Biological systems depend on finely tuned interactions of their components. Thus, regulating these components is critical for the system's functionality. In prokaryotic cells, riboswitches are regulatory elements controlling transcription or translation. Riboswitches are RNA molecules that are usually located in the 5′-untranslated region of protein-coding genes. They generate secondary structures leading to the regulation of the expression of the downstream protein-coding gene (Kavita and Breaker, 2022). Riboswitches are very versatile and can bind a wide range of small molecules; in many cases, these are metabolic byproducts from the gene’s enzymatic or signaling pathway. Their versatility and abundance in many species make them attractive for synthetic biological circuits. One class that has been drawing the attention of synthetic biologists is toehold switches (Ekdahl et al., 2022; Green et al., 2014). These are single-stranded RNA molecules harboring the necessary elements for translation initiation of the downstream gene: a ribosome-binding site and a start codon. Conformation change of toehold switches is triggered by an RNA molecule, which enables translation.

To exploit the most out of toehold switches, automation of their design would be highly advantageous. Cisneros and colleagues (Cisneros et al., 2022) developed a tool, “Toeholder”, that automates the design of toehold switches and performs in silico tests to select switch candidates for a target gene. Toeholder is an open-source tool that provides a comprehensive and automated workflow for the design of toehold switches. While web tools have been developed for designing toehold switches (To et al., 2018), Toeholder represents an intriguing approach to engineering biological systems by coupling synthetic biology with computational biology. Using molecular dynamics simulations, it identified the positions in the toehold switch where hydrogen bonds fluctuate the most. Identifying these regions holds great potential for modifications when refining the design of the riboswitches. To be effective, toehold switches should provide a strong ON signal and a weak OFF signal in the presence or the absence of a target, respectively. Toeholder nicely ranks the candidate toehold switches based on experimental evidence that correlates with toehold performance (based on good ON/OFF ratios).

Riboswitches are highly appealing for a broad range of applications, including pharmaceutical and medical purposes (Blount and Breaker, 2006; Giarimoglou et al., 2022; Tickner and Farzan, 2021), thanks to their adaptability and inexpensiveness. The Toeholder tool developed by Cisneros and colleagues is expected to promote the implementation of toehold switches into these various applications.

References

Blount KF, Breaker RR (2006) Riboswitches as antibacterial drug targets. Nature Biotechnology, 24, 1558–1564. https://doi.org/10.1038/nbt1268

Cisneros AF, Rouleau FD, Bautista C, Lemieux P, Dumont-Leblond N, ULaval 2019 T iGEM (2022) Toeholder: a Software for Automated Design and In Silico Validation of Toehold Riboswitches. bioRxiv, 2021.11.09.467922, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.11.09.467922

Ekdahl AM, Rojano-Nisimura AM, Contreras LM (2022) Engineering Toehold-Mediated Switches for Native RNA Detection and Regulation in Bacteria. Journal of Molecular Biology, 434, 167689. https://doi.org/10.1016/j.jmb.2022.167689

Giarimoglou N, Kouvela A, Maniatis A, Papakyriakou A, Zhang J, Stamatopoulou V, Stathopoulos C (2022) A Riboswitch-Driven Era of New Antibacterials. Antibiotics, 11, 1243. https://doi.org/10.3390/antibiotics11091243

Green AA, Silver PA, Collins JJ, Yin P (2014) Toehold Switches: De-Novo-Designed Regulators of Gene Expression. Cell, 159, 925–939. https://doi.org/10.1016/j.cell.2014.10.002

Kavita K, Breaker RR (2022) Discovering riboswitches: the past and the future. Trends in Biochemical Sciences. https://doi.org/10.1016/j.tibs.2022.08.009

Tickner ZJ, Farzan M (2021) Riboswitches for Controlled Expression of Therapeutic Transgenes Delivered by Adeno-Associated Viral Vectors. Pharmaceuticals, 14, 554. https://doi.org/10.3390/ph14060554

To AC-Y, Chu DH-T, Wang AR, Li FC-Y, Chiu AW-O, Gao DY, Choi CHJ, Kong S-K, Chan T-F, Chan K-M, Yip KY (2018) A comprehensive web tool for toehold switch design. Bioinformatics, 34, 2862–2864. https://doi.org/10.1093/bioinformatics/bty216

