The potential of family-free rearrangements towards gene orthology inference

Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, Algorithms Mol Biol 16:4, 2021] for exactly computing the rearrangement distance of two genomes in a family-free setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.

PaReBrick: PArallel REarrangements and BReaks identification toolkit

Motivation High plasticity of bacterial genomes is provided by numerous mechanisms including horizontal gene transfer and recombination via numerous flanking repeats. Genome rearrangements such as inversions, deletions, insertions, and duplications may independently occur in different strains, providing parallel adaptation or phenotypic diversity. Specifically, such rearrangements might be responsible for virulence, antibiotic resistance, and antigenic variation. However, identification of such events requires laborious manual inspection and verification of phyletic pattern consistency. Results Here we define the term “parallel rearrangements” as events that occur independently in phylogenetically distant bacterial strains and present a formalization of the problem of parallel rearrangements calling. We implement an algorithmic solution for the identification of parallel rearrangements in bacterial populations as a tool PaReBrick. The tool takes a collection of strains represented as a sequence of oriented synteny blocks and a phylogenetic tree as input data. It identifies rearrangements, tests them for consistency with a tree, and sorts the events by their parallelism score. The tool provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved.We demonstrated PaReBrick’s efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes. Availability PaReBrick is written in Python and is available on GitHub https://github.com/ctlab/parallelrearrangements Supplementary information Supplementary data are available at Bioinformatics online.

R-loops and regulatory changes in chronologically ageing fission yeast cells drive non-random patterns of genome rearrangements

Aberrant repair of DNA double-strand breaks can recombine distant chromosomal breakpoints. Chromosomal rearrangements compromise genome function and are a hallmark of ageing. Rearrangements are challenging to detect in non-dividing cell populations, because they reflect individually rare, heterogeneous events. The genomic distribution of de novo rearrangements in non-dividing cells, and their dynamics during ageing, remain therefore poorly characterized. Studies of genomic instability during ageing have focussed on mitochondrial DNA, small genetic variants, or proliferating cells. To characterize genome rearrangements during cellular ageing in non-dividing cells, we interrogated a single diagnostic measure, DNA breakpoint junctions, using Schizosaccharomyces pombe as a model system. Aberrant DNA junctions that accumulated with age were associated with microhomology sequences and R-loops. Global hotspots for age-associated breakpoint formation were evident near telomeric genes and linked to remote breakpoints elsewhere in the genome, including the mitochondrial chromosome. Formation of breakpoint junctions at global hotspots was inhibited by the Sir2 histone deacetylase and might be triggered by an age-dependent de-repression of chromatin silencing. An unexpected mechanism of genomic instability may cause more local hotspots: age-associated reduction in an RNA-binding protein triggering R-loops at target loci. This result suggests that biological processes other than transcription or replication can drive genome rearrangements. Notably, we detected similar signatures of genome rearrangements that accumulated in old brain cells of humans. These findings provide insights into the unique patterns and possible mechanisms of genome rearrangements in non-dividing cells, which can be promoted by ageing-related changes in gene-regulatory proteins.

Genome of the world’s smallest flowering plant, Wolffia australiana, helps explain its specialized physiology and unique morphology

Watermeal, Wolffia australiana, is the smallest known flowering monocot and is rich in protein. Despite its great potential as a biotech crop, basic research on Wolffia is in its infancy. Here, we generated the reference genome of a species of watermeal, W. australiana, and identified the genome-wide features that may contribute to its atypical anatomy and physiology, including the absence of roots, adaxial stomata development, and anaerobic life as a turion. In addition, we found evidence of extensive genome rearrangements that may underpin the specialized aquatic lifestyle of watermeal. Analysis of the gene inventory of this intriguing species helps explain the distinct characteristics of W. australiana and its unique evolutionary trajectory.

Shared and Unique Evolutionary Trajectories to Ciprofloxacin Resistance in Gram-Negative Bacterial Pathogens

The challenge of spreading antibiotic resistance calls for systematic efforts to develop more “irresistible” drugs based on a deeper understanding of dynamics and mechanisms of antibiotic resistance acquisition. To address this challenge, we have established a comparative resistomics approach which combines experimental evolution in a continuous-culturing device, the morbidostat, with ultradeep sequencing of evolving microbial populations to identify evolutionary trajectories (mutations and genome rearrangements) leading to antibiotic resistance over a range of target pathogens.

