sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data

Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen

The spatial organization of eukaryotic genomes is linked to their biological functions, although it is not clear how this impacts the overall evolution of a genome. Here, we uncover the three-dimensional (3D) genome organization of the phytopathogen Verticillium dahliae, known to possess distinct genomic regions, designated adaptive genomic regions (AGRs), enriched in transposable elements and genes that mediate host infection. Short-range DNA interactions form clear topologically associating domains (TADs) with gene-rich boundaries that show reduced levels of gene expression and reduced genomic variation. Intriguingly, TADs are less clearly insulated in AGRs than in the core genome. At a global scale, the genome contains bipartite long-range interactions, particularly enriched for AGRs and more generally containing segmental duplications. Notably, the patterns observed for V. dahliae are also present in other Verticillium species. Thus, our analysis links 3D genome organization to evolutionary features conserved throughout the Verticillium genus.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Transcriptomic and genomic effects of gamma-radiation exposure on strains of the black yeast Exophiala dermatitidis evolved to display increased ionizing radiation resistance

Melanized fungi thrive in extreme environments, including those with high levels of ionizing radiation. To understand the role that melanin may play in ionizing radiation resistance, we previously performed an adaptive laboratory evolution experiment in which we used melanized and non-melanized strains of the yeast Exophiala dermatitidis to develop evolved lines that exhibit increased ionizing radiation resistance. In this study, we further characterized these evolved lines by analyzing their response to ionizing radiation at the transcriptomic and genomic levels. RNA sequencing showed that the response to gamma irradiation in both unevolved and evolved strains involved the induction of DNA repair genes. However, in the melanized lines evolved to exhibit increased ionizing radiation resistance, DNA-associated genes were constitutively expressed, compared to their expression levels in wild type. Non-melanized lines that were evolved to be resistant to ionizing radiation, on the other hand, exhibited upregulation of genes involved in redox homeostasis, even under non-irradiated conditions. Additionally, we characterized genome-wide mutations induced by a single high dose of gamma radiation in these evolved lines and observed that while melanin did not directly affect survival after gamma radiation exposure, melanized lines that evolved to exhibit higher ionizing radiation resistance experienced fewer mutations, whereas similarly evolved, non-melanized lines accumulated more mutations, similar to the parent, non-melanized strain. These results underscore the complex yet measurable role of melanin in the response to ionizing radiation in E. dermatitidis. Furthermore, this study enhances our understanding of the mechanisms underlying the recovery after ionizing radiation exposure in melanized fungi and offers insights into the potential therapeutic applications of melanin and other redox molecules for protecting against ionizing radiation-induced damage. IMPORTANCE Ionizing radiation poses a significant threat to living organisms and human health, given its destructive nature and widespread use in fields such as medicine and the potential for nuclear disasters. Melanized fungi exhibit remarkable survival capabilities, enduring doses up to 1,000-fold higher than mammals. Through adaptive laboratory evolution, we validated the protective role of constitutive upregulation of DNA repair genes in the black yeast Exophiala dermatitidis, enhancing survival after radiation exposure. Surprisingly, we found that evolved strains lacking melanin still achieved high levels of radioresistance. Our study unveiled the significance of robust activation and enhancement of redox homeostasis, as evidenced by the profound transcriptional changes and increased accumulation of mutations, in substantially improving ionizing radiation resistance in the absence of melanin. These findings underscore the delicate balance between DNA repair and redox homeostasis for an organism's ability to endure and recover from radiation exposure.

MSV: a modular structural variant caller that reveals nested and complex rearrangements by unifying breakends inferred directly from reads

Structural variant (SV) calling belongs to the standard tools of modern bioinformatics for identifying and describing alterations in genomes. Initially, this work presents several complex genomic rearrangements that reveal conceptual ambiguities inherent to the representation via basic SV. We contextualize these ambiguities theoretically as well as practically and propose a graph-based approach for resolving them. For various yeast genomes, we practically compute adjacency matrices of our graph model and demonstrate that they provide highly accurate descriptions of one genome in terms of another. An open-source prototype implementation of our approach is available under the MIT license at https://github.com/ITBE-Lab/MA .

