英国伦敦玛丽女王大学 Mario dos Reis 和英国布里斯托大学 Philip C. J. Donoghue 共同合作取得了重要的突破。他们开发了整合系统基因组数据的哺乳动物进化物种级时间线的方法。相关研究成果于2021年12月22日发表在《自然》杂志上。

在这里，研究人员开发了一种贝叶斯分子时钟法（Bayesian molecular-clock dating approach），整合来自 72 种哺乳动物的基因组信息，估计了 4705 种哺乳动物的时间树。他们的方法展示了越来越大的系统发育基因组数据集产生了越来越小的不确定性的时间估计，促进了宏观进化假说的精确检验。例如，研究人员自信地推翻了起源于古近纪的胎盘哺乳动物的爆炸性模型，并表明冠胎盘起源于晚白垩世，在古新世/始新世具有明确的序数多样化。他们新的贝叶斯方法有助于在一个综合的框架内分析完整基因组和数千个物种，从而可以解决迄今为止关于物种多样化的棘手研究问题。他们的方法可以用来处理其他需要分析物种水平的植物体基因组数据的动植物多样性的争议案例。

据了解，高通量测序项目已经为物种水平的系统发育提供了基因组规模的序列数据。然而，用于推断时间树的最先进的贝叶斯方法 （Bayesian methods）在计算上局限于小数据集，无法利用大量的新基因组。就哺乳动物而言，对有限数据集的分子时钟分析（molecular-clock analysis）产生了对分支年龄相互矛盾的估计，具有很大的不确定性，因此，胎盘哺乳动物进化的时间线目前仍然存在争议。

附：英文原文

Title: A Species-Level Timeline of Mammal Evolution Integrating Phylogenomic Data

Author: lvarez-Carretero, Sandra, Tamuri, Asif U., Battini, Matteo, Nascimento, Fabrcia F., Carlisle, Emily, Asher, Robert J., Yang, Ziheng, Donoghue, Philip C. J., dos Reis, Mario

Issue&Volume: 2021-12-22

Abstract: 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 deluge of new 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 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 Paleogene8 and show crown Placentalia originated in the Late Cretaceous with unambiguous ordinal diversification in the Paleocene/Eocene. Our new 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. As such, our approach can be used to tackle other contentious cases of animal and plant diversifications that require analysis of species-level phylogenomic datasets.

DOI: 10.1038/s41586-021-04341-1

Source: https://www.nature.com/articles/s41586-021-04341-1