Phylodynamic models can be used to estimate diversification trajectories from time-calibrated phylogenies. Here we apply two such models to phylogenies of non-avian dinosaurs, a clade whose evolutionary history has been widely debated. Although some authors have suggested that the clade experienced a decline in diversity, potentially starting millions of years before the end-Cretaceous mass extinction, others have suggested that the group remained highly diverse right up until the Cretaceous-Paleogene (K-Pg) boundary. Our results show that model assumptions, likely with respect to incomplete sampling, have a large impact on whether dinosaurs appear to have experienced a long-term decline or not. The results are also highly sensitive to the topology and branch lengths of the phylogeny used. Developing comprehensive models of sampling bias, and building larger and more accurate phylogenies, are likely to be necessary steps for us to determine whether dinosaur diversity was or was not in decline before the end-Cretaceous mass extinction.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895757PMC
http://dx.doi.org/10.1017/ext.2024.5DOI Listing

Publication Analysis

Top Keywords

phylodynamic models
8
non-avian dinosaurs
8
end-cretaceous mass
8
mass extinction
8
mechanistic phylodynamic
4
models
4
models provide
4
provide conclusive
4
conclusive evidence
4
evidence non-avian
4

Similar Publications

Phylodynamic models can be used to estimate diversification trajectories from time-calibrated phylogenies. Here we apply two such models to phylogenies of non-avian dinosaurs, a clade whose evolutionary history has been widely debated. Although some authors have suggested that the clade experienced a decline in diversity, potentially starting millions of years before the end-Cretaceous mass extinction, others have suggested that the group remained highly diverse right up until the Cretaceous-Paleogene (K-Pg) boundary.

View Article and Find Full Text PDF

The importance of genomic surveillance strategies for pathogens has been particularly evident during the coronavirus disease 2019 (COVID-19) pandemic, as genomic data from the causative agent, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), have guided public health decisions worldwide. Bayesian phylodynamic inference, integrating epidemiology and evolutionary biology, has become an essential tool in genomic epidemiological surveillance. It enables the estimation of epidemiological parameters, such as the reproductive number, from pathogen sequence data alone.

View Article and Find Full Text PDF

Molecular Evolution of the () Genes in Human Parainfluenza Virus Type 2.

Microorganisms

February 2025

Advanced Medical Science Research Center, Gunma Paz University, Takasaki-shi 370-0006, Gunma, Japan.

Human parainfluenza virus type 2 (HPIV2) is a clinically significant respiratory pathogen, which highlights the necessity of studies on its molecular evolution. This study investigated the evolutionary dynamics, phylodynamics, and structural characteristics of the HPIV2 fusion () gene using a comprehensive dataset spanning multiple decades and geographic regions. Phylogenetic analyses revealed two distinct clusters of HPIV2 gene sequences, which were estimated to have diverged from a common ancestor approximately a century ago.

View Article and Find Full Text PDF

Phylodynamics beyond neutrality: the impact of incomplete purifying selection on viral phylogenies and inference.

Philos Trans R Soc Lond B Biol Sci

February 2025

Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC 27607, USA.

Viral phylodynamics focuses on using sequence data to make inferences about the population dynamics of viral diseases. These inferences commonly include estimation of growth rates, reproduction numbers and times of most recent common ancestor. With few exceptions, existing phylodynamic inference approaches assume that all observed and ancestral viral genetic variation is fitness-neutral.

View Article and Find Full Text PDF

A Bayesian phylodynamic inference framework for single-cell CRISPR/Cas9 lineage tracing barcode data with dependent target sites.

Philos Trans R Soc Lond B Biol Sci

February 2025

Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland.

Analysing single-cell lineage relationships of an organism is crucial towards understanding the fundamental cellular dynamics that drive development. Clustered regularly interspaced short palindromic repeats (CRISPR)-based dynamic lineage tracing relies on recent advances in genome editing and sequencing technologies to generate inheritable, evolving genetic barcode sequences that enable reconstruction of such cell lineage trees, also referred to as phylogenetic trees. Recent work generated custom computational strategies to produce robust tree estimates from such data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!