Reconstructing Deep Population History using Palaeoproteomics

My PhD Project

The last two decades have seen the wide use of methods to extract, identify and utilize biological information from deceased organisms, dating back to thousands of years. From these biological materials we have been able to obtain a vast amount of knowledge regarding our direct ancestors, their movements, diets and diseases. We have also been able to discover information regarding our close relative species along with their ancient admixtures, introgressions and hybridizations. The primary driver for most of these advancements has been aDNA and the various new ways of isolating, amplifying, sequencing and analyzing it. 

In my Phd project we will attempt to use a different source of biological information, ancient protein data, to answer questions about ancient humans, their genetic history, admixture events and population traits as well as evaluate our ability to use this kind of data. The project will be focused on analyzing ancient proteomes from archaic hominids and developing models for inferring their population history during the Pleistocene, as part of the PUSHH European Training Network. 

The main objective will be to use paleoproteomics data to accurately reconstruct population histories and determine the relationships among different groups of hominins, whose genomes are currently unreachable due to their age. We intent to combine ancient protein sequences with in silico translated protein sequences from archaic and modern hominins, so as to reconstruct the gene trees of these sequences and model the deep population history of multiple hominin groups, including population split times and admixture events. An important challenge is that the set of reconstructed gene trees across the genome will not be equivalent to the true population history of our studied hominin groups. Due to incomplete lineage sorting, hybridization and population structure, it is highly likely that a considerable proportion of the gene trees that we reconstruct will have a different topology from the topology of the true population history. We also intend to develop methods that can account for this discordance and maximize the amount of information that can be extracted from these sequences.

Secondments

Secondment period of 3 months in Year 3 under the supervision of Dr. Jurgen Cox at the Max Planck Institute of Biochemistry, Munich, to learn proteomic data analysis with MaxQuant and other specialised tools.

CV

December 2019 - June 2020

Research Internship 

Using a simulation framework of ‘Non-Wright-Fisher’ spatial modeling to assess population collapse, its connection with species genetic diversity erosion and identification using temporaneous sampling.

Evogenomics Lab, GLOBE institute, Faculty of Health and Medical Sciences, University of Copenhagen - Denmark. Under Tom Gilbert with the dual supervision of Shyam Gopalakrishnan and Hernan Morales.

2017 - 2019

Master in Bioinformatics  

MSc Thesis: “Dynamic demographic models for the study of the Second Greek colonization (8th - 6th century BCE).”

Ancient DNA Lab, Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology – Hellas / Evolab , Institute of Computer Science, Foundation of Research and Technology – Hellas. Under the dual supervision of Dimitris Kafetzopoulos (♰) and Pavlos Pavlidis.

February 2017 - May 2017

Erasmus+ experience 

Project: “Analysis of the intra- and inter-population genomic diversity of human Tunisian populations” 

Anthropology Lab, Department of Animal and Human Biology, University of Rome “La Sapienza”. Under the supervision of  Destro-Bisol Giovanni and Paulo Anagnostou.

2012 – 2017

Bachelor in Biology 

BSc Thesis: “Evolution of Algyroides nigropunctatus and Algyroides moreoticus in the Balkan Peninsula.”

Molecular Systematics Lab, Natural History Museum of Crete. Under the supervision of Nikolaos Poulakakis. 

Publications

Taurozzi, A. J., Rüther, P. L., Patramanis, I., Koenig, C., Sinclair Paterson, R., Madupe, P. P., ... & Cappellini, E. (2024). Deep-time phylogenetic inference by paleoproteomic analysis of dental enamel. Nature Protocols, 1-32.

Pinto, A. V., Hansson, B., Patramanis, I., Morales, H. E., & van Oosterhout, C. (2024). The impact of habitat loss and population fragmentation on genomic erosion. Conservation Genetics, 25(1), 49-57.

Kubat, J., Paterson, R., Patramanis, I., Barker, G., Demeter, F., Filoux, A., ... & Bacon, A. M. (2023). Geometric morphometrics and paleoproteomics enlighten the paleodiversity of Pongo. Plos one, 18(12), e0291308.

Madupe, P. P., Koenig, C., Patramanis, I., Rüther, P. L., Hlazo, N., Mackie, M., ... & Cappellini, E. (2023). Enamel proteins reveal biological sex and genetic variability within southern African Paranthropus. bioRxiv, 2023-07.

Patramanis, I., Ramos-Madrigal, J., Cappellini, E., & Racimo, F. (2023). PaleoProPhyler: a reproducible pipeline for phylogenetic inference using ancient proteins. Peer Community Journal, 3.