The European Reference Genome Atlas (ERGA) (Mc Cartney et al, 2024, Mazzoni et al, 2023) demonstrates the collaborative spirit and intellectual abilities of researchers from 33 European countries. This ambitious project, which is part of the Earth BioGenome Project (Lewin et al., 2018) Phase II, has embarked on an unprecedented mission: to decipher the genetic makeup of 150,000 species over a span of four years. At the heart of ERGA is a decentralized pilot infrastructure specifically built to assist the production of high-quality reference genomes. This structure acts as a scaffold for the massive task of genome sequencing, giving the necessary framework to manage the complexity of genomic research. The research paper under consideration offers a comprehensive narrative of ERGA's evolution, outlining both successes and challenges encountered along the road. 

One of the most significant issues addressed in the manuscript is the equitable distribution of resources and expertise among participating laboratories and countries. In a project of this magnitude, it is critical to leverage the pooled talents and capacities of researchers from across Europe. ERGA's pan-European network promotes communications and collaboration, creating an environment in which knowledge flows freely and barriers are overcome. This adoption of strong coordination and communication tactics will be essential to ERGA's success. Scientific collaboration depends on efficient communication channels because they allow researchers to share resources, collaborate on new initiatives, and exchange ideas. Through a diverse range of gatherings, courses, and virtual discussion boards, ERGA fosters an environment of transparency and cooperation among members, enabling scientists to overcome challenges and make significant discoveries. The importance ERGA places on training and information transfer programmes is a pillar of its strategy. Understanding the importance of capacity development, ERGA invests in providing researchers with the knowledge and abilities necessary for effectively navigating the complicated terrain of genomic research. A wide range of subjects are covered in training programmes (Larivière et al. 2023), from sample preparation and collection to data processing methods and sequencing technology. Through the development of a group of highly qualified experts, ERGA creates the foundation for continued advancement and creativity in the genomics sector.

This manuscript also covers in detail the technological workflows and sequencing techniques used in ERGA's pilot infrastructure. With the aid of cutting-edge sequencing technologies based on both long-read and short-read sequencing, they are working to unravel the complex structure of the genetic code with a level of accuracy and precision never before possible. To guarantee the accuracy of genetic data and prevent mistakes and flaws that can jeopardize the findings' integrity, quality control methods are put in place. Despite having a focus on genome sequencing due to its technological complexities, ERGA also remains firm in its dedication to metadata collection and sample validation. Metadata serves as a critical link between raw genetic data and useful scientific insights, giving necessary context and allowing researchers to draw practical findings from their investigations. Sample validation approaches improve the reliability and reproducibility of the results, providing users confidence in the quality of the genetic data provided by ERGA.​

Looking ahead, ERGA envisions its decentralized infrastructure serving as a model for global collaborative research efforts. By embracing diversity, encouraging cooperation, and pushing for open access to data and resources, ERGA hopes to catalyze scientific discovery and generate positive change in the field of biodiversity genomics. ERGA aims to promote a more equitable and sustainable future for all by ongoing interaction with stakeholders, intensive outreach and education activities, and policy change advocacy. In addition to its immediate goals, ERGA considers the long-term implications of its work. As genomic technology progresses, the potential application of high-quality reference genomes will continue to grow. From informing conservation efforts and illuminating evolutionary histories to revolutionizing healthcare and agriculture, it is likely that ERGA's contributions will have far-reaching consequences for people and the planet as a whole.​

Furthermore, ERGA understands the importance of interdisciplinary collaboration in addressing the difficult challenges of the twenty-first century. ERGA aims to integrate genetic research into larger initiatives to promote sustainability and biodiversity conservation by forming relationships with stakeholders from other areas, such as policymakers, conservationists, and indigenous groups. Through shared knowledge and community action, ERGA seeks to create a future in which mankind coexists peacefully with the natural world, guided by a thorough grasp of its genetic legacy and ecological interconnectivity.

