Scientists have proposed a new method of computing evolutionary trees that can quickly obtain accurate dates

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5ce9463b4840dd4 - Scientists have proposed a new method of computing evolutionary trees that can quickly obtain accurate dates

it is reported that the mass extinction wiped out more than 70% of species, including all dinosaurs

these findings confirm that the ancestors of the modern placental mammalian population were after the k-pg extinction 66 million years ago, which solves the controversy about the origin of modern mammals. Placental mammals are the most diverse group of existing mammals, including primates, rodents, cetaceans, carnivores, Chiroptera (bats) and humans

the research group is led by Dr. Mario DOS Reis (Queen Mary College, University of London) and Professor Phil Donoghue (University of Bristol). The members include scientists from Queen Mary College, Bristol University, University of London, Imperial College London and Cambridge University

Dr. Sandra Á lvarez Carretero, the first author of the paper from UCL (then at Queen Mary University), said: “By integrating the complete genome and necessary fossil information in the analysis, we can reduce uncertainty and obtain a precise evolutionary timetable. Do modern mammalian populations coexist with dinosaurs or originated after the mass extinction? We now have a clear answer.”

“the time line of mammalian evolution is perhaps one of the most controversial topics in evolutionary biology. Early research has provided an estimate of the origin of modern viviparous fauna in the deep Cretaceous and dinosaur era. In the past 20 years, research has shuttled back and forth between post-k-pg and pre-k-pg diversification schemes,” added Professor Donoghue, co-first author of this paper, “Our precise timetable solves this problem.”

rapid method of genome analysis

with the worldwide sequencing projects now producing hundreds of genome sequences and planning to sequence more than one million species, evolutionary biologists will soon have a lot of information in their hands. However, the current methods of analyzing the existing huge genome data sets and creating evolutionary schedules are inefficient and computationally expensive

“inferring the evolutionary timeline is a basic goal of biology. However, the most advanced methods rely on using computers to simulate the evolutionary timeline and evaluate the most reasonable timeline. In our case, it is difficult to analyze the huge data set, involving the genetic data of nearly 5000 mammalian species and 72 complete genomes,” said Dr. DOS Reis

in this study, researchers developed a new and fast Bayesian method to analyze a large number of genome sequences, taking into account the uncertainty in the data. “We solve the computational barrier by dividing the analysis into sub steps: first use 72 genomes to simulate the timeline, and then use the results to guide the simulation of other species,” Dr. DOS Reis pointed out. “Using the genome can reduce uncertainty because it can reject unreliable timelines from the simulation.”

“our data processing pipeline obtains as much genomic data as possible for as many mammalian species. This is very challenging, because the gene database contains inaccurate content, we must develop a strategy to identify poor quality samples or wrong label data that must be deleted,” added Dr. Asif tamuri, co-author of the paper from UCL. It is reported that he is responsible for assembling mammalian genome data sets

through this new method, the research team can reduce the calculation time of this complex analysis from decades to a few months. “If we try to analyze this large mammalian data set in a supercomputer without using the Bayesian method we have developed, we will have to wait decades to infer the mammalian time tree,” said Á lvarez Carretero, “Imagine how long this analysis might take if we used our own personal computers. In addition, we managed to reduce the calculation time by 100 times. This new method can not only analyze genomic data sets, but also greatly reduce the carbon dioxide emissions due to calculation due to higher efficiency.”

it is reported that the method developed in this study can be used to solve other controversial evolutionary timelines that need to analyze large data sets. By combining the novel Bayesian method with the genome of the upcoming Darwin tree of life and earth biogenome projects, the idea of estimating a reliable evolutionary time scale for the life tree now seems to be achievable