Hoa Nguyen-Phuc - PhD Defense - 2015-08-03 Final Version

Hoa Nguyen-‐Phuc

August 3, 2015

Spatial genetic characterizations of neutral and adaptive variation

of Red Junglefowl (Gallus gallus) in South Central Vietnam

Introduction

Part I Neutral genetic variation

Part II Genetic structure dependence to landscape patterns

Part III Adaptive genetic variation

PhD-‐wide conclusions

Outline

(1) Turkey, (2) Guinea pig, Llama, (3) Pig, Rabbit, (4) Cattle, Donkey, (5) Cattle, Pig, (6) Cattle, Chicken, (7) Horse, (8) Yak, (9) Pig. Swamp Buffalo, Chicken,

(10) Pig, Chicken, (11) Dromedary, (12) Reindeer.

FAO 2007

Introduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ionsL ive stock Domestication History Evo l ution and D istribution of Gallus Spat ial Ecology Study Design

40-‐plus livestock species.

10 domestication centers.

Only 2 wild progenitor species still exist…

CENTERS OF

ORIGINS -‐

LIVESTOCK

DOMESTICATION


Poultry industry is a multi-‐billion business.

40 billion chickens produced worldwide annually.


‘Selection wall’ of growth and

reproductive traits.

Susceptibility to zoonotic diseases.


Indigenous or heritage breeds for maintaining poultry genetic diversity

“Đông Tảo” heritage breed in Vietnam -‐ $US 1,000 for this ‘broiler’!

Green

South Central Vietnam

Rubin et al 2010

Red

Grey

Ceylon

Green

Introduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ionsL i vestock Domestication History Evolution and Distribution of Gallus Spat ial Ecology Study Design

Introduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

F2 Hybrid

Red Junglefowl

“Bamboo” Breed

L i vestock Domestication History Evolution and Distribution of Gallus Spat ial Ecology Study Design

Storey et al 2010

①Very broad extent: a common avian species ② Regional extent: terrestrial birds limited by landscape features?

L i vestock Domestication History Evo l ution and D istribution of Gallus Spat ial Ecology Study DesignIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

③ Local extent: an ‘island’ model

④ Ecology & demography extent: niche and a polygynous breeding

Human density 190/km2

Gallus gallus spadiceus

Gallus gallus gallus

1960s

1920s

Before 1880

Eclipse ‘clean genotype’ plumages (Peterson & Brisbin 1998)

Sub species

L i vestock Domestication History Evo l ution and D istribution of Gallus Spat ial Ecology Study DesignIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

Research Goal:

To investigate the spatial processes of neutral and adaptive genetic variation in wild Red

Junglefowl and the interactions with the underlying environment.

Research Questions:

① What are major processes influencing the (broad & fine-‐scale) spatial neutral

variation?

② Are landscape features deciding factors for (fine-‐scale) genetic variation?

③ Are the functionally adaptive genes more diverse than the neutral genes? Are there

higher diversity in wild Red Junglefowl than in domestic chickens?

• 7 field sites (~ 50,000ha). • East vs West sites of the AnnamiteMountain Range.•Major sites: CTN, HBA, LGO, YDN (>30 samples).• Lowland vs Highland sites.

Introduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ionsL i vestock Domestication History Evo l ution and D istribution of Gallus Spat ial Ecology Study Design

Highland -‐ HBAHighland -‐ YDD

Lowland -‐ CTNLowland -‐ LGO

14

Elephants in CTN and YDN

Walking snare: Very low capture efficiency (~ 0.25 bird/day).

Efforts to maintain the snare lines. Captured more*

Partridges, Peafowls, and Pheasants.

Decoy ‘baiting’ rooster: Effective & flexible method (~ 1.8

bird/day). Capture more territorial males.

Sample size: 212 birds -‐ 172 roosters, 23 hens, 17 chicks -‐

(and > 100 Phasianid birds) of blood and swap samples.

Introduction Neutral Variation Spatial Dependence Adaptive Variation Conclus ions

Research Question:What are major processes influencing the

(broad & fine-‐scale) spatial neutral variation of Red Junglefowl?

Hypothesis: The ground-‐dwelling Red Junglefowl have

substantial inter-‐population variation due to (broad-‐scale)

habitat fragmentation and (fine-‐scale) movement.

Central Highland coffee just in Starbuck’s stores this weekend!


