One way to identify all organisms at their various life stages is by their genetic signature. DNA-based taxonomy, gene tagging and barcoding are different shortcuts used to name such strategies (Lamb et al. 2019; Tautz et al. 2003). Reading and analyzing nucleic acid sequences to perform genetic inventories is now faster than ever, and the latest nucleic acid sequencing technologies reveal an impressive taxonomic, genetic, and functional diversity hidden in all ecosystems (Lamb et al. 2019; Sunagawa et al. 2015). This knowledge should enable us to evaluate biodiversity across its scales, from genetic to species to ecosystem and is sometimes referred to with the neologism of ecogenomics (Dicke et al. 2004).

The metabarcoding approach is a key workhorse of ecogenomics. At the core of metabarcoding strategies lies the sequencing of amplicons obtained from so-called multi-template PCR, a formidable and potent experiment with the potential to unravel hidden biosphere components from different samples obtained from organisms or the environment (Kalle et al. 2014; Rodríguez-Ezpeleta et al. 2021). Next to this core approach, and equally important, lies the bioinformatic analysis to convert the raw sequencing data into amplicon sequence variants or operational taxonomic units and interpretable abundance tables.

Methodologically, the analysis of sequences obtained from metabarcoding projects is replete with devilish details. This is why different pipelines and tools have been developed, starting with mothur (Schloss et al. 2009) and QIIME 2 (Bolyen et al. 2019), but including more user friendly tools such as FROGS (Escudié et al. 2018). Yet, across all available tools, scientists must choose the optimal algorithms and parameter values to filter raw reads, trim primers, identify chimeras and cluster reads into operational taxonomic units. In addition, the number of genetic markers used to characterize a sample using metabarcoding has increased as  sequencing methods are now less costly and more efficient. In such cases, results and interpretations may become limited or confounded. This is where the novel tools proposed by Barnabé and colleagues (2024), mbctools, will benefit researchers in this field.

The authors provide a detailed description with a walk-through of the mbctools pipeline to analyse raw reads obtained in a metabarcoding project. The mbctools pipeline can be installed under different computing environments, requires only VSEARCH and a few Python dependencies, and is easy to use with a menu-driven interface. Users need to prepare their data following simple rules, providing single or paired-end reads, primer and target database sequences. An interesting feature of mbctools output is the possibility of integration with the metaXplor visualization tool developed by the authors (Sempéré et al. 2021). As it stands, mbctools should be used for short-read sequences. The taxonomy assignment module has the advantage to enable parameters exploration in an easy way, but it may be oversimplistic for specific taxa.

The lightweight aspect of mbctools and its overall simplicity are appealing. These features will make it a useful pipeline for training workshops and to help disseminate the use of metabarcoding. It also holds the potential for further improvement, by the developers or by others. In the end, mbctools will support study reproducibility by enabling a streamlined analysis of raw reads, and like many useful tools, only time will tell whether it is widely adopted.

         
References

Barnabé C, Sempéré G, Manzanilla V, Millan JM, Amblard-Rambert A, Waleckx E (2024) mbctools: A user-friendly metabarcoding and cross-platform pipeline for analyzing multiple amplicon sequencing data across a large diversity of organisms. bioRxiv, ver. 2 peer-reviewed and recommended by PCI Genomics https://doi.org/10.1101/2024.02.08.579441

Bolyen E, Rideout JR, Dillon MR, Bokulich NA, et al. (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology, 37, 852–857. https://doi.org/10.1038/s41587-019-0209-9

Dicke M, van Loon JJA, de Jong PW (2004) Ecogenomics benefits community ecology. Science, 305, 618–619. https://doi.org/10.1126/science.1101788

Escudié F, Auer L, Bernard M, Mariadassou M, Cauquil L, Vidal K, Maman S, Hernandez-Raquet G, Combes S, Pascal G (2018) FROGS: Find, Rapidly, OTUs with Galaxy Solution. Bioinformatics, 34, 1287-1294. https://doi.org/10.1093/bioinformatics/btx791

Kalle E, Kubista M, Rensing C (2014) Multi-template polymerase chain reaction. Biomolecular Detection and Quantification, 2, 11–29. https://doi.org/10.1016/j.bdq.2014.11.002

Lamb CT, Ford AT, Proctor MF, Royle JA, Mowat G, Boutin S (2019) Genetic tagging in the Anthropocene: scaling ecology from alleles to ecosystems. Ecological Applications, 29, e01876. https://doi.org/10.1002/eap.1876

Rodríguez-Ezpeleta N, Zinger L, Kinziger A, Bik HM, Bonin A, Coissac E, Emerson BC, Lopes CM, Pelletier TA, Taberlet P, Narum S (2021) Biodiversity monitoring using environmental DNA. Molecular Ecology Resources, 21, 1405–1409. https://doi.org/10.1111/1755-0998.13399

Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75, 7537-41. https://doi.org/10.1128/AEM.01541-09

Sempéré G, Pétel A, Abbé M, Lefeuvre P, Roumagnac P, Mahé F, Baurens G, Filloux D 2021 metaXplor: an interactive viral and microbial metagenomic data manager. Gigascience, 10, https://doi.org/10.1093/gigascience/giab001

Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, Djahanschiri B, Zeller G, Mende DR, Alberti A, Cornejo-Castillo FM, Costea PI, Cruaud C, d’Ovidio F, Engelen S, Ferrera I, Gasol JM, Guidi L, Hildebrand F, Kokoszka F, Lepoivre C, Lima-Mendez G, Poulain J, Poulos BT, Royo-Llonch M, Sarmento H, Vieira-Silva S, Dimier C, Picheral M, Searson S, Kandels-Lewis S, Tara Oceans coordinators, Bowler C, de Vargas C, Gorsky G, Grimsley N, Hingamp P, Iudicone D, Jaillon O, Not F, Ogata H, Pesant S, Speich S, Stemmann L, Sullivan MB, Weissenbach J, Wincker P, Karsenti E, Raes J, Acinas SG, Bork P (2015) Structure and function of the global ocean microbiome. Science, 348, 1261359. https://doi.org/10.1126/science.1261359

Tautz D, Arctander P, Minelli A, Thomas RH, Vogler AP (2003) A plea for DNA taxonomy. Trends in Ecology & Evolution, 18, 70–74. https://doi.org/10.1016/S0169-5347(02)00041-1

While it is widely agreed that the conservation of local breeds is key to the maintenance of livestock biodiversity, the implementation of such programmes is often carried out by amateur breeders and may be inadequate due to a lack of knowledge and financial resources. Bortoluzzi et al. (2024) clearly demonstrate the utility of whole-genome sequencing (WGS) data for this purpose, compare two scenarios that differ in the consistency of conservation efforts, and provide valuable recommendations for conservation programmes.

Genetic diversity in livestock is generally considered to be crucial to maintaining food security and ensuring the provision of necessary nutrients to humans (Godde et al. 2021). It is also important to recognise that the preservation of local breeds is a matter of cultural identity for certain regions, and that the products of these breeds are niche products which are in high demand. Especially today, as we face extreme