New information on the evolution of modern mammals

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A new study has provided the most detailed chronology of mammalian evolution to date.

The research describes a new rapid computational approach to obtain precisely dated evolutionary trees, called “time trees”.

The authors used the new method to analyze a mammalian genomic dataset in an attempt to answer a long-standing question of whether modern mammal groups appeared before or after the Cretaceous-Paleogene mass extinction (K -Pg), which wiped out over 70 percent of all species, including all dinosaurs.

The results, published in the journal Nature, confirm the ancestors of modern mammal groups after the extinction of K-Pg that occurred 66 million years ago, settling a controversy over the origins of modern mammals.

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 UCL article (then at Queen Mary), said: “By incorporating complete genomes into the necessary analysis and fossil information, we were able to reduce uncertainties and obtain a precise evolutionary schedule. Did modern mammal groups coexist with dinosaurs, or did they appear after mass extinction? We now have a definitive answer.

Professor Donoghue from the School of Earth Sciences at the University of Bristol added: “The chronology of mammalian evolution is perhaps one of the most controversial topics in evolutionary biology. Early studies provided original estimates for modern groups deep in the Cretaceous Period, during the time of the dinosaurs. Over the past two decades, studies have oscillated between post-K-Pg and pre-K-Pg diversification scenarios. Our precise timetable fixes the problem.

With global sequencing projects now producing hundreds to thousands of genome sequences, and with imminent plans to sequencing more than a million species, evolutionary biologists will soon have a wealth of information at their disposal. arrangement. However, current methods for analyzing the large sets of genomic data available and creating evolutionary timelines are inefficient and computationally expensive.

Dr dos Reis said: “Deducing evolutionary chronologies is a fundamental goal of biology. However, state-of-the-art methods rely on the use of computers to simulate evolutionary timelines and assess the most plausible. In our case, this was difficult due to the gigantic dataset analyzed, involving genetic data from almost 5,000 species of mammals and 72 complete genomes.

In this study, the researchers developed a new, fast Bayesian approach to analyze a large number of genomic sequences, while taking into account uncertainties in the data.

Dr dos Reis added: “We solved the computational hurdles by dividing the analysis into substeps: first by simulating timelines using the 72 genomes, then using the results to guide simulations on the remaining species. . The use of genomes reduces the uncertainty because it allows to reject the implausible timelines of the simulations. “

Dr Asif Tamuri, co-lead author of the UCL paper, who was responsible for assembling the mammalian genomic dataset, said: “Our data processing pipeline generated so much data genomics for as many mammalian species as possible. This was difficult because the DNA databases contain inaccuracies and we had to develop a strategy to identify poor quality samples or mislabeled data that had to be deleted.

Thanks to their new approach, the team was able to reduce the computing time of this complex analysis from several decades to several months.

Dr Álvarez-Carretero added: “If we had tried to analyze this large mammal dataset in a supercomputer without using the Bayesian method we developed, we would have had to wait decades to derive the time tree. mammals. Imagine how long this scan could take if we were to use our own PCs.

“In addition, we have succeeded in reducing the computation time by a factor of 100. This new approach not only allows the analysis of genomic datasets, but also, by being more efficient, considerably reduces the CO2 emissions released from the system. does computer science.

The method developed in the study could be used to tackle other controversial evolutionary timelines that require the analysis of large data sets. By integrating the new Bayesian approach into future genomes of 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 Biosciences Research Council, UK.

Reference: Álvarez-Carretero S, Tamuri AU, Battini M, et al. A species-level chronology of mammalian evolution incorporating phylogenomic data. Nature. 2021. doi: 10.1038 / s41586-021-04341-1

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