Plenary Lecture

When did Mitochondrial Eve Live? - Computer Simulations Can Help to Answer the Question.

Professor Krzysztof A. Cyran
Institute of Informatics,
Silesian Univ. of Technology,
Gliwice, Poland
Email: Krzysztof.Cyran@polsl.pl

Abstract: One of the crucial issues in contemporary evolutionary genetics is the problem of dating the common ancestors of different species. It is a well-known fact that the results of analysis of genetic variation are affected by history of given population. Applicability of several existing approaches based on coalescence theory is limited to deterministic population histories, known to be unrealistic in the case of our own species. In the lecture the computer simulation-based approach will be presented, which is capable of dealing with arbitrary population history scenarios, including populations evolving stochastically and/or with environmental changes. This approach arises from the comparison of O’Connell model of branching processes genealogy and Wright-Fisher model of genetic drift. The latter assumes multinomial sampling between generations and thus asymptotically Poisson distribution of the number of progeny for any individual. Since the assumptions of this model are not always fulfilled in reality, there exists a problem of the influence of the departure from WF model on the distribution of the coalescence time and further analysis of genetic variation. The lecture will show an attempt to solve the problem using time-forward computer simulations of branching processes and numerically approximated distribution of coalescence time for a pair of alleles. There have been performed simulations of over 105 human population histories evolving for 104 generations. Assuming the human generation length to be approximately 20 years, each simulation history corresponds to 200,000 years. Simulations of so many trajectories modeling such long periods in an unbiased way excluded the use of built-in pseudo-random number generator. The reason for that is either too short range of generator aperiodicity or failing some statistical tests. Therefore there was implemented an advanced random number generator being the composition of two other generators. This advanced generator had the desirable aperiodicity length of 2144, furthermore, it satisfied known statistical tests. These methods were applied to estimate the age of our most recent female common ancestor, often called Mitochondrial Eve. The estimates are based on the genetic material taken from hyper variable region I (HVRI) and hyper variable region II (HVRII) of mitochondrial DNA belonging to contemporary humans and Neanderthal fossils. Obtained results indicate that after changing the outgroup from chimpanzee to Neanderthals, the stochastic genetic models with different assumptions tend to give similar predictions, and therefore these predictions are much more reliable than they were before. Moreover, these estimates are very similar to those obtained lately by other researchers with the use of phylogenetic trees, which increases reliability of both estimates obtained by conceptually different methods.
 

Brief Biography of the Speaker:
Krzysztof Cyran was born in 1968, in Cracow, Poland. He received MSc degree in computer science (1992) and PhD degree (with honours) in technical sciences with specialty in computer science (2000) from the Silesian University of Technology SUT, Gliwice, Poland. His PhD dissertation addresses the problem of image recognition with the use of computer generated holograms applied as ring-wedge detectors. In 2003-2004 he was a Visiting Scholar in Department of Statistics at Rice University in Houston, US. He is currently the Assistant Professor and the Vice-Head of the Institute of Informatics at SUT.

Dr Cyran has received several awards of the Rector of the SUT for his scientific achievements. In 2004-2005 he was a member of International Society for Computational Biology. He is a member of the Editorial Board of Journal of Biological Systems and a reviewer for Optoelectronic Review, Mathematical Biosciences and Engineering, and Studia Informatica.

He has been an author and co-author of more than 60 technical papers in journals (several of them indexed by Thomson Scientific) and conference proceedings, and has been involved in numerous statutory projects led at the Institute and some scientific grants awarded by the State Committee for Scientific Research. His current research interests are in image recognition and processing, artificial intelligence, digital circuits, decision support systems, rough sets, computational population genetics and bioinformatics.