Adapted from
Cavalli
-
Sforza & Feldman, 2003

[
12,000
]

[55,000]

Homo sapiens
sapiens

1. Better
understand human evolution


Origin of modern human (when,
where, how many?)


Relationship with other members of the
Homo

genus




2. Distinguish
between the effect of demography and those
of
selection (biomedical applications)

Why aiming at a good demographic model

Gene
-
specific factors

mutations

recombination

selection

A complex past demography

fluctuation in effective pop. size

substructure

migrations

Observed patterns of genetic

diversity in contemporary populations

A complex demography

Adapted from Cavalli
-
Sforza & Feldman, 2003

[10,000]

[
55,000]

demographic and

spatial expansions

population bottlenecks

fast migration events

population isolation

secondary contacts

SPLATCHE

SP
atia
L

A
nd
T
emporal
C
oalescences in
H
eterogeneous
E
nvironment

(http://cmpg.unibe.ch/software/splatche)

From environment to demography

Spatial
resolution
: 100 km

low

high

Carrying

capacity

low

high

Friction

From environment to demography

Demographic

simulations

stepping
-
stone
model
(cellular
automata
)

Cell

or
deme

Pop. size

time

Demography

and spatial expansion

Population
density

Genetic

simulations

Simulated genealogy

Mutation

Modèle de mutation

ACCTAGTACAATCGGTAATGCCATTGGT

T
CCT
T
GTA…ATTGGT

ACC
G
AGTA…
G
TTGGT

Summary statistics


Within population:


S
,
p


Between populations


Pairwise

F
ST


Global

F
ST


Globally



S,
p

Draw
parameter
values
from priors

Simulate
one
genealogy

Generate
genetic
data

Compute
summary
statistics

1
-
10
mio
.

Computer clusters

UBELIX (>500
nodes
)

Zooblythii

(~40
nodes
)

A
PPROXIMATE

B
AYESIAN

C
OMPUTATIONS

(ABC)
C
OMPUTATIONAL

ISSUES

Computational

issues


A fully spatially
-
explicit model using 500 loci in 800
individuals:





10 CPU
-
years



Adding long
-
distance dispersal:





20 CPU
-
years

SPLATCHE on the grid


early 2005: joined the Biomed VO of the EGEE
project



mid
2005: tested on GILDA test bed, and deployed
on the Grid



since mid 2006: production mode and optimization

Use of SPLATCHE on the grid

N simulations

Independent simulations:

-

the more CPUs, the better

-

job failures are not that bad

GRID


Posterior distribution of
demographic/genetic
parameters of interest

Statistical tools

Optimizations

5 mio.
simulations


GRID

Reduction of the number of simulations (Daniel
Wegmann
)

By MCMC. Promising
results (~50
times less
sims
)

Submission time

multi
-
threaded application using up to 30 RBs
(used for the WISDOM project)

Fetching time of job outputs

in
-
house multi
-
threaded solution for
checking status and getting outputs

Geographic origin of human dispersal

Ray
et
al.
(2005
)
Genome

Research

Interactions among populations



Interaction between modern humans
and Neanderthals in Europe

Currat & Excoffier

(2004),
PLoS Biol.

Plausible introducti on si te 1
LAGOON CREEK (first sight: 1979)
Initial introduction site in Australia
GORDONVALE (1935)
K
D
M
N
W
B
T
R
E
120
0
120
240
360
Kilometers
1999
1982
1988
1992
1995
1996
1997
1998
Plausible introducti on si te 2
NORMANTON (first sight: 1964)
Cane toad invasion in Australia

Estoup
, A., Baird, S. J. E., Ray, N.,
Currat
, M.,
Cornuet
, J.
-
M., Santos, F., Beaumont, M. A. and L.
Excoffier
. Combining genetic, historical and geographic data to reconstruct the dynamics of
the
bioinvasion

of cane toad
Bufo

marinus
.
Submitted

Take
-
home message

A good human demographic model is
important

Realistic spatially
-
explicit approaches
are essential

The grid is key for sufficient
exploration of parameter space

User support and connections
outside one’s discipline is crucial