Comprehensive characterization of copy number variation (CNV) called from array, long- and short-read data

BACKGROUND

SNP arrays, short- and long-read genome sequencing are genome-wide high-throughput technologies that may be used to assay copy number variants (CNVs) in a personal genome. Each of these technologies comes with its own limitations and biases, many of which are well-known, but not all of them are thoroughly quantified.

RESULTS

We assembled an ensemble of public datasets of published CNV calls and raw data for the well-studied Genome in a Bottle individual NA12878. This assembly represents a variety of methods and pipelines used for CNV calling from array, short- and long-read technologies. We then performed cross-technology comparisons regarding their ability to call CNVs. Different from other studies, we refrained from using the golden standard. Instead, we attempted to validate the CNV calls by the raw data of each technology.

CONCLUSIONS

Our study confirms that long-read platforms enable recalling CNVs in genomic regions inaccessible to arrays or short reads. We also found that the reproducibility of a CNV by different pipelines within each technology is strongly linked to other CNV evidence measures. Importantly, the three technologies show distinct public database frequency profiles, which differ depending on what technology the database was built on.

Ivory poaching and the rapid evolution of tusklessness in African elephants

[Figure: see text].

Viola: a structural variant signature extractor with user-defined classifications

SUMMARY

Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g. cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data.

AVAILABILITY AND IMPLEMENTATION

Viola is available on pip (https://pypi.org/project/Viola-SV/) and the source code is on GitHub (https://github.com/dermasugita/Viola-SV).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transposable Elements Contribute to Genome Dynamics and Gene Expression Variation in the Fungal Plant Pathogen Verticillium dahliae

Transposable elements (TEs) are a major source of genetic and regulatory variation in their host genome and are consequently thought to play important roles in evolution. Many fungal and oomycete plant pathogens have evolved dynamic and TE-rich genomic regions containing genes that are implicated in host colonization and adaptation. TEs embedded in these regions have typically been thought to accelerate the evolution of these genomic compartments, but little is known about their dynamics in strains that harbor them. Here, we used whole-genome sequencing data of 42 strains of the fungal plant pathogen Verticillium dahliae to systematically identify polymorphic TEs that may be implicated in genomic as well as in gene expression variation. We identified 2,523 TE polymorphisms and characterize a subset of 8% of the TEs as polymorphic elements that are evolutionary younger, less methylated, and more highly expressed when compared with the remaining 92% of the total TE complement. As expected, the polyrmorphic TEs are enriched in the adaptive genomic regions. Besides, we observed an association of polymorphic TEs with pathogenicity-related genes that localize nearby and that display high expression levels. Collectively, our analyses demonstrate that TE dynamics in V. dahliae contributes to genomic variation, correlates with expression of pathogenicity-related genes, and potentially impacts the evolution of adaptive genomic regions.

Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field

A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors-and beyond-to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.

Towards a better understanding of the low recall of insertion variants with short-read based variant callers

BACKGROUND

Since 2009, numerous tools have been developed to detect structural variants using short read technologies. Insertions >50 bp are one of the hardest type to discover and are drastically underrepresented in gold standard variant callsets. The advent of long read technologies has completely changed the situation. In 2019, two independent cross technologies studies have published the most complete variant callsets with sequence resolved insertions in human individuals. Among the reported insertions, only 17 to 28% could be discovered with short-read based tools.

RESULTS

In this work, we performed an in-depth analysis of these unprecedented insertion callsets in order to investigate the causes of such failures. We have first established a precise classification of insertion variants according to four layers of characterization: the nature and size of the inserted sequence, the genomic context of the insertion site and the breakpoint junction complexity. Because these levels are intertwined, we then used simulations to characterize the impact of each complexity factor on the recall of several structural variant callers. We showed that most reported insertions exhibited characteristics that may interfere with their discovery: 63% were tandem repeat expansions, 38% contained homology larger than 10 bp within their breakpoint junctions and 70% were located in simple repeats. Consequently, the recall of short-read based variant callers was significantly lower for such insertions (6% for tandem repeats vs 56% for mobile element insertions). Simulations showed that the most impacting factor was the insertion type rather than the genomic context, with various difficulties being handled differently among the tested structural variant callers, and they highlighted the lack of sequence resolution for most insertion calls.

CONCLUSIONS

Our results explain the low recall by pointing out several difficulty factors among the observed insertion features and provide avenues for improving SV caller algorithms and their combinations.