Live-cell chromosome dynamics in Arabidopsis thaliana reveals increased chromatin mobility in response to DNA damage

Double-strand breaks (DSBs) are a particularly deleterious type of DNA damage potentially leading to translocations and genome instability. Homologous recombination (HR) is a conservative repair pathway in which intact homologous sequences are used as a template for repair. How damaged DNA molecules search for homologous sequences in the crowded space of the cell nucleus is, however, still poorly understood, especially in plants. Here, we measured global chromosome and DSB site mobility, in Arabidopsis thaliana, by tracking the motion of specific loci using the lacO/LacI tagging system and two GFP-tagged HR regulators, RAD51 and RAD54. We observed an increase in chromatin mobility upon the induction of DNA damage, specifically at the S/G2 phases of the cell cycle. Importantly, this increase in mobility was lost on sog1-1 mutant, a central transcription factor of the DNA damage response (DDR), indicating that repair mechanisms actively regulate chromatin mobility upon DNA damage. Interestingly, we observed that DSB sites show remarkably high mobility levels at the early HR stage. Subsequently, a drastic decrease of DSB mobility is observed, which seems to be associated to the relocation of DSBs to the nucleus periphery. Altogether, our data suggest that changes in chromatin mobility are triggered in response to DNA damage, and that this may act as a mechanism to enhance the physical search within the nuclear space to locate a homologous template during homology-directed DNA repair.

Improving the Genome Annotation of Rhizoctonia solani Using Proteogenomics

Background: Rhizoctonia solani is a pathogenic fungus that causes serious diseases in many crops, including rice, wheat, and soybeans. In crop production, it is very important to understand the pathogenicity of this fungus, which is still elusive. It might be helpful to comprehensively understand its genomic information using different genome annotation strategies. Methods: Aiming to improve the genome annotation of R. solani, we performed a proteogenomic study based on the existing data. Based on our study, a total of 1060 newly identified genes, 36 revised genes, 139 single amino acid variants (SAAVs), 8 alternative splicing genes, and diverse post-translational modifications (PTMs) events were identified in R. solani AG3. Further functional annotation on these 1060 newly identified genes was performed through homology analysis with its 5 closest relative fungi. Results: Based on this, 2 novel candidate pathogenic genes, which might be associated with pathogen-host interaction, were discovered. In addition, in order to increase the reliability and novelty of the newly identified genes in R. solani AG3, 1060 newly identified genes were compared with the newly published available R. solani genome sequences of AG1, AG2, AG4, AG5, AG6, and AG8. There are 490 homologous sequences. We combined the proteogenomic results with the genome alignment results and finally identified 570 novel genes in R. solani. Conclusion: These findings extended R. solani genome annotation and provided a wealth of resources for research on R. solani.

Quantitative modeling of fine-scale variations in the Arabidopsis thaliana crossover landscape

In essentially all species where meiotic crossovers have been studied, they occur preferentially in open chromatin, typically near gene promoters and to a lesser extent at the end of genes. Here, in the case of Arabidopsis thaliana, we unveil further trends arising when one considers contextual information, namely summarized epigenetic status, size of underlying genomic regions and degree of divergence between homologs. For instance we find that intergenic recombination rate is reduced if those regions are less than 1.5 kb in size. Furthermore, we propose that the presence of single nucleotide polymorphisms is a factor driving enhanced crossover rate compared to when homologous sequences are identical, in agreement with previous works comparing rates in homozygous and heterozygous blocks. Lastly, by integrating these different factors, we produce a quantitative and predictive model of the recombination landscape that reproduces much of the experimental variation.

Improved prediction of protein-protein interactions using AlphaFold2

Predicting the structure of interacting protein chains is fundamental for understanding the function of proteins. Here, we examine the use of AlphaFold2 (AF2) for predicting the structure of heterodimeric protein complexes. We find that using the default AF2 protocol, 44% of the models in a test set can be predicted accurately. However, by optimising the multiple sequence alignment, we can increase the accuracy to 59%. In comparison, the alternative fold-and-dock method RoseTTAFold is only successful in 10% of the cases on this set, template-based docking 35% and traditional docking methods 22%. We can distinguish acceptable (DockQ>0.23) from incorrect models with an AUC of 0.85 on the test set by analysing the predicted interfaces. The success is higher for bacterial protein pairs, pairs with large interaction areas consisting of helices or sheets, and many homologous sequences. Further, we test the possibility to distinguish interacting from non-interacting proteins and find that by analysing the predicted interfaces, we can separate truly interacting from non-interacting proteins with an AUC of 0.82 in the ROC curve, compared to 0.76 with a recently published method. In addition, when using a more realistic negative set, including mammalian proteins, the identification rate remains (AUC=0.83), resulting in that 27% of interactions can be identified at a 1% FPR. All scripts and tools to run our protocol are freely available at: https://gitlab.com/ElofssonLab/FoldDock.

