- Large genomic datasets are key to understanding species’ evolution, but analysis of such large datasets can be slow and requires lots of computational power.
- A team led by researchers at Queen Mary University of London, University of Bristol and UCL have developed a more efficient method to estimate evolutionary timelines using genomic datasets.
- Using their novel computational approach, the researchers confirmed modern mammal groups originated after the Cretaceous-Palaeogene mass extinction, shedding new light on a long-standing controversy in evolutionary biology.
A new study, published today in the journal Nature, has provided the most detailed timeline of mammal evolution to date.
The research describes a new and fast computational approach to obtain precisely dated evolutionary trees, known as ‘timetrees’. The authors used the novel method to analyse a mammal genomic dataset and answer a long-standing question around whether modern placental mammal groups originated before or after the Cretaceous-Palaeogene (K-Pg) mass extinction, which wiped out over 70 per cent of all species, including all dinosaurs.
The findings confirm the ancestors of modern placental mammal groups postdate the K-Pg extinction that occurred 66 million years ago, settling a controversy around the origins of modern mammals. Placental mammals are the most diverse group of living mammals, and include groups such as primates, rodents, cetaceans, carnivorans, chiropterans (bats) as well as humans.
The research team was led by Dr Mario dos Reis (Queen Mary University of London) and Professor Phil Donoghue (University of Bristol), and included scientists from Queen Mary, University of Bristol, UCL, Imperial College London, and the University of Cambridge.
Dr Sandra Álvarez-Carretero, lead author of the paper from UCL (then at Queen Mary), says: “By integrating complete genomes in the analysis and the necessary fossil information, we were able to reduce uncertainties and obtain a precise evolutionary timeline. Did modern mammal groups co-exist with the dinosaurs, or did they originate after the mass extinction? We now have a definite answer.”
“The timeline of mammal evolution is perhaps one of the most contentious topics in evolutionary biology. Early studies provided origination estimates for modern placental groups deep in the Cretaceous, in the dinosaur era. The past two decades had seen studies moving back and forth between post- and pre-K-Pg diversification scenarios. Our precise timeline settles the issue.” adds Prof Donoghue, co-senior author of the paper.
With worldwide sequencing projects now producing hundreds to thousands of genome sequences, and with imminent plans to sequence more than a million species, evolutionary biologists will soon have a wealth of information at their hands. However, current methods to analyse the vast genomic datasets available and create evolutionary timelines are inefficient and computationally expensive.
“Inferring evolutionary timelines is a fundamental goal of biology. However, state-of-the-art methods rely on using computers to simulate evolutionary timelines and assess the most plausible ones. In our case, this was difficult due to the gigantic dataset analysed, involving genetic data from almost 5,000 mammal species and 72 complete genomes,” Dr dos Reis says.
In this study, the researchers developed a new, fast Bayesian approach to analyse large numbers of genome sequences, whilst also accounting for uncertainties within the data. “We solved the computational hurdles by dividing the analysis in sub-steps: first simulating timelines using the 72 genomes and then using the results to guide the simulations on the remaining species. Using genomes reduces uncertainty because it allows rejection of unplausible timelines from the simulations,” says Dr dos Reis.
“Our data processing pipeline sourced as much genomic data for as many mammal species as possible. This was challenging because genetic databases contain inaccuracies and we had to develop a strategy to identify poor quality samples or mislabelled data that had to be removed,” adds Dr Asif Tamuri, co-lead author of the paper from UCL, who was responsible for assembling the mammal genomic dataset.
Using their novel approach, the team were able to reduce computation time for this complex analysis from decades to months. “If we had tried to analyse this large mammal dataset in a supercomputer without using the Bayesian method we have developed, we would have had to wait decades to infer the mammal timetree. Just imagine how long this analysis could take if we were to use our own PCs,” says Dr Álvarez-Carretero. “In addition, we managed to reduce computation time by a factor of 100. This new approach not only allows the analysis of genomic datasets, but also, by being more efficient, substantially reduces the CO2 emissions released due to computing,” Dr Álvarez-Carretero continues.
The method developed in the study could be used to tackle other contentious evolutionary timelines that require analysis of large datasets. By integrating the novel Bayesian approach with the forthcoming genomes from the Darwin Tree of Life and Earth BioGenome projects, the idea of estimating a reliable evolutionary timescale for the Tree of Life now seems within reach.
The research was funded by the Biotechnology and Biological Sciences Research Council.
ENDS
Notes to editors
- Research publication: ‘A Species-Level Timeline of Mammal Evolution Integrating Phylogenomic Data’ Álvarez-Carretero et al. (2021) Nature DOI: 10.1038/s41586-021-04341-1
- Once the embargo lifts, the paper will be available at: https://www.nature.com/articles/s41586-021-04341-1
- For more information or a copy of the paper, please contact: m.dosreisbarros@qmul.ac.uk
About Queen Mary University of London
At Queen Mary University of London, we believe that the diversity of ideas helps us achieve the previously unthinkable.
Throughout our history, we’ve fostered social justice and improved lives through academic excellence. And we continue to live and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers.
Our reformer heritage informs our conviction that great ideas can and should come from anywhere. It’s an approach that has brought results across the globe, from the communities of east London to the favelas of Rio de Janeiro.
We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.
About UCL – London’s Global University
UCL is a diverse global community of world-class academics, students, industry links, external partners, and alumni. Our powerful collective of individuals and institutions work together to explore new possibilities.
Since 1826, we have championed independent thought by attracting and nurturing the world's best minds. Our community of more than 43,800 students from 150 countries and over 14,300 staff pursues academic excellence, breaks boundaries and makes a positive impact on real world problems.
We are consistently ranked among the top 10 universities in the world and are one of only a handful of institutions rated as having the strongest academic reputation and the broadest research impact.
We have a progressive and integrated approach to our teaching and research – championing innovation, creativity and cross-disciplinary working. We teach our students how to think, not what to think, and see them as partners, collaborators and contributors.
For almost 200 years, we are proud to have opened higher education to students from a wide range of backgrounds and to change the way we create and share knowledge.
We were the first in England to welcome women to university education and that courageous attitude and disruptive spirit is still alive today. We are UCL.
www.ucl.ac.uk | Follow @uclnews on Twitter | Read news at www.ucl.ac.uk/news/ | Listen to UCL podcasts on SoundCloud | Find out what’s on at UCL Minds
Journal
Nature
Article Title
A Species-Level Timeline of Mammal Evolution Integrating Phylogenomic Data
Article Publication Date
22-Dec-2021