Finally, the manuscript exemplifies ERGA's collaborative ambitions and achievements, capturing the spirit of creativity and collaboration that defines this ground-breaking effort. As ERGA continues to push the boundaries of genetic research, it remains dedicated to scientific excellence, inclusivity, and the quest of knowledge for the benefit of society. I wholeheartedly recommend the publication of this groundbreaking initiative, offering my enthusiastic endorsement for its valuable contribution to the scientific community.​​

References
Larivière, D., Abueg, L., Brajuka, N. et al. (2024). Scalable, accessible and reproducible reference genome assembly and evaluation in Galaxy. Nature Biotechnology 42, 367-370. https://doi.org/10.1038/s41587-023-02100-3

Lewin, H. A., Robinson, G. E., Kress, W. J., Baker, W. J., Coddington, J., Crandall, K. A., Durbin, R., Edwards, S. V., Forest, F., Gilbert, M. T. P., Goldstein, M. M., Grigoriev, I. V., Hackett, K. J., Haussler, D., Jarvis, E. D., Johnson, W. E., Patrinos, A., Richards, S., Castilla-Rubio, J. C., … Zhang, G. (2018). Earth BioGenome Project: Sequencing life for the future of life. Proceedings of the National Academy of Sciences, 115(17), 4325–4333. https://doi.org/10.1073/pnas.1720115115

Mazzoni, C. J., Claudio, C.i, Waterhouse, R. M. (2023). Biodiversity: an atlas of European reference genomes. Nature 619 : 252-252. https://doi.org/10.1038/d41586-023-02229-w

Mc Cartney, A. M., Formenti, G., Mouton, A., Panis, D. de, Marins, L. S., Leitão, H. G., Diedericks, G., Kirangwa, J., Morselli, M., Salces-Ortiz, J., Escudero, N., Iannucci, A., Natali, C., Svardal, H., Fernández, R., Pooter, T. de, Joris, G., Strazisar, M., Wood, J., … Mazzoni, C. J. (2024). The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.09.25.559365​

Any multicellular organism is a molecular mosaic with some somatic mutations accumulated between cell lineages. Big long-lived trees have nourished this imaginary of a somatic mosaic tree, from the observation of spectacular phenotypic mosaics and also because somatic mutations are expected to potentially be passed on to gametes in plants (review in Schoen and Schultz 2019). The lower cost of genome sequencing now offers the opportunity to tackle the issue and identify somatic mutations in trees.

However, when it comes to characterizing this somatic mosaic from genome sequences, things become much more difficult than one would think in the first place. What separates cell lineages ontogenetically, in cell division number, or in time? How to sample clonal cell populations? How do somatic mutations distribute in a population of cells in an organ or an organ sample? Should they be fixed heterozygotes in the sample of cells sequenced or be polymorphic? Do we indeed expect somatic mutations to be fixed? How should we identify and count somatic mutations?

To date, the detection of somatic mutations has mostly been done with a single variant caller in a given study, and we have little perspective on how different callers provide similar or different results. Some studies have used standard SNP callers that assumed a somatic mutation is fixed at the heterozygous state in the sample of cells, with an expected allele coverage ratio of 0.5, and less have used cancer callers, designed to detect mutations in a fraction of the cells in the sample. However, standard SNP callers detect mutations that deviate from a balanced allelic coverage, and different cancer callers can have different characteristics that should affect their outcomes.

In order to tackle these issues, Schmitt et al. (2022) conducted an extensive simulation analysis to compare different variant callers. Then, they reanalyzed two large published datasets on pedunculate oak, Quercus robur.  The analysis of in silico somatic mutations allowed the authors to evaluate the performance of different variant callers as a function of the allelic fraction of somatic mutations and the sequencing depth. They found one of the seven callers to provide better and more robust calls for a broad set of allelic fractions and sequencing depths. The reanalysis of published datasets in oaks with the most effective cancer caller of the in silico analysis allowed them to identify numerous low-frequency mutations that were missed in the original studies.

