Learning about human demography and natural selection with ancient DNA

Iain Mathieson

Department of Genetics

Perelman School of Medicine

University of Pennsylvania

1

Lazaridis et al. 2014

“Ancient human genomes

suggest three ancestral

populations for present-day

Europeans”2

Cumulative published ancient human genome-wide data

32010 2012 2014 2016 2018 2020

Cum

ula

tive a

ncie

nt hum

an g

eno

mes

01

000

20

00

3000

400

05

000

Haak, Lazaridis et al. 2015 Massive migration from the steppe was a source for Indo-European languages in Europe4

Mittnik et al. 2019 Kinship-based social inequality in Bronze Age Europe

Cassidy et al. 2020 A dynastic elite in monumental Neolithic society

Amorim et al. 2018 Understanding 6th-century barbarian social organization and migration through paleogenomics 5

Keller et al. 2018 Ancient Yersinia pestis genomes from across Western Europe reveal early diversification during the First Pandemic (541–750)

Spyrou et al. 2018 Analysis of 3800-year-old Yersinia pestis genomes suggests Bronze Age origin for bubonic plague

6

Images: Cornelius Bachter, Lot Tourisme, Istvan Takas, South Tyrol Museum, Kenny Arne Lang Antonsen, John Maynard Friedman

How do humans adapt to environmental, cultural and social change?

7

8

Mesolithic Neolithicpost-

Neolithic11,000 BP 5500 BP

7000 BP

4500 BP

26,000 BP

Early Late

1000 BP45,000 BP

BP: Years before present

Upper PaleolithicUpper Paleolithic

9

10,000 years ago

Skoglund et al. 2012Lazaridis et al. 2014

Olalde et al. 2014Gamba et al. 2014

Jones et al. 2015Haak et al. 2015Jones et al. 2017

Gonzalez-Fortes et al 2018Mathieson et al. 2018

10

Early Farmers~8500 BP

7100 BP

5100 BP

4900 BP

7000 BP8500 years ago to 5000 years ago

Bramanti et al. 2009Skoglund et al. 2012Lazaridis et al. 2014

Gamba et al. 2014Skoglund et al. 2014

Haak et al. 2015Mathieson et al. 2015

Cassidy et al. 2016Hofmanová et al. 2016

Lipson et al. 2017Mathieson et al. 2018

11

Mesolithic Neolithic

11,000 BP 5500 BP

7000 BP

4500 BP

26,000 BP

Early Late

45,000 BP

BP: Years before present

Upper PaleolithicUpper Paleolithic

12

Steppe ancestry~4500 BP

4500 years ago

Allentoft et al. 2015Haak et al. 2015

Olalde et al. 2018Gamba et al. 2014Cassidy et al. 2016

13

Mesolithic Neolithicpost-

Neolithic11,000 BP 5500 BP

7000 BP

4500 BP

26,000 BP

Early Late

1000 BP45,000 BP

BP: Years before present

Upper PaleolithicUpper Paleolithic

14

13980 7700 6950 5620 4935 4405 4191 3856 3350 2400 1345

Individual Date (years BP)

Ance

stry

0.0

0.2

0.4

0.6

0.8

1.0

Time (years BP)

Ancestry

14,000 7000 5000 4000 3000 2000

Hunter-gatherer

Early Farmer

Steppe 15

13980 7700 6950 5620 4935 4405 4191 3856 3350 2400 1345

Individual Date (years BP)

Ancestry

0.00.2

0.40.6

0.81.0

Agriculture Metallurgy

Images: South Tyrol Museum, Kenny Arne Lang Antonsen, John Maynard Friedman

Urbanization Social hierarchy

Changes in genetic ancestry

How do humans adapt to environmental, cultural and social change?

16

Detecting selection with ancient DNA

17

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-lo

g1

0(P

-valu

e)

0

10

20

30

40

50

60

Chromosome

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 20 22

LCT

TLR1

SLC45A2

SLC22A4

MHC

ZSCAN31

DHCR7NADSYN1GRM5 ATXN2

OAS1

CHR13:31MbHERC2

CYP1A2

14 genome-wide significant signals of selection

Mathieson I et al.

Genome-wide signals of selection in 230 ancient Eurasians

December 2015 18

LCT: Lactase persistence

NADSYN1/DHCR7: Vitamin D metabolism

FADS1/2: Decreased triglyceride levels

ATXN2/SHD2B3: Associated with celiac disease, Type 1 diabetes

SLC22A4: Ergothioneine uptake, celiac disease, IBD

CYP1A1: Metabolism of exogenous substances; caffeine.