Reddish hackles

Golden-‐yellow hackles


Methods:

• Amplified Fragment Length Polymorphism AFLP

(Eco+CAT/Eco+GA and Eco+GG/Eco+GC).

• Statistics of population genetics by AFLPsurv.

• Variance-‐based analyses -‐ Principal Component

Analysis PCA and sPCA.

• Distance-‐based -‐ Correlogram.

• Genetic models -‐ Bayesian clustering Geneland

R-‐package: Voronoi tessellation procedures,

spatially explicit, forward MCMC (1,000

iterations in ‘super’ computer) to estimate K

number of genetically distinct populations.

Sites n PLP He PA FST

BDP 5 0.296 0.1242 1 -‐-‐

NCA 6 0.386 0.1380 3 -‐-‐

TKU 9 0.432 0.1432 9 -‐-‐

CTN 44 0.445 0.1533 16 0.0713

HBA 56 0.427 0.1492 8 0.1392

LGO 34 0.368 0.1243 9 0.0625

YDN 58 0.458 0.1916 33 0.1559

TOTAL 212 389 / 431 0.1420 -‐-‐ 0.1028

Table 1.1: Statistics of population genetics for 7 field sites

He expected heterozygosity, PLP proportion of polymorphic loci,

PA private alleles, FST genetic differentiation

CTN

YDN

HBA

LGO

BDP

NCA

TKU

Population Structure Spat ial Range MetapopulationIntroduction Neutral Variation Spatial Dependence Adaptive Variation Conclus ions

PRINCIPAL COMPONENT ANALYSIS


GLOBAL BAYESIAN CLUSTERING

UPGMA dendrogram from 1,000 iterations

9 populational clusters

from 7 sampling sites


GLOBAL BAYESIAN CLUSTERINGModel with all 212 RJFs, UPGMA dendrogram from 1,000 iterations

LGO CTN

YDNHBA


YDNHBA

Strong population structure particularly at local scale -‐congruency between Bayesian clustering genetic models, and:

• Ordination variance-‐based method PCA

• Sampling localities

CTN

YDN

HBA

LGO

CTN YDNHBA LGO

Population St ructure Spat ial Range MetapopulationIntroduction Neutral Variation Spatial Dependence Adaptive Variation Conclus ions

sPCA eigenvalues

sPCA’s regressed PC scores

Correlogram

[Local] Genetic clustering

Spatial range of ≤ 6km

X coordinate

Ycoordinate

km

X coordinate

Ycoordinate

Population St ructure Spat ial Range Metapopulat ionIntroduction Neutral Variation Spatial Dependence Adaptive Variation Conclus ions

Conclusions of neutral genetic variation:

• Strong population structure of Red Junglefowl at both

broad and fine scales.

• Congruencies in PCA, sPCA, correlogram, Bayesian

clustering in detecting structure and spatial patterns.

• Classicalmetapopulation of Red Junglefowl in

geographical context.


G

L

Voronoi Posterior cluster membership

Elevation

Research Question:

Are landscape features deciding factors for (fine-‐scale)

genetic variation?

Hypothesis:

Geographic distance, movement, and demography (e.g.

philopatry) are important factors explaining local

genetic variation in Red Junglefowl.


CCA

QStandardized

Matrixn x n

Regression Q to L

Qfit

Explained Variancesn x n

Qres

Residual Variances

n x n

Variogram

GDissimilarity Coefficients

n x n

LCost Distances

n x n

CA

① ②

③

④

⑤

Methods:Multi-‐Scale Ordination (MSO) of gradient

analysis (CA & CCA), regression, variogram.

① G -‐ AFLP genetic dissimilarity coefficients

4 major field sites & simulated data

② L -‐ Landscape cost distances (least-‐cost)

③ check for CSR

④ Ordination

⑤ Regression

⑥ Variogram

K̂

⑥

K̂

Total Covariances (Genetics to Landscapes)

Residual Variances (Autocorrelation in Genetics)

CA

km

Simulated genotypes(random)

Observed genotypes

FST = 0.071 FST = 0.156FST = 0.063FST = 0.139varia

nces

Ycoordinate

km

CTN YDNLGOHBAIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

CTN YDNHBA LGO

r distance of argument Poisson

X coordinate

Simulated genotypes (structured)

