Biology subjects

Weber, C. C.

Publications and source records attributed to Weber, C. C..

6 recordsLinked to original sources

bioRxiv2025

Forty New Genomes Shed Light on Sexual Reproduction and the Origin of Tetraploidy in Microsporidia

Microsporidia are single-celled, obligately intracellular parasites with growing public health, agricultural, and economic importance. Despite this, Microsporidia remain relatively enigmatic, with many aspects of their biology and evolution unexplored. Key questions include whether Microsporidia undergo sexual reproduction, and the nature of the relationship between tetraploid and diploid lineages. While few high-quality microsporidian genomes currently exist to help answer such questions, large-scale biodiversity genomics initiatives, such as the Darwin Tree of Life project, can generate high-quality genome assemblies for microsporidian parasites when sequencing infected host species. Here, we present 40 new microsporidian genome assemblies from infected arthropod hosts that were sequenced to create reference genomes. Out of the 40, 32 are complete genomes, eight of which are chromosome-level, and eight are partial microsporidian genomes. We characterised 14 of these as polyploid and five as diploid. We found that tetraploid genome haplotypes are consistent with autopolyploidy, in that they coalesce more recently than species, and that they likely recombine. Within some genomes, we found large-scale rearrangements between the homeologous genomes. We also observed a high rate of rearrangement between genomes from different microsporidian groups, and a striking tolerance for segmental duplications. Analysis of chromatin conformation capture (Hi-C) data indicated that tetraploid genomes are likely organised into two diploid compartments, similar to dikaryotic cells in fungi, with evidence of recombination within and between compartments. Together, our results provide evidence for the existence of a sexual cycle in Microsporidia, and suggest a model for the microsporidian lifecycle that mirrors fungal reproduction.

genomics↗

bioRxiv2024

Kudoa genomes from contaminated hosts reveal extensive gene order conservation and rapid sequence evolution

Myxozoans are obligate endoparasites that belong to the phylum Cnidaria. Compared to their closest free-living relatives, they have evolved highly simplified body plans and reduced genomes. Kudoa iwatai, for example, has lost upwards of two thirds of genes thought to have been present in its ancestors. However, little is known about myxozoan genome architecture because of a lack of sufficiently contiguous genome assemblies. This work presents two new, near-chromosomal Kudoa genomes, built entirely from low-coverage long reads from infected fish samples. The results illustrate the potential of using unsupervised learning methods to disentangle sequences from different sources, and facilitate producing genomes from undersampled taxa. Extracting distinct components of chromatin interaction networks allows scaffolds from mixed samples to be assigned to their source genomes. Meanwhile, low-dimensional embeddings of read composition permit targeted assembly of potential parasite reads. Despite drastic changes in genome architecture in the lineage leading to Kudoa and considerable sequence divergence between the two genomes, gene order is highly conserved. Although parasitic cnidarians show rapid protein evolution compared to their free-living relatives, there is limited evidence of less efficient selection. While deleterious substitutions may become fixed at a higher rate, large evolutionary distances between species make robustly analysing patterns of molecular evolution challenging. These observations highlight the importance of filling in taxonomic gaps, to allow a comprehensive assessment of the impacts of parasitism on genome evolution.

genomics↗

bioRxiv2024

Disentangling Cobionts and Contamination in Long-Read Genomic Data using Sequence Composition

The recent acceleration in genome sequencing targeting previously unexplored parts of the tree of life presents computational challenges. Samples collected from the wild often contain sequences from several organisms, including the target, its cobionts, and contaminants. Effective methods are therefore needed to separate sequences. Though advances in sequencing technology make this task easier, it remains difficult to taxonomically assign sequences from eukaryotic taxa that are not well-represented in databases. Therefore, reference-based methods alone are insufficient. Here, I examine how we can take advantage of differences in sequence composition between organisms to identify symbionts, parasites and contaminants in samples, with minimal reliance on reference data. To this end, I explore data from the Darwin Tree of Life project, including hundreds of high-quality HiFi read sets from insects. Visualising two-dimensional representations of read tetranucleotide composition learned by a Variational Autoencoder can reveal distinct components of a sample. Annotating the embeddings with additional information, such as coding density, estimated coverage, or taxonomic labels allows rapid assessment of the contents of a dataset. The approach scales to millions of sequences, making it possible to explore unassembled read sets, even for large genomes. Combined with interactive visualisation tools, it allows a large fraction of cobionts reported by reference-based screening to be identified. Crucially, it also facilitates retrieving genomes for which suitable reference data are absent.

