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School of Biological and Behavioural Sciences

Matteo Fumagalli, has recently published a paper about the genomic footprint of social stratification in admixing American populations.

Senior Lecturer in Genetics, Matteo Fumagalli, has recently published a paper about the genomic footprint of social stratification in admixing American populations.

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Senior Lecturer in Genetics, Matteo Fumagalli, has recently published a paper about the genomic footprint of social stratification in admixing American populations.

With funding from the Leverhulme Trust and working alongside Alex Mas-Sandoval and Sara Mathieson he has helped define the genetic effect of social stratification by proposing a new mating model.

Cultural and socioeconomic variances play a pivotal role in dividing human societies and moulding their genetic composition beyond the influence of geography alone. While mating choices are often influenced by sociocultural stratification, many demographic models in population genetics typically assume random mating.

Exploiting the correlation between sociocultural stratification and the distribution of genetic ancestry in admixed populations, their study aims to infer this complex process in the Americas.

To do so, the group conducted simulations encompassing a broad spectrum of admixture scenarios under this model. Subsequently, they deep neural network to accurately predict mating parameters based on genomic data.

The findings illustrate how population stratification, influenced by socially constructed racial and gender hierarchies, has significantly shaped admixture dynamics in the Americas since European colonization and the subsequent Atlantic slave trade.

When he is not researching, Dr Matteo Fumagalli is busy teaching a range of modules across undergraduate and postgraduate level in evolution, statistics and software development while contributing to the Centre for Academic Inclusion in Science and Engineering.

To read more about this study please visit: https://pubmed.ncbi.nlm.nih.gov/38038347/

 

 

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