FST = 0.300 FST = 0.300FST = 0.300FST = 0.300

K̂

Point Pattern, Genetic Structure, & Variograms Spat ial Dependence Landscape Classification

change FST

change Spatial Structure FST = 0.300

Spatial Dependence

(CCA)

CTN YDNLGOHBAPoi nt Pattern, Genetic Struc ture, & Variograms Spat ial Dependence Landscape Classification


Topography(CA)

Inertia 1.06%

Inertia 1.38%

Observed genotypes

(CA)

CTN YDNHBA LGO

Point Pattern, Genetic Struc ture, & Variograms Spat ial Dependence Landscape ClassificationIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

CTN

YDN

HBA

LGO

True altitude (0, 2400m) → (1,100) log transform → (0,2) categorical → 1,2,3,4

Point Pattern, Genetic Struc ture, & Variograms Spat ial Dependence Landscape ClassificationIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

Conclusions of spatial dependence:

• Multi-‐scale ordination (MSO) methods can effectively detect spatial genetic covariances

in variogram analysis.

• No spatial dependence of spatial genetic patterns to landscape features.

E.g. Mantel tests have Type I error in matrix permutation of two correlated data sets.

• Classification of landscape patterns is good for model validation.

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Elevation

(B)

Geographic Distance

(A)

Geographic Distance


Hess & Edwards 2002

Shiina et al 2004

Major Histocompatibility Complex (MHC)

84-‐SNP panel in chicken MHC


Research Question:

Are 84-‐SNP MHC genes retained at high diversity and high variation compared to neutrality variation (Chapter 1) and to intensively-‐selected chicken lines?

Hypothesis:

The wild Red Junglefowl’ MHC genes are adaptive (under Balancing Selection) and independent to areas.

Methods:

• 84-‐SNP panel with high-‐density SNP detection KASP platform.

• Bayesian haplotype phasing construction.

• Nucleotide analyses and statistics.

• Recombination and Linkage Disequilibrium analyses.

Selection types

Haplotype var iation Recombinant Popula tion structureIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

Site CTN HBA LGO YDN

Sample 46 56 39 58

Unique haplotypes/chromosomes 92/92 82/112 48/78 91/116

Haplotype diversity Hd 100% 98.97% 97.86% 99.39%

Gene diversity 76 76 71 75

Average number of difference K 24.5745 23.9067 23.4393 24.1789

Nucleotide diversity π 0.2926 0.2846 0.2790 0.2878

Tajima’s D 2.1236 2.1381 2.0641 2.2986

Segregation site S 76 76 71 75

Recombination parameter 0.0065 0.0020 0.0013 0.0024

Recombination rate (average) 1.3100 1.3000 1.13000 1.3400

ρ̂

ρ

Table 3.2: Haplotype

diversity and statistics

of Red Junglefowl in

four sampling sites

Haplotype var iation Recombinant Popula tion structureIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

Line type No. Samples

No. Haplotypes

Nucleotide diversity π

Haplotype diversity Hd

Haplotype percentage

Red Junglefowl -‐ ALL 199 310 77.89%

CTN 46 92 0.29260 100.00% 100.00%HBA 56 82 0.28460 98.97% 73.21%LGO 39 48 0.27900 97.86% 61.54%YDN 58 91 0.28780 99.39% 78.45%Broiler-‐UAB-‐AMC-‐1957 71 8 0.25347 80.42% 5.63%Broiler-‐UAB-‐AMC-‐1978S 64 5 0.19893 63.78% 3.91%Broiler-‐UAB-‐AMC-‐1978D 78 10 0.25537 80.98% 6.41%Broiler-‐UGA-‐ACRB 100 11 0.25796 80.32% 5.50%Broiler-‐UGA-‐ARB 71 4 0.21043 70.95% 2.82%Broiler-‐UAR-‐RB 54 7 0.26625 75.86% 6.48%Standard-‐UAB-‐BPR 76 4 0.24627 73.50% 2.63%Standard-‐UAB-‐SBPR 80 4 0.25612 70.57% 2.50%Standard-‐USK-‐BPR 96 2 0.04281 17.13% 1.04%Standard-‐UAB-‐SRIR 80 4 0.11339 40.58% 2.50%Standard-‐UAB-‐WL 72 3 0.10629 33.41% 2.08%Standard-‐UAB-‐LS 77 3 0.18736 57.92% 1.95%Standard-‐UAB-‐NH 73 4 0.05272 55.93% 2.74%Standard-‐Ill-‐NH 94 3 0.05874 33.23% 1.60%Standard-‐UAB-‐BL 76 1 0.00000 0.00% 0.66%Synthetic-‐Ill-‐PC 92 3 0.13741 52.47% 1.63%Synthetic-‐USK-‐EPI 97 9 0.23621 66.90% 4.64%