bioinformatics↗

bioRxiv2019

Ambiguity coding allows accurate inference of evolutionary parameters from alignments in an aggregated state-space

How can we best learn the history of a proteins evolution? Ideally, a model of sequence evolution should capture both the process that generates genetic variation and the functional constraints determining which changes are fixed. However, in practical terms the most suitable approach may simply be the one that combines the convenience of easily available input data with the ability to return useful parameter estimates. For example, we might be interested in a measure of the strength of selection (typically obtained using a codon model) or an ancestral structure (obtained using structural modelling based on inferred amino acid sequence and side chain configuration).\n\nBut what if data in the relevant state-space are not readily available? We show that it is possible to obtain accurate estimates of the outputs of interest using an established method for handling missing data. Encoding observed characters in an alignment as ambiguous representations of characters in a larger state-space allows the application of models with the desired features to data that lack the resolution that is normally required. This strategy is viable because the evolutionary path taken through the observed space contains information about states that were likely visited in the \"unseen\" state-space. To illustrate this, we consider two examples with amino acid sequences as input.\n\nWe show that{omega} , a parameter describing the relative strength of selection on non-synonymous and synonymous changes, can be estimated in an unbiased manner using an adapted version of a standard 61-state codon model. Using simulated and empirical data, we find that ancestral amino acid side chain configuration can be inferred by applying a 55-state empirical model to 20-state amino acid data. Where feasible, combining inputs from both ambiguity-coded and fully resolved data improves accuracy. Adding structural information to as few as 12.5% of the sequences in an amino acid alignment results in remarkable ancestral reconstruction performance compared to a benchmark that considers the full rotamer state information. These examples show that our methods permit the recovery of evolutionary information from sequences where it has previously been inaccessible.

evolutionary biology↗

bioRxiv2018

Physicochemical amino acid properties better describe substitution rates in large populations

Substitutions between chemically distant amino acids are known to occur less frequently than those between more similar amino acids. This knowledge, however, is not reflected in most codon substitution models, which treat all non-synonymous changes as if they were equivalent in terms of impact on the protein. A variety of methods for integrating chemical distances into models have been proposed, with a common approach being to divide substitutions into radical or conservative categories. Nevertheless, it remains unclear whether the resulting models describe sequence evolution better than their simpler counterparts.\n\nWe propose a parametric codon model that distinguishes between radical and conservative substitutions, allowing us to assess if radical substitutions are preferentially removed by selection. Applying our new model to a range of phylogenomic data, we find differentiating between radical and conservative substitutions provides significantly better fit for large populations, but see no equivalent improvement for smaller populations. Comparing codon- and amino acid models using these same data shows that alignments from large populations tend to select phylogenetic models containing information about amino acid exchangeabilities, whereas the structure of the genetic code is more important for smaller populations.\n\nOur results suggest selection against radical substitutions is, on average, more pronounced in large populations than smaller ones. The reduced observable effect of selection in smaller populations may be due to stronger genetic drift making it more challenging to detect preferences. Our results imply an important connection between the life history of a phylogenetic group and the model that best describes its evolution.

evolutionary biology↗

bioRxiv2017

Protein Evolution Depends On Multiple Distinct Population Size Parameters

That population size affects the fate of new mutations arising in genomes, modulating both how frequently they arise and how efficiently natural selection is able to filter them, is well established. It is therefore clear that these distinct roles for population size that characterize different processes should affect the evolution of proteins and need to be carefully defined. Empirical evidence is consistent with a role for demography in influencing protein evolution, supporting the idea that functional constraints alone do not determine the composition of coding sequences.\n\nGiven that the relationship between population size, mutant fitness and fixation probability has been well characterized, estimating fitness from observed substitutions is well within reach with well-formulated models. Molecular evolution research has, therefore, increasingly begun to leverage concepts from population genetics to quantify the selective effects associated with different classes of mutation. However, in order for this type of analysis to provide meaningful information about the intra- and inter-specific evolution of coding sequences, a clear definition of concepts of population size, what they influence, and how they are best parameterized is essential.\n\nHere, we present an overview of the many distinct concepts that \"population size\" and \"effective population size\" may refer to, what they represent for studying proteins, and how this knowledge can be harnessed to produce better specified models of protein evolution.

evolutionary biology↗