I recommend the study of Schmitt et al. (2022) first because it shows the benefit of using cancer callers in the study of somatic mutations, whatever the allelic fraction you are interested in at the end. You can select fixed heterozygotes if this is your ultimate target, but cancer callers allow you to have in addition a valuable overview of the allelic fractions of somatic mutations in your sample, and most do as well as SNP callers for fixed heterozygous mutations. In addition, Schmitt et al. (2022) provide the pipelines that allow investigating in silico data that should correspond to a given study design, encouraging to compare different variant callers rather than arbitrarily going with only one. We can anticipate that the study of somatic mutations in non-model species will increasingly attract attention now that multiple tissues of the same individual can be sequenced at low cost, and the study of Schmitt et al. (2022) paves the way for questioning and choosing the best variant caller for the question one wants to address.

References

Schoen DJ, Schultz ST (2019) Somatic Mutation and Evolution in Plants. Annual Review of Ecology, Evolution, and Systematics, 50, 49–73. https://doi.org/10.1146/annurev-ecolsys-110218-024955

Schmitt S, Leroy T, Heuertz M, Tysklind N (2022) Somatic mutation detection: a critical evaluation through simulations and reanalyses in oaks. bioRxiv, 2021.10.11.462798. ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.10.11.462798

The development (and standardization) of high-throughput sequencing techniques has revolutionized evolutionary biology, to the point that we almost see as normal fine-detail studies of genome architecture evolution (Robert et al., 2022), adaptation to new habitats (Rahi et al., 2019), or the development of key evolutionary novelties (Hilgers et al., 2018), to name three examples. One of the fields that has benefited the most is phylogenomics, i.e. the use of genome-wide data for inferring the evolutionary relationships among organisms. Dealing with such amount of data, however, has come with important analytical and computational challenges. Likewise, although the steady generation of genomic data from virtually any organism opens exciting opportunities for comparative analyses, it also creates a sort of “information fog”, where it is hard to find the most appropriate and/or the higher quality data. I have personally experienced this not so long ago, when I had to spend several weeks selecting the most complete transcriptomes from several phyla, moving back and forth between the NCBI SRA repository and the relevant literature.

In an attempt to deal with this issue, some research labs have committed their time and resources to the generation of taxa- and topic-specific databases (Lathe et al., 2008), such as MolluscDB (Liu et al., 2021), focused on mollusk genomics, or EukProt (Richter et al., 2022), a protein repository representing the diversity of eukaryotes. A new database that promises to become an important resource in the near future is MATEdb (Fernández et al., 2022), a repository of high-quality genomic data from Metazoa. MATEdb has been developed from publicly available and newly generated transcriptomes and genomes, prioritizing quality over quantity. Upon download, the user has access to both raw data and the related datasets: assemblies, several quality metrics, the set of inferred protein-coding genes, and their annotation. Although it is clear to me that this repository has been created with phylogenomic analyses in mind, I see how it could be generalized to other related problems such as analyses of gene content or evolution of specific gene families. In my opinion, the main strengths of MATEdb are threefold:

1. Rosa Fernández and her team have carefully scrutinized the genomic data available in several repositories to retrieve only the most complete transcriptomes and genomes, saving a lot of time in data mining to the user.
2. These data have been analyzed to provide both the assembly and the set of protein-coding genes, easing the computational burden that usually accompanies these pipelines. Interestingly, all the data have been analyzed with the same software and parameters, facilitating comparisons among taxa.
3. Genomic analysis can be intimidating, and even more for inexperienced users. That is particularly important when it comes to transcriptome and genome assembly because it has an effect in all downstream analyses. I believe that having access to already analyzed data softens this transition. The users can move forward on their research while they learn how to generate and analyze their data at their own pace.

On a negative note, I see two main drawbacks. First, as of today (September 16th, 2022) this database is in an early stage and it still needs to incorporate a lot of animal groups. This has been discussed during the revision process and the authors are already working on it, so it is only a matter of time until all major taxa are represented. Second, there is a scalability issue. In its current format it is not possible to select the taxa of interest and the full database has to be downloaded, which will become more and more difficult as it grows. Nonetheless, with the appropriate resources it would be easy to find a better solution. There are plenty of examples that could serve as inspiration, so I hope this does not become a big problem in the future.

Altogether, I and the researchers that participated in the revision process believe that MATEdb has the potential to become an important and valuable addition to the metazoan phylogenomics community. Personally, I wish it was available just a few months ago, it would have saved me so much time.

