Stepwise evolution of a butterfly supergene via duplication and inversion

ABSTRACTSupergenes maintain adaptive clusters of alleles in the face of genetic mixing. Although usually attributed to inversions, there are few cases in which the specific mechanisms of recombination suppression, and their timing, have been reconstructed in detail. We investigated the origin of the BC supergene, which controls variation in warning colouration in the African Monarch butterfly, Danaus chrysippus. By generating chromosome-scale assemblies for all three alleles, we identified multiple structural differences. Most strikingly, we find that a region of >1 million bp underwent several segmental duplications at least 7.5 million years ago. The resulting duplicated fragments appear to have triggered four inversions in surrounding parts of the chromosome, resulting in stepwise growth of the region of suppressed recombination. Phylogenies for the inversions are incongruent with the species tree, and suggest that structural polymorphisms have persisted for at least 4.1 million years. In addition to the role of duplications in triggering inversions, our results suggest a previously undescribed mechanism of recombination suppression through independent losses of divergent duplicated tracts. Overall, our findings challenge the idea of instantaneous supergene evolution through a single inversion event, instead pointing towards a stepwise process involving a variety of structural changes.

Stepwise Evolution of a Klebsiella pneumoniae Clone within a Host Leading to Increased Multidrug Resistance

Within-host evolution is a survival strategy that can occur in many pathogens and is often associated with the emergence of novel antimicrobial-resistant (AMR) bacteria. To analyze this process, suitable sets of clinical isolates are required.

Evolution of chlorophyll degradation is associated with plant transition to land

Colonization of land by green plants (Viridiplantae) some 500 million years ago was made possible by large metabolic and biochemical adaptations. Chlorophyll, the central pigment of photosynthesis, is highly photo-active. In order to mitigate deleterious effects of pigment accumulation, some plants have evolved a coordinated pathway to deal with chlorophyll degradation end-products, so-called phyllobilins. This pathway has been so far mostly unravelled in Arabidopsis thaliana. Here, large-scale comparative phylogenomic coupled to an innovative biochemical characterization strategy of phyllobilins allow a better understanding how such a pathway appeared in Viridiplantae. Our analysis reveals a stepwise evolution of the canonical pheophorbide a monooxygenase/phyllobilin pathway. It appears to have evolved gradually, first in chlorophyte’s chloroplasts, to ensure multicellularity by detoxifying chlorophyll catabolites, and in charophytes outside chloroplasts to allow adaptation of embryophytes to land. At least six out of the eight genes involved in the pathway were already present in the last common ancestor of green plants. This strongly suggests parallel evolution of distinct enzymes catalysing similar reactions in various lineages, particularly for the dephytylation step. Together, our study suggests that chlorophyll degradation accompanied the transition from water to land, and was therefore of great importance for plant diversification.

Stepwise Evolution and Exceptional Conservation of ORF1a/b Overlap in Coronaviruses

The programmed frameshift element (PFE) rerouting translation from ORF1a to ORF1b is essential for propagation of coronaviruses. The overlap between the two reading frames, a slippery sequence, and an ensemble of secondary structure elements places severe constraints on this region as most possible nucleotide substitution may disrupt one or more of these features. Here we performed a comparative analysis of all available coronaviral genomic data available to date to demonstrate exceptional conservation and detect signatures of selection within the PFE region.

Stepwise Evolution of Photocatalytic Spinel-Structured (Co,Cr,Fe,Mn,Ni)3O4 High Entropy Oxides from First-Principles Calculations to Machine Learning

High entropy oxides (HEOx) are novel materials, which increase the potential application in the fields of energy and catalysis. However, a series of HEOx is too novel to evaluate the synthesis properties, including formation and fundamental properties. Combining first-principles calculations with machine learning (ML) techniques, we predict the lattice constants and formation energies of spinel-structured photocatalytic HEOx, (Co,Cr,Fe,Mn,Ni)3O4, for stoichiometric and non-stoichiometric structures. The effects of site occupation by different metal cations in the spinel structure are obtained through first-principles calculations and ML predictions. Our predicted results show that the lattice constants of these spinel-structured oxides are composition-dependent and that the formation energies of those oxides containing Cr atoms are low. The computing time and computing energy can be greatly economized through the tandem approach of first-principles calculations and ML.

Stepwise evolution and exceptional conservation of ORF1a/b overlap in coronaviruses

The programmed frameshift element (PFE) rerouting translation from ORF1a to ORF1b is essential for propagation of coronaviruses. A combination of genomic features that make up PFE--the overlap between the two reading frames, a slippery sequence, as well as an ensemble of complex secondary structure elements--puts severe constraints on this region as most possible nucleotide substitution may disrupt one or more of these elements. The vast amount of SARS-CoV-2 sequencing data generated within the past year provides an opportunity to assess evolutionary dynamics of PFE in great detail. Here we performed a comparative analysis of all available coronaviral genomic data available to date. We show that the overlap between ORF1a and b evolved as a set of discrete 7, 16, 22, 25, and 31 nucleotide stretches with a well defined phylogenetic specificity. We further examined sequencing data from over 350,000 complete genomes and 55,000 raw read datasets to demonstrate exceptional conservation of the PFE region.

Stepwise Evolution of Photocatalytic Spinel-Structured (Co,Cr,Fe,Mn,Ni)3O4 High Entropy Oxides from First-Principles Calculations to Machine Learning

High entropy oxides (HEOx) are novel materials, which increase the potential application in the fields of energy and catalysis. However, a series of HEOx is too novel to evaluate the synthesis properties, including formation and fundamental properties. Combining first-principles calculations with machine learning (ML) techniques, we predict the lattice constants and formation energies of spinel-structured photocatalytic HEOx, (Co,Cr,Fe,Mn,Ni)3O4, for stoichiometric and non-stoichiometric structures. The effects of site occupation by different metal cations in the spinel structure are obtained through first-principles calculations and ML predictions. Our predicted results show that the lattice constants of these spinel-structured oxides are composition-dependent and that the formation energies of those oxides containing Cr atoms are low. The computing time and computing energy can be greatly economized through the tandem approach of first-principles calculations and ML.