Reconstructing Deep Population History using Palaeoproteomics

ESR13 Ioannis Patramanis

Born and raised in Athens but having spent around 7 years of studying and living in Crete.

Ever since I finished school I have harbored an interest in biology, especially evolutionary biology, which I have been able to satisfy with my academic choices. Along with this however, I have always been excited over human history. The last few years I have been able to combine these seemingly different interest into one, via the study of human population genetics. Through my internship projects as well as my Master in bioinformatics, I have been able to both learn the basic theory of population genetics and familiarize myself with the most popular tools and formats used in the field.

Now, with this Phd project, I find myself officially entering the field of population genetics and anthropology in search of new methods and ways to uncover our own past. Our project involves the use of protein data from ancient human remains to infer population histories without the acquisition of aDNA, as well as a theoretical and statistical evaluation of the techniques we will be using to do so. Finally we will be looking into state of the art machine learning methods to improve the amount of information that can be obtained from ancient proteins

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.

Planned secondments

Secondment period of 4 months, during PhD year 2, at University of Luxembourg under Aurélien Ginolhac’s supervision to build a pipeline streamlining the entire palaeoproteomic bioinformatic workflow, including peptide-spectrum matching, damage detection, amino acidic substitution detection and phylogeny reconstruction.


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.

Host Institution

Denmark 🇩🇰



Jürgen Cox 🇩🇪