Biology subjects

Schrempf, D.

Publications and source records attributed to Schrempf, D..

9 recordsLinked to original sources

bioRxiv2023

An evolutionary timescale for Bacteria calibrated using the Great Oxidation Event

Most of lifes diversity and history is microbial but it has left a meagre fossil record, greatly hindering understanding of evolution in deep time. However, the co-evolution of life and the Earth system has left signatures of bacterial metabolism in the geochemical record, most conspicuously the Great Oxidation Event (GOE) [~]2.33 billion years ago (Ga, (Poulton et al. 2021)), in which oxygenic photosynthesis and tectonism (Eguchi, Seales, and Dasgupta 2019) transformed Earths biosphere from dominantly anaerobic to aerobic. Here, we combine machine learning and phylogenetic reconciliation to infer ancestral transitions to aerobic lifestyles during bacterial evolution. Linking these transitions to the GOE provides new constraints to infer the timetree of Bacteria. We find that extant bacterial phyla are truly ancient, having radiated in the Archaean and the Proterozoic: the oldest include Bacillota (Firmicutes), which radiated 3.1-3.7 Ga, Cyanobacteria (3.3-3.5 Ga) and Patescibacteria (3-3.5 Ga). We show that most bacterial phyla were ancestrally anaerobic and that most transitions to an aerobic lifestyle post-dated the GOE. Our analyses trace oxygen production and consumption back to Cyanobacteria. From that starting point, horizontal transfer seeded aerobic lifestyles across bacterial diversity over hundreds of millions of years. Our analyses demonstrate that the diversification of aerobes proceeded in two waves corresponding to the GOE and to a second sustained rise in atmospheric O2 at the dawn of the Palezoic (Krause et al. 2022).

evolutionary biology↗

bioRxiv2023

ATP synthase evolution on a cross-braced dated tree of life

The timing of early cellular evolution from the divergence of Archaea and Bacteria to the origin of eukaryotes remains poorly constrained. The ATP synthase complex is thought to have originated prior to the Last Universal Common Ancestor (LUCA) and analyses of ATP synthase genes, together with ribosomes, have played a key role in inferring and rooting the tree of life. Here we reconstruct the evolutionary history of ATP synthases using an expanded sampling of Archaea, Bacteria, and eukaryotes. We developed a phylogenetic cross-bracing approach making use of endosymbioses and ancient gene duplications of the major ATP synthase subunits to infer a highly resolved, dated species tree and establish an absolute timeline for ATP synthase evolution. Our analyses show that the divergence of the ATP synthase into F- and A/V-type lineages, was a very early event in cellular evolution dating back to more than 4Ga potentially predating the diversification of Archaea and Bacteria. Our cross-braced, dated tree of life also provides insight into more recent evolutionary transitions including eukaryogenesis, showing that the eukaryotic nuclear and mitochondrial lineages diverged from their closest archaeal (2.67-2.19Ga) and bacterial (2.58-2.12Ga) relatives at roughly the same time, with the nuclear stem being moderately longer.

evolutionary biology↗

bioRxiv2022

Compositionally constrained sites drive long branch attraction

AO_SCPLOWBSTRACTC_SCPLOWAccurate phylogenies are fundamental to our understanding of the pattern and process of evolution. Yet, phylogenies at deep evolutionary timescales, with correspondingly long branches, have been fraught with controversy resulting from conflicting estimates from models with varying complexity and goodness of fit. Analyses of historical as well as current empirical datasets, such as alignments including Microsporidia, Nematoda or Platyhelminthes, have demonstrated that inadequate modeling of across-site compositional heterogeneity, which is the result of biochemical constraints that lead to varying patterns of accepted amino acids along sequences, can lead to erroneous topologies that are strongly supported. Unfortunately, models that adequately account for across-site compositional heterogeneity remain computationally challenging or intractable for an increasing fraction of contemporary datasets. Here, we introduce "compositional constraint analysis", a method to investigate the effect of site-specific constraints on amino acid composition on phylogenetic inference. We show that more constrained sites with lower diversity and less constrained sites with higher diversity exhibit ostensibly conflicting signal under models ignoring across-site compositional heterogeneity that lead to long branch attraction artifacts and demonstrate that more complex models accounting for across-site compositional heterogeneity can ameliorate this bias. We present CAT-PMSF, a pipeline for diagnosing and resolving phylogenetic bias resulting from inadequate modeling of across-site compositional heterogeneity based on the CAT model. CAT-PMSF is robust against long branch attraction in all alignments we have examined. We suggest using CAT-PMSF when convergence of the CAT model cannot be assured. We find evidence that compositionally constrained sites are driving long branch attraction in two metazoan datasets and recover evidence for Porifera as the sister group to all other animals.

evolutionary biology↗

bioRxiv2021

Divergent evolutionary trajectories of bryophytes and tracheophytes from a complex common ancestor of land plants

