Biology subjects

Conradsen, C.

Publications and source records attributed to Conradsen, C..

3 recordsLinked to original sources

bioRxiv2026

A simple test demonstrates that many prokaryotic accessory genes are adaptive.

Bacterial genomes often contain many genes that are only present in a subset of strains, the so-called accessory genes. Whether these genes are adaptive, neutral or deleterious remains contentious. Here we introduce a simple test to differentiate between these possibilities. If an accessory gene is adaptive then the sequence of the gene should be conserved, and the ratio of non-synonymous to synonymous diversity,{pi} n/{pi}s, should be less than one. In contrast, if the gene is neutral or deleterious, selection should not conserve the gene sequence, and{pi} n/{pi}s should equal one. We apply this test to accessory genes in Escherichia coli and Staphylococcus aureus, two highly divergent bacterial species with a large and a small pangenome respectively. We find{pi} n/{pi}s<1 for genes at all frequencies in both species demonstrating that many are adaptive. We estimate that at least 75% of all the accessory genes are maintained by selection in the two species that we have analysed, equating to thousands of adaptive accessory genes in both species, a substantial increase on previous estimates. Significance statementMany bacterial genes are found in only a subset of the strains of a bacterial species. These are referred to as accessory genes. Whether, accessory genes are adaptive, allowing certain strains to inhabit particular niches, remains a highly contentious question. In this paper we introduce a simple test of whether accessory genes are adaptive and show that >75% of them are, in two highly divergent bacterial species. This radically alters our view of this type of genetic variation and bacterial evolution.

evolutionary biology↗

bioRxiv2025

Identification of multivariate phenotypes most influenced by mutation: Drosophila serrata wings as a case study

The distribution of pleiotropic mutational effects impacts phenotypic adaptation. However, small effect sizes and high sampling error of covariances hinder investigations of the factors influencing this distribution. Here, we explored the potential for shared information across traits affected by the same mutations to counter sampling error, allowing robust characterisation of patterns of mutational input. Exploiting a published dataset representing 12 samples of the same mutation accumulation experiment in Drosophila serrata, we inferred robust signals of mutational effects from the concordance across samples. Krzanowski common subspace analysis identified a multivariate wing trait with statistically supported mutational variance in all samples. Importantly, this multivariate trait was aligned with the major axis of among-line (mutational) variance within most population samples. That is, despite considerable heterogeneity among samples in individual (co)variance parameter estimates, the predominant pattern of correlated mutational effects was identified in datasets reflecting a typical mutation accumulation experimental design. Two other multivariate traits were statistically supported across most samples. Smaller effect sizes (lower mutational variance) with concomitant larger sampling error or other factors (e.g., microenvironmental dependence of effects) may reduce the robustness of estimated mutational input for these traits. Overall, our results suggest sampling error does not preclude multivariate analyses of mutation accumulation experiments from extending our knowledge of pleiotropic mutational effects.

genetics↗

bioRxiv2021

Causes of variability in estimates of mutational variance from mutation accumulation experiments

Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardised estimates of this mutational variance, VM, span two orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using two approaches. First, meta-analyses of ~150 estimates from 37 mutation accumulation (MA) studies did not support a difference among taxa (which differ in mutation rate) in standardised VM, but provided equivocal support for standardised VM to vary with trait type (life history versus morphology, predicted to differ in mutation rate). Notably, several experimental factors were confounded with taxon and trait, and further empirical data are required to resolve their influences. Second, we analysed morphological data from an experiment in Drosophila serrata to determine the potential for unintentional heterogeneity among environments in which phenotypes were measured (i.e., among laboratories or time points) or transient segregation of mutations within MA lines to affect standardised VM. Approximating the size of an average MA experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardised VM for morphological traits. This heterogeneity was (partially) attributable to unintended environmental variation or within line segregation of mutations only for wing size, not wing shape traits. We conclude that sampling error contributed substantial variation within this experiment, and infer that it will also contribute substantially to differences among published estimates. We suggest a logistically permissive approach to improve the precision of estimates, and consequently our understanding of the dynamics of mutational variance of quantitative traits.

genetics↗