SLC45A2, GRM5: Light skin pigmentation

HERC2/OCA2: Blue eye color

TLR1/6/10: Immunity, leprosy, TB and other mycobacterial resistance

OAS1/2/3: Viral resistance; Neanderthal introgressed haplotype

ZSCAN32: Autophagy

MHC: Immunity, everything.

Diet

Pigmentation

Immunity

19

35°N

40°N

45°N

50°N

55°N

60°N

10°W 5°W 0° 5°E 10°E 15°E 20°E

Longitude

Latitu

de

Alle

le f

requ

en

cy

Se

lectio

n c

oeff

icie

nt

010002000300040005000

0.0

0.2

0.4

0.6

0.00

0.01

0.02

Date in years BP

Population

Britain

Central

Iberia

Italy

Lactase persistence appears very recently

Date in years BP5000 4000 3000 2000 1000 0

20

Selection coefficient

rs1229984 (ADH1B)

Selection coefficient

rs671 (ALDH2)

Allele frequency

rs1229984 (ADH1B)

Allele frequency

rs671 (ALDH2)

02000400060008000 02000400060008000

0.0

0.1

0.2

0.3

0.0025

0.0050

0.0075

0.0100

0.0

0.2

0.4

0.6

0.8

0.005

0.010

0.015

0.020

Date in years BP

Population

North

South

CHB

CHS

20°N

25°N

30°N

35°N

40°N

45°N

50°N

55°N

90°E 100°E 110°E 120°E 130°E

Longitude

Latitu

de

Ethanol Acetaldehyde Acetic Acid

ADH1B ALDH2

Selection on the alcohol dehydrogenase pathway in East Asia

21

LCT: Lactase persistence

NADSYN1/DHCR7: Vitamin D metabolism

FADS1/2: Decreased triglyceride levels

ATXN2/SHD2B3: Associated with celiac disease, Type 1 diabetes

SLC22A4: Ergothioneine uptake, celiac disease, IBD

CYP1A1: Metabolism of exogenous substances; caffeine.

SLC45A2, GRM5: Light skin pigmentation

HERC2/OCA2: Blue eye color

TLR1/6/10: Immunity, leprosy, TB and other mycobacterial resistance

OAS1/2/3: Viral resistance; Neanderthal introgressed haplotype

ZSCAN32: Autophagy

MHC: Immunity, everything.

Diet

Pigmentation

Immunity

22

Fumagalli et al 2015

Increase; p < 0.0001

Decrease; p<0.0001

Increase; p < 0.05

Increase

Decrease; p<0.05

Decrease

What does the selected FADS allele do?

Trait p-valueMean platelet (thrombocyte) volume 3.0477e-105Red blood cell (erythrocyte) distribution width 5.1363e-93Platelet count 1.256e-87Red blood cell (erythrocyte) count 1.2592e-50Haemoglobin concentration 5.6775e-40Monocyte percentage 8.5623e-30Platelet crit 2.7662e-25Mean sphered cell volume 4.3386e-25Eosinophill count 5.2404e-25Haematocrit percentage 1.8602e-23Mean corpuscular volume 2.7039e-21

Top 10 UK Biobank PheWAS

http://geneatlas.roslin.ed.ac.uk

One of the most significant

genome-wide signals for lipids

(Teslovitch et al. 2010)

Other associations:

Sex-hormone binding globulin

(P=10-20)

Male testosterone (P=10-5)

Male estrodiaol (P=10-4)23

See also:

Harris et al. 2019

Hlusko et al. 2019

Mathieson & Mathieson 2018

Buckley et al. 2017

Ye et al. 2017

Amorim et al. 2017

Mathieson et al. 2015

Fumagalli et al. 2015

Mathias et al. 2012

Ameur et al. 2012

Mathieson (2020)

In fact, FADS1 has been under selection

for hundreds of thousands of years…

24

Ameur et al. 2012

Derived allele

Ancestral allele

“Mixed” (~derived)

25

See also:

Harris et al. 2019

Hlusko et al. 2019

Mathieson & Mathieson 2018

Buckley et al. 2017

Ye et al. 2017

Amorim et al. 2017

Mathieson et al. 2015

Fumagalli et al. 2015

Mathias et al. 2012

Ameur et al. 2012

Mathieson (2020)

In fact, FADS1 has been under selection

for hundreds of thousands of years…

26

Mathieson 2020

But…. the selected (ancestral) allele was already common

before the split of Eurasian and Native American ancestors

(consistent with a meat-heavy Upper Paleolithic diet)

27

See also:

Harris et al. 2019

Hlusko et al. 2019

Mathieson & Mathieson 2018

Buckley et al. 2017

Ye et al. 2017

Amorim et al. 2017

Mathieson et al. 2015

Fumagalli et al. 2015

Mathias et al. 2012

Ameur et al. 2012

Mathieson (2020)