Characterization of gross genome rearrangements in Deinococcus radiodurans recA mutants

Genome stability in radioresistant bacterium Deinococcus radiodurans depends on RecA, the main bacterial recombinase. Without RecA, gross genome rearrangements occur during repair of DNA double-strand breaks. Long repeated (insertion) sequences have been identified as hot spots for ectopic recombination leading to genome rearrangements, and single-strand annealing (SSA) postulated to be the most likely mechanism involved in this process. Here, we have sequenced five isolates of D. radiodurans recA mutant carrying gross genome rearrangements to precisely characterize the rearrangements and to elucidate the underlying repair mechanism. The detected rearrangements consisted of large deletions in chromosome II in all the sequenced recA isolates. The mechanism behind these deletions clearly differs from the classical SSA; it utilized short (4–11 bp) repeats as opposed to insertion sequences or other long repeats. Moreover, it worked over larger linear DNA distances from those previously tested. Our data are most compatible with alternative end-joining, a recombination mechanism that operates in eukaryotes, but is also found in Escherichia coli. Additionally, despite the recA isolates being preselected for different rearrangement patterns, all identified deletions were found to overlap in a 35 kb genomic region. We weigh the evidence for mechanistic vs. adaptive reasons for this phenomenon.

PaReBrick: PArallel REarrangements and BReakpoints identification toolkit

Motivation: High plasticity of bacterial genomes is provided by numerous mechanisms including horizontal gene transfer and recombination via numerous flanking repeats. Genome rearrangements such as inversions, deletions, insertions, and duplications may independently occur in different strains, providing parallel adaptation. Specifically, such rearrangements might be responsible for multi-virulence, antibiotic resistance, and antigenic variation. However, identification of such events requires laborious manual inspection and verification of phyletic pattern consistency. Results: Here we define the term "parallel rearrangements" as events that occur independently in phylogenetically distant bacterial strains and present a formalization of the problem of parallel rearrangements calling. We implement an algorithmic solution for the identification of parallel rearrangements in bacterial population, as a tool PaReBrick. The tool takes synteny blocks and a phylogenetic tree as input and outputs rearrangement events. The tool tests each rearrangement for consistency with a tree, and sorts the events by their parallelism score and provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved. We proved PaReBrick's efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes. Availability: PaReBrick is written in Python and is available on GitHub: https://github.com/ctlab/parallel-rearrangements .

High Rates of Genome Rearrangements and Pathogenicity of Shigella spp.

Shigella are pathogens originating within the Escherichia lineage but frequently classified as a separate genus. Shigella genomes contain numerous insertion sequences (ISs) that lead to pseudogenisation of affected genes and an increase of non-homologous recombination. Here, we study 414 genomes of E. coli and Shigella strains to assess the contribution of genomic rearrangements to Shigella evolution. We found that Shigella experienced exceptionally high rates of intragenomic rearrangements and had a decreased rate of homologous recombination compared to pathogenic and non-pathogenic E. coli. The high rearrangement rate resulted in independent disruption of syntenic regions and parallel rearrangements in different Shigella lineages. Specifically, we identified two types of chromosomally encoded E3 ubiquitin-protein ligases acquired independently by all Shigella strains that also showed a high level of sequence conservation in the promoter and further in the 5′-intergenic region. In the only available enteroinvasive E. coli (EIEC) strain, which is a pathogenic E. coli with a phenotype intermediate between Shigella and non-pathogenic E. coli, we found a rate of genome rearrangements comparable to those in other E. coli and no functional copies of the two Shigella-specific E3 ubiquitin ligases. These data indicate that the accumulation of ISs influenced many aspects of genome evolution and played an important role in the evolution of intracellular pathogens. Our research demonstrates the power of comparative genomics-based on synteny block composition and an important role of non-coding regions in the evolution of genomic islands.