Table 3.4:

Comparison of

MHC haplotypes of

Red Junglefowl vs

domestic chickens

~ 99%

~ 3%

~ 80%~ 0.29

~ 56%~ 0.17

Haploty pe v a riation Recombinant Popula tion structureIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

CTN HBA YDNLGO

Recombination: consistently high across populations with significant recombination ‘hotspots’.

0065.0ˆ =ρ3100.1=ρ

0020.0ˆ =ρ3000.1=ρ

0013.0ˆ =ρ

1300.1=ρ

0024.0ˆ =ρ

3400.1=ρ

Haploty pe v a riation Recombinant Popula tion structureIntroduction Neutra l Variation Spatial Dependence Adaptive Variation Conclus ions

D’ < 1, LOD < 2

D’ < 1, LOD >= 2

D’ = 1, LOD < 2

D’ = 1, LOD >= 2

CTN HBA YDNLGO

Linkage Disequilibrium (LD): little LD across the 84-‐SNPs, but evidence of common LD blocks.

CTN

HBA

YDN

LGO

Haploty pe v a riation Recombinant Popula tion s tructureIntroduction Neutra l Variation Spatial Dependence Adaptiv e Varia tion Conclus ions

CTN HBA YDNLGO

Haplotype Networks


CTN HBA LGO YDN

Haplotype Network

(for 4 populations):

too variable, almost

random for structure.

CTN

HBA

YDN

LGO

A


LGO


YDN

P

P

PP

P


Source of Variation Degree of freedom

Sum of Squares

Variance components

Percentage of variation

Among K populations 3 2.79 0.0042 0.83%

Among N individuals within K populations 195 101.18 0.0237 4.66%

Within N individuals 199 94.00 0.4724 94.51%

Total 397 197.98 0.4998 100.00%

FST = 0.0038

(FST = 0.1028 by neutral AFLPs)

Table 3.3: Analysis of Molecular Variance (AMOVA)


Conclusions of MHC adaptive variation:

Tremendous diversity and variation in the 84-‐SNP MHC haplotypes

• Haplotype diversity ~ 100%.

• Unique haplotypes ~ 80% of total haplotypes (compared to ~ 3% in domestic chickens).

• High recombination rates with a few significant recombination hotspots.

• Little linkage disequilibrium blocks.

• No population structure, 94% variation among individual birds.

Under local adaptation and balancing selection.


Species movement -‐ Classical metapopulation structure

(FST = 0.1028) by barriers and spatial range.

NEUTRAL VARIATION ADAPTIVE VARIATION

Balancing selection -‐ Local adaptation (FST = 0.0038, 94% variation

between birds, 80% unique haplotypes) to environmental condition.

Landcover Layer H5N1 exposure

Var i ation i n geographical context Agr i cultural d iversity Conservation implication


One of the richest genetic resources to serve

as genetic resources in future breeding and

conservation programs.

3% MHC diversity in chickens vs. 80% in Red Junglefowl

Wild maize distribution

Variation in geographical context Agr i cultural d iversity Conservation implication


Spatial genetic patterns help to understand other threatened Phasianids in

Southeast Asia and landscape management.

Common Quail Scaly-‐breasted Partridge Germain’s Peacock Pheasant

Variation in geographical context Agri cul tural d iversi ty Conservation implication

Acknowledgements

ü Mark Berres

ü Zach Perry, Triet Tran, Monica Turner, Jun Zhu

ü Sean Schoville, Janet Fulton, Jeb Barzen

ü Staff and trappers of the seven field sites

ü Animal Sciences, Fadl Lab, Kirkpatrick Lab, friends @ Berres Lab, @

HCMC University of Science, @ HCMC Zoo, and @ Southern Institute

of Ecology

ü Hatch Fund, Halpin Fund, Animal Sciences, Rufford Small Grant

Thank you!

Questions, please!

Hoa Nguyen-Phuc - PhD Defense - 2015-08-03 Final Version

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