SPAGeDi a program for Spatial Pattern Analysis of Genetic Diversityby Olivier J. Hardy and Xavier Vekemans

SPAGeDi a program for Spatial Pattern Analysis of Genetic Diversityby Olivier J. Hardy and Xavier Vekemans

Goal: characterise spatial genetic structure of mapped individuals or populations using genotype data of any ploidy level

Compute: - inbreeding coef - pairwise relatedness/differentiation coef between indiv/pop averages / distance classes association with distance (regression with lin/log distance) ( isolation by distance, neighbourhood size estimates)

- actual variance of relatedness coef Ritland’s approach for marker based estimate of h2

Tests: - permutations (of genes, individuals, or spatial locations) - jackknife over loci ( SE for multilocus estimates)

Option: - restricted analysis within or among categories of ind/pop

http://www.ulb.ac.be/sciences/lagev/

Input data Input data

Input file with :- format #’s (#ind, #categ, #spat coord, #loci, #digits/allele, ploidy)- distance intervals- for each ind :

- name- category (facultative) - spatial coordinates- genotype at each locus

Analyses defined on keyboard while running the program :- indiv vs pop level- stat to compute (+ within/among categ)- tests, …

2-genes coef :- "kinship" coef (Loiselle 1995; Ritland 1996)

- "relationship" coef (Moran’s I; Lynch & Ritland 1999; Wang 2002)

- kinship type coef based on allele size (Streiff et al. 1999)

- ar distance measure (Rousset 2000)

4-genes coef :- "fraternity" coef

(Lynch & Ritland 1999; Wang 2002)

Statistics computed: "relatedness" coef at the individual level Statistics computed: "relatedness" coef at the individual level

also for dominant marker(Hardy 2003)

Centaurea corymbosa87 individuals

9 SSR loci (2-11 alleles)

-0.005

-0.004

-0.003

-0.002

-0.001

0

0.001

0.002

0.003

0.004

0.005

10 (251) 20 (255) 30 (340) 40 (414) 50 (415) 100 (1078) 250 (988)

max dist in meters (# pairs)

Var

(kin

ship

coe

f) +

/- S

EEstimates of the actual variance of pairwise kinship coef

in natural populationsEstimates of the actual variance of pairwise kinship coef

in natural populations

Chamaecrista fasciculata1365 individuals6 enzymatic loci

-0.006

-0.004

-0.002

0

0.002

0.004

0.006

0.008

0.01

0.012

2 (13626) 4 (19825) 8 (14714) 20 (1166) 75 (39748)

max dist in meters (# pairs)

Var(

kins

hip

coef

) +/-

SE

Quercus petreae43 individuals149 AFLP loci

-0.002

0

0.002

0.004

0.006

0.008

0.01

50 (146) 100 (279) 200 (404) 305 (74)

max dist (#pairs)

Var(k

insh

ip c

oef)

+/- S

E

Quercus petreae165 individuals

6 SSR loci (15-27 alleles)

-0.0006

-0.0004

-0.0002

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

50 (2299) 100 (3980) 200 (6264) 305 (987)

max dist in meters (# pairs)

Var(

kins

hip

coef

) +/-

SE

Quercus petreae165 individuals

6 SSR loci (15-27 alleles)Estimates over 2299 pairs (<50 m)

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

0.0014

Loiselle etal., 1995

Ritland, 1996 Moran's I Queller &Goodnight,

1989

Lynch &Ritland, 1999

Wang, 2002

Var(k

insh

ip c

oef)

+/- S

EConsistency among kinship coef estimators Consistency among kinship coef estimators

Reliable estimates of the actual variance of pairwise relatednessrequire

- large data set (300 – 1000 individuals)

- very polymorphic markers and/or many loci

SSR

AFLP ???