Beyond the reach of homology: successive computational filters find yeast pheromone genes

The mating of fungi depends on pheromones that mediate communication between two mating types. Most species use short peptides as pheromones, which are either unmodified (e.g., α-factor in Saccharomyces cerevisiae) or C-terminally farnesylated (e.g., a-factor in S. cerevisiae). Peptide pheromones have been found by genetics or biochemistry in small number of fungi, but their short sequences and modest conservation make it impossible to detect homologous sequences in most species. To overcome this problem, we used a four-step computational pipeline to identify candidate a-factor genes in sequenced genomes of the Saccharomycotina, the fungal clade that contains most of the yeasts: we require that candidate genes have a C-terminal prenylation motif, are fewer than 100 amino acids long, contain a proteolytic processing motif upstream of the potential mature pheromone sequence, and that closely related species contain highly conserved homologs of the potential mature pheromone sequence. Additional manual curation exploits the observation that many species carry more than one a-factor gene, encoding identical or nearly identical pheromones. From 332 fungal genomes, we identified strong candidate pheromone genes in 238 genomes, covering 13 clades that are separated from each other by at least 100 million years, the time required for evolution to remove detectable sequence homology. For one small clade, the Yarrowia, we demonstrated that our algorithm found the a-factor genes: deleting all four related genes in the a-mating type of Yarrowia lipolytica prevents mating.

Two New Records of Upeneus Spottocaudalis and U. Sundaicus (Perciformes: Mullidae) from the Northern South China Sea Based on the Morphology and DNA Barcoding

In this study, two new records of goatfishes Upeneus spottocaudalis and U. sundaicus from the South China Sea, combing evidence from morphology and DNA barcodes for species identification. ML tree and NJ tree result showed that the sequences of U. spottocaudalis and U. sundaicus were clustered with the homologous sequences form GenBank, respectively, and the intraspecific genetic distances of U. spottocaudalis (0.2%) and U. sundaicus (0.3%) were less than 2%. Automatic Barcode Gap Discovery (ABGD) analysis also supported this result of classification.

Heterologous synapsis in C. elegans is regulated by meiotic double-strand breaks and crossovers

Alignment of the parental chromosomes during meiotic prophase is key to the formation of genetic exchanges, or crossovers, and consequently to the successful production of gametes. In almost all studied organisms, alignment involves synapsis: the assembly of a conserved inter-chromosomal interface called the synaptonemal complex (SC). While the SC usually synapses homologous sequences, it can assemble between heterologous sequences. However, little is known about the regulation of heterologous synapsis. Here we study the dynamics of heterologous synapsis in the nematode C. elegans. We characterize two experimental scenarios: SC assembly onto a folded-back chromosome that cannot pair with its homologous partner; and synapsis of pseudo-homologs, a fusion chromosome partnering with an unfused chromosome half its size. We observed elevated levels of heterologous synapsis when the number of meiotic double-strand breaks or crossovers were reduced, indicating that the promiscuity of synapsis is regulated by break formation or repair. By manipulating the levels of breaks and crossovers, we infer both chromosome-specific and nucleus-wide regulation on heterologous synapsis. Finally, we identify differences between the two conditions, suggesting that attachment to the nuclear envelope plays a role in regulating heterologous synapsis.

Improving fragment-based ab initio protein structure assembly using low-accuracy contact-map predictions

Sequence-based contact prediction has shown considerable promise in assisting non-homologous structure modeling, but it often requires many homologous sequences and a sufficient number of correct contacts to achieve correct folds. Here, we developed a method, C-QUARK, that integrates multiple deep-learning and coevolution-based contact-maps to guide the replica-exchange Monte Carlo fragment assembly simulations. The method was tested on 247 non-redundant proteins, where C-QUARK could fold 75% of the cases with TM-scores (template-modeling scores) ≥0.5, which was 2.6 times more than that achieved by QUARK. For the 59 cases that had either low contact accuracy or few homologous sequences, C-QUARK correctly folded 6 times more proteins than other contact-based folding methods. C-QUARK was also tested on 64 free-modeling targets from the 13th CASP (critical assessment of protein structure prediction) experiment and had an average GDT_TS (global distance test) score that was 5% higher than the best CASP predictors. These data demonstrate, in a robust manner, the progress in modeling non-homologous protein structures using low-accuracy and sparse contact-map predictions.

Mating can initiate stable RNA silencing that overcomes epigenetic recovery

Stable epigenetic changes appear uncommon, suggesting that changes typically dissipate or are repaired. Changes that stably alter gene expression across generations presumably require particular conditions that are currently unknown. Here we report that a minimal combination of cis-regulatory sequences can support permanent RNA silencing of a single-copy transgene and its derivatives in C. elegans simply upon mating. Mating disrupts competing RNA-based mechanisms to initiate silencing that can last for >300 generations. This stable silencing requires components of the small RNA pathway and can silence homologous sequences in trans. While animals do not recover from mating-induced silencing, they often recover from and become resistant to trans silencing. Recovery is also observed in most cases when double-stranded RNA is used to silence the same coding sequence in different regulatory contexts that drive germline expression. Therefore, we propose that regulatory features can evolve to oppose permanent and potentially maladaptive responses to transient change.