系统基因组学
进化生物学
生物
哺乳动物
贝叶斯概率
克莱德
时间轴
超级矩阵
系统发育树
多元化(营销策略)
计算生物学
古生物学
计算机科学
地理
基因
遗传学
人工智能
仿射李代数
纯数学
考古
营销
业务
域代数上的
数学
当前代数
作者
Sandra Álvarez-Carretero,Asif U. Tamuri,Matteo Battini,Fabrícia F. Nascimento,Emily Carlisle,Robert J. Asher,Ziheng Yang,Philip C. J. Donoghue,Mario dos Reis
出处
期刊:Nature
[Springer Nature]
日期:2021-12-22
卷期号:602 (7896): 263-267
被引量:119
标识
DOI:10.1038/s41586-021-04341-1
摘要
High-throughput sequencing projects generate genome-scale sequence data for species-level phylogenies1-3. However, state-of-the-art Bayesian methods for inferring timetrees are computationally limited to small datasets and cannot exploit the growing number of available genomes4. In the case of mammals, molecular-clock analyses of limited datasets have produced conflicting estimates of clade ages with large uncertainties5,6, and thus the timescale of placental mammal evolution remains contentious7-10. Here we develop a Bayesian molecular-clock dating approach to estimate a timetree of 4,705 mammal species integrating information from 72 mammal genomes. We show that increasingly larger phylogenomic datasets produce diversification time estimates with progressively smaller uncertainties, facilitating precise tests of macroevolutionary hypotheses. For example, we confidently reject an explosive model of placental mammal origination in the Palaeogene8 and show that crown Placentalia originated in the Late Cretaceous with unambiguous ordinal diversification in the Palaeocene/Eocene. Our Bayesian methodology facilitates analysis of complete genomes and thousands of species within an integrated framework, making it possible to address hitherto intractable research questions on species diversifications. This approach can be used to address other contentious cases of animal and plant diversifications that require analysis of species-level phylogenomic datasets.
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