References

Fernández R, Tonzo V, Guerrero CS, Lozano-Fernandez J, Martínez-Redondo GI, Balart-García P, Aristide L, Eleftheriadi K, Vargas-Chávez C (2022) MATEdb, a data repository of high-quality metazoan transcriptome assemblies to accelerate phylogenomic studies. bioRxiv, 2022.07.18.500182, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.07.18.500182

Hilgers L, Hartmann S, Hofreiter M, von Rintelen T (2018) Novel Genes, Ancient Genes, and Gene Co-Option Contributed to the Genetic Basis of the Radula, a Molluscan Innovation. Molecular Biology and Evolution, 35, 1638–1652. https://doi.org/10.1093/molbev/msy052

Lathe W, Williams J, Mangan M, Karolchik, D (2008). Genomic data resources: challenges and promises. Nature Education, 1(3), 2.

Liu F, Li Y, Yu H, Zhang L, Hu J, Bao Z, Wang S (2021) MolluscDB: an integrated functional and evolutionary genomics database for the hyper-diverse animal phylum Mollusca. Nucleic Acids Research, 49, D988–D997. https://doi.org/10.1093/nar/gkaa918

Rahi ML, Mather PB, Ezaz T, Hurwood DA (2019) The Molecular Basis of Freshwater Adaptation in Prawns: Insights from Comparative Transcriptomics of Three Macrobrachium Species. Genome Biology and Evolution, 11, 1002–1018. https://doi.org/10.1093/gbe/evz045

Richter DJ, Berney C, Strassert JFH, Poh Y-P, Herman EK, Muñoz-Gómez SA, Wideman JG, Burki F, Vargas C de (2022) EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotes. bioRxiv, 2020.06.30.180687, ver. 5 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2020.06.30.180687

Robert NSM, Sarigol F, Zimmermann B, Meyer A, Voolstra CR, Simakov O (2022) Emergence of distinct syntenic density regimes is associated with early metazoan genomic transitions. BMC Genomics, 23, 143. https://doi.org/10.1186/s12864-022-08304-2

The first time I heard of ”onagres” in French was when I was a teenager, through the books of Pierre Bordage as fantastic monsters, or through historical games as Roman siege weapons (onagers). At this time, I was far from imagining that “onagre” also refers to a very large flowering plant family, as it is the French term for evening primroses.

In this family, the genus Ludwigia comprises species that are invasive (resembling in that way the ancient armies using onagers to invade cities) in aquatic environments, degrading ecosystems already fragilized by human activities. To counteract this phenomenon, it is of high importance to understand their propagation of these species. However, the knowledge about their genetics and diversity is very scarce, and thus tracking their dispersal using genetic information is complicated, and in fact almost impossible.

Barloy-Hubler et al. (2024) proposed in the present manuscript a new set of chloroplastic genomes from two of these species, Ludwigia grandiflora subsp. hexapetala and Ludwigia peploides subsp. montevidensis, and compared them to the published chloroplastic genome of Ludwigia octovalis. They explored the possibility of assembling these genomes relying solely on short reads and showed that long reads were necessary to obtain an almost complete assembly for these plastid genomes. In addition, through this approach, they detected two haplotypes in Ludwigia grandiflora subsp. hexapetala as compared to one in a short-read assembly. This highlights the need for long reads data to assess the structure and diversity of chloroplastic genomes. The authors were also able to clarify the phylogeny of the genus Ludwigia. Finally, they identified multiple potential single nucleotide polymorphisms and simple sequence repeats for future evaluation of diversity and dispersal of those invasive species.

This analysis, while appearing more technical than biological at first glance, is in fact of high importance for the understanding of ecology and preservation of fragile ecosystems, such as the European watersheds. Indeed, new scientific results and insights are generally linked to a reevaluation of previously analyzed data or samples through new technologies, and this paper is a quite clever example of that matter.

References

Barloy-Hubler F, Gac A-LL, Boury C, Guichoux E, Barloy D (2024) Sequencing, de novo assembly of Ludwigia plastomes, and comparative analysis within the Onagraceae family. bioRxiv, ver. 5 peer-reviewed and recommended by PCI Genomics. https://doi.org/10.1101/2023.10.20.563230

Bordage, P (1993) Les Guerriers du Silence, L'Atalante, ISBN 9782905158697