In fact, FADS1 has been under selection

for hundreds of thousands of years…

28

Years BP

De

rive

d a

llele

fre

quen

cy

0.02

0.02

0.04

0.04

0.06

0.06

0.08 0.08 0.1 0.12

12000 10000 8000 6000 4000 2000 0

0.0

0.2

0.4

0.6

0.8

1.0

0.01

0.01

0.02

0.02

0.03

0.03

0.04

0.04

0.05

0.05

0.06

0.06

0.07

0.07

0.08

0.08 0.09 0.1 0.11

0.12 0.02

0.02

0.04

0.04

0.06

0.06

0.08

0.08 0.1 0.1

0.12

0.12

0.14

●

●

●

●

Hunter−gatherers

Early Farmers

Steppe Ancestry

Direct evidence of selection on the derived allele

Mathieson & Mathieson (2018)

In Europe

02000400060008000

0.0

0.2

0.4

0.6

0.005

0.010

0.015

0.020

Date in years BP

Region

North

South

In East Asia

8000 4000 06000 20008000 4000 06000 200010,00012,000

Date in years before present Date in years before present

29

See also:

Harris et al. 2019

Hlusko et al. 2019

Mathieson & Mathieson 2018

Buckley et al. 2017

Ye et al. 2017

Amorim et al. 2017

Mathieson et al. 2015

Fumagalli et al. 2015

Mathias et al. 2012

Ameur et al. 2012

Mathieson (2020)

In fact, FADS1 has been under selection

for hundreds of thousands of years…

30

… and may still be under selection today

Mathieson et al. (bioRxiv)

Genome-wide analysis identifies genetic effects on reproductive

success and ongoing natural selection at the FADS locus.

CADM2 – strong signal of balancing selectionassociated with risk-taking behavior

FADS1

Melinda Mills John Perry31

Selection scan (past 10,000 years)

Mathieson et al. (2015); selection

coefficient estimated to be 0.78%

Genome-wide association study for fertility

Derived allele increases number of children

by ~0.013, corresponding to a selection

coefficient of ~0.74%

… and may still be under selection today

Mathieson et al. (bioRxiv)

Genome-wide analysis identifies genetic effects on reproductive

success and ongoing natural selection at the FADS locus. 32

Years BP

De

rive

d a

llele

fre

qu

en

cy

0.02

0.02

0.04

0.04

0.06

0.06

0.08

0.08

0.1

0.1

0.12

0.12

0.14

0.14 0.16

0.16

12000 10000 8000 6000 4000 2000 0

0.0

0.2

0.4

0.6

0.8

1.0

0.01

0.01

0.02

0.02

0.03

0.03

0.04

0.04

0.05

0.05

0.06

0.06

0.07

0.07

0.08

0.08 0.09

0.1

0.11

0.12

0.02

0.02

0.04

0.04 0.06

0.06

0.08

0.08

0.1

0.1

0.12

0.12

Hunter−gatherers

Early Farmers

Steppe Ancestry

EarlyUP

ElMiron

Malta

Satsurblia

(cov=7.8)

Vestonice

Villabruna

0.0

0.2

0.4

0.6

0.01 0.10 1.00

Coverage

Derived haplotype frequency (false positive)

Villabruna

EarlyUPVestonice

ElMiron

Malta

Satsurblia

EarlyUP

ElMiron

Malta

Satsurblia

Vestonice

Villabruna

0.0

0.2

0.4

0.6

100002000030000

Date (Years BP)

Derived haplotype frequency

Method

Direct

Imputed

Years BP

Mathieson & Mathieson 2018

Increases in frequency by about 20% in 4,000 years

(0.005% per-year, correcting for changes in ancestry)

Increases by 0.009% per-birth-year

in UK Biobank (correcting for 10

PCs and assessment center)

Mathieson et al. bioRxiv

No other fertility GWAS signals overlap with historical selection scans (CMS, SDS or ancient DNA

scans) (with the exception of CADM2 which has a strong signal of long-term balancing selection)

… and may still be under selection today

33

• How did humans adapt to changes in environment and culture? Evolutionary change is one (but only one) aspect.

• Ancient DNA allows us to track the evolution of functional loci very precisely in time and space.

• The real goal here is to try to understand why these loci are under selection by integrating archaeological and biological evidence.

• The FADS locus is an extreme (perhaps unique) example of an allele that has been under selection, at different times and places, for hundreds of thousands of years.