The origin of plants and their colonization of land resulted in the transformation of the terrestrial environment. Here we investigate the evolution of the land plants (embryophytes) and their two main lineages, the tracheophytes (vascular plants) and bryophytes (non-vascular plants). We used new fossil calibrations, relative lineage dating implied by horizontal gene transfer, and new phylogenomic methods for mapping gene family origins. Distinct rooting strategies resolve tracheophytes and bryophytes as monophyletic sister groups that diverged during the Cambrian, 515-494 Ma. The embryophyte stem is characterised by a burst of gene innovation, while bryophytes subsequently experienced a no less dramatic episode of reductive genome evolution in which they lost genes associated with the elaboration of vasculature and the stomatal complex. Overall, our analyses confirm that extant tracheophytes and bryophytes are both highly derived; as a result, understanding the origin of land plants requires tracing character evolution across the diversity of modern lineages.

evolutionary biology↗

bioRxiv2021

Simultaneous estimation of per cell division mutation rate and turnover rate from bulk tumour sequence data

Tumors often harbor orders of magnitude more mutations than healthy tissues. The increased number of mutations may be due to an elevated mutation rate or frequent cell death and correspondingly rapid cell turnover, or a combination of the two. It is difficult to disentangle these two mechanisms based on widely available bulk sequencing data, where sequences from individual cells are intermixed and, thus, the cell lineage tree of the tumor cannot be resolved. Here we present a method that can simultaneously estimate the cell turnover rate and the rate of mutations from bulk sequencing data. Our method works by simulating tumor growth and finding the parameters with which the observed data can be reproduced with maximum likelihood. Applying this method to a real tumor sample, we find that both the mutation rate and the frequency of death may be high. Author SummaryTumors frequently harbor an elevated number of mutations, compared to healthy tissue. These extra mutations may be generated either by an increased mutation rate or the presence of cell death resulting in increased cellular turnover and additional cell divisions for tumor growth. Separating the effects of these two factors is a nontrivial problem. Here we present a method which can simultaneously estimate cell turnover rate and genomic mutation rate from bulk sequencing data. Our method is based on the estimation of the parameters of a generative model of tumor growth and mutations. Applying our method to a human hepatocellular carcinoma sample reveals an elevated per cell division mutation rate and high cell turnover.

bioinformatics↗

bioRxiv2020

Relative time constraints improve molecular dating

Dating the tree of life is central to understanding the evolution of life on Earth. Molecular clocks calibrated with fossils represent the state of the art for inferring the ages of major groups. Yet, other information on the timing of species diversification can be used to date the tree of life. For example, horizontal gene transfer events and ancient coevolutionary relationships such as (endo)symbioses can imply temporal relationships between two nodes in a phylogeny (Davin et al. 2018). These alternative sources of temporal constraints can be particularly helpful when the geological record is sparse, e.g. for microorganisms, which represent the vast majority of extant and extinct biodiversity. Here, we present a new method to combine fossil calibrations and relative age constraints to estimate chronograms. We provide an implementation of relative age constraints in RevBayes (Hohna et al. 2016) that can be combined in a modular manner with the wide range of molecular dating methods available in the software. We use both realistic simulations and empirical datasets of 40 Cyanobacteria and 62 Archaea to evaluate our method. We show that the combination of relative age constraints with fossil calibrations significantly improves the estimation of node ages.

evolutionary biology↗

bioRxiv2019

IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era

IQ-TREE (http://www.iqtree.org) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

evolutionary biology↗

bioRxiv2019

Scalable empirical mixture models that account for across-site compositional heterogeneity

Biochemical demands constrain the range of amino acids acceptable at specific sites resulting in across-site compositional heterogeneity of the amino acid replacement process. Phylogenetic models that disregard this heterogeneity are prone to systematic errors, which can lead to severe long branch attraction artifacts. State-of-the-art models accounting for across-site compositional heterogeneity include the CAT model, which is computationally expensive, and empirical distribution mixture models estimated via maximum likelihood (C10 to C60 models). Here, we present a new, scalable method EDCluster for finding empirical distribution mixture models involving a simple cluster analysis. The cluster analysis utilizes specific coordinate transformations which allow the detection of specialized amino acid distributions either from curated databases, or from the alignment at hand. We apply EDCluster to the HOGENOM and HSSP databases in order to provide universal distribution mixture (UDM) models comprising up to 4096 components. Detailed analyses of the UDM models demonstrate the removal of various long branch attraction artifacts and improved performance compared to the C10 to C60 models. Ready-to-use implementations of the UDM models are provided for three established software packages (IQ-TREE, Phylobayes, and RevBayes).

bioinformatics↗

bioRxiv2018

Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity

Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data while accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also provide bmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.

bioinformatics↗