Population Structure and History in Sub-Saharan Africa Manjinder Sandhu

Why study genetic diversity in Africa? Africa has the greatest genetic and linguistic diversity in the world Genetic diversity has implications for the design of studies Can large scale genomic studies be carried out across Africa? Can we utilise population differentiation for fine mapping? Can admixture mapping be used for certain traits?

What is the African Genome Variation Project? Study of 16 ethno-linguistic groups across SSA from populations relevant to medical genomics 100 individuals with dense (2.5M) genotype data in each Largest diversity panel from Africa so far Aim: to study genetic variation in Africa to inform large scale studies in African genomics

Population structure and admixture

Eurasian cline YRI CEU

Khoe-San cline YRI Juhoansi

European and Khoe-San admixture in SSA South Africa North Africa East Africa East Central Africa West Central Africa West Africa Bantu Khoe-San K=2 K=3 K=4 K=5 K=6

Population differentiation

Confirming Eurasian and Khoe-San admixture pop A pop B pop C f3,C;A,B Z score CEU YRI Zulu 0.00543 33.528 Fula -0.01115 -59.361 Jola 0.005366 31.897 Mandinka -4.5E-05 -0.338 Wolof -0.00079 -5.376 Baganda -0.00316 -23.709 Banyarwanda -0.01206 -74.707 Barundi -0.00904 -64.071 LWK -0.00322 -21.533 Kalenjin -0.01042 -50.547 Kikuyu -0.01618 -89.291 SOMALI -0.01459 -47.375 AMHARA -0.02385 -87.02 OROMO -0.02391 -85.192 Igbo 0.000502 5.297 Ga-Adangbe 0.000008 0.078 Sotho 0.005022 31.282 pop A pop B pop C f3,C;A,B Z score YRI Juhoansi Zulu -0.00705 -44.604 Sotho -0.00984 -64.773 Fula 0.005064 38.379 Jola 0.007087 51.022 Mandinka 0.003206 29.069 Wolof 0.005002 40.037 Baganda -0.00067 -6.157 Barundi -0.00207 -19.407 Banyarwanda -0.00044 -3.81 LWK -0.00017 -1.394 Kikuyu 0.003081 20.333 Kalenjin 0.009667 49.396 Igbo -0.0004 -5.39 Ga-Adangbe -5.9E-05 -0.773 OROMO 0.042493 92.355 AMHARA 0.048456 99.369 SOMALI 0.043256 94.98

Quantifying and dating admixture European admixture Khoe-San admixture

European and HG admixture in SSA Khoe-San admixture European admixture

Interpretation Widespread European admixture in all SSA populations, dating to different time-points Broadly consistent with demographic history Hunter gatherer admixture seen in many SSA populations, particularly southern bantu populations Dating consistent with the bantu expansion

How can this information be leveraged in the study of African genomics Most populations used for epidemiological studies in Sub-Saharan Africa are not very differentiated Differentiation seems to arise largely from admixture rather than divergence or drift Implications for large-scale genomic studies and fine mapping

Next steps Using admixture mapping of traits for phenotypically differentiated diseases between different populations Understanding the relationship between admixture and LD structure in African populations in the context of fine mapping

Acknowledgements WTSI South Africa Deepti Gurdasani Eleftheria Zeggini Tommy Carstensen Savita Karthikeyan Cristina Pomilla Georgina Murphy Elizabeth Young Ioanna Tachmazidou Konstantinos Hatzikotoulas Wellcome Trust MRC Uganda Anatoli Kamali Janet Seely Pontiano Kaleebu CRGGH Charles Rotimi Daniel Shriner Fasil Ayele Ayesha Motala Fraser Pirie Michele Ramsey Ananyo Choudhury Ghana/Kenya/Nigeria Adebowale Adeyemo Albert Amoah Clement Adebamowo Johnnie Oli Ethiopia Chris Tyler Smith Luca Pagani Malariagen Dominic Kwiatkowski Sanger pipelines