34

Selection on polygenic traits

Dan JuSamantha Cox 35

Jablonski & Chaplin 200936

~180 independent loci for skin pigmentation

Data: UK Biobank; Visualization: http://geneatlas.roslin.ed.ac.uk37

AFR

EAS

EUR

SAS

0.0

0.5

1.0

010000200003000040000

Date (years BP)

Score

Dark skin pigmentation alleles were more common in the past

Proportion of dark skin

pigmentation alleles

Ju & Mathieson 2020 bioRxiv38

0.0

0.5

1.0

500010000

Date (years BP)

Score

Population

EF

HG

SP

Proportion of dark skin

pigmentation alleles

Hunter-gatherersEarly farmersSteppe ancestry

Dark skin pigmentation alleles were more common in the past

Ju & Mathieson 2020 bioRxiv39

Selection driven by a relatively small number of variants

DDB1

HERC2HERC2

SLC24A5

MC1R

SLC45A2

0.00

0.01

0.02

0.03

0.04

0.000 0.005 0.010 0.015

VE within UK

VE

be

twe

en

UK

and

YR

I

Ju & Mathieson 2020 bioRxiv

Variance explained within the UK population

Variance explained between UK and West Africa

40

Selection on skin pigmentation likely drove frequency changes at 5-10 large-effect loci

Alleles associated with lighter skin pigmentation were less common in the past

The data are consistent with constant selection over the past 45,000 years

Caution against interpreting these results as prediction of pigmentation in ancient populations.

41

Anatomical femur length

Lateral tibia length

Talo-cural height

Sacral height

Vertebral height

Basion-bregma height

“Anatomical model” Fully 1956

“Mathematical model” Trotter & Gleser 1952

See: Raxter, Auerbach & Ruff 2006

Stature estimation from skeletons

Slide: Samantha Cox 42

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1617

1819

2021

22

0

50

100

150

200

250

Chromosome

log 1

0p

-val

ue

Height

Genome-wide association studies for height

UK Biobank: ~3000 genome-wide significant loci

=

𝑆𝑁𝑃𝑠

𝛽𝑖𝑋𝑖

For some set {i} of SNPs, effect sizes 𝛽 and genotypes 𝑋

Polygenic risk score (PRS)

43

Height PRS predicts skeletal stature

44

p=0.002

p=8.7x10-11

p= 2.9x10-7

p=3.6x10-5

Cox SL, Ruff CB, Maier RM & Mathieson I Genetic effects on stature in Prehistoric Europe 2019

p=8.2x10-7

Cox SL, Ruff CB, Maier RM & Mathieson I Genetic effects on stature in Prehistoric Europe 2019

Sitting height remains nearly constant

45

Recent decrease in bone density

[Chirchir et al 2017] 46

Neolithic decrease in bone density and strength

p=0.002

p= 2.9x10-7

p=3.6x10-5

Heel Bone Mineral Density PRS

Cox SL, Ruff CB, Maier RM & Mathieson I Genetic effects on stature in Prehistoric Europe 2019

Femoral bending strength

47

Chan et al. 2015

Decreasing limb length in

paleolithic Europe may have a

genetic basis

Reflects difference between

present-day Northern and Tropical

populations

An example of Allen’s rule, driven

by adaptation to climate?

Stature certainly seems adaptive….

48

Increasing stature in Bronze Age Steppe

ancestry populations contemporary with

increasing social inequality, rapid

population range expansions and increased

male reproductive variance.

Stature certainly seems adaptive….

Varna Man - 6500 years ago

Buried with more gold than anyone ever had before

Image: Ivan Ivanov

Varna regional museum of history49

Steppe ancestry is fairly strongly correlated with stature…

Skoglund & Mathieson 201850

…but the causality is unclear

Present-day populations with

more steppe ancestry are taller

Height-increasing variants are

associated with steppe ancestry

Environmental effects cause greater

height in some populations

Steppe populations were genetically taller than other

populations

Question 1Natural

selection

Genetic drift

Question 2

1. Are there genetic differences in height between populations?

2. If there are differences, are they driven by selection

51

• For skin pigmentation we can find robust evidence of polygenic selection. Ancient DNA allows us to identify the timing of selection, as for single loci.

• For height, we can actually measure the correlation with phenotypes, but the genomic evidence for selection is unclear. Technical issues such as population stratification in GWAS limit our ability to make inference

• Future program involves using ancient DNA to resolve the interaction of genetics and environment.

52

AcknowledgmentsPennSamantha CoxDan JuBárbara BitarelloLaura ColbranArslan Zaidi

ElsewhereDavid Reich (Harvard)Sara Mathieson (Haverford)Christopher Ruff (Johns Hopkins)John Perry (Cambridge)Melinda Mills (Oxford)

Results and opinions presented here are the responsibility of the author(s) and do not necessarily represent the official views of NIH or other funding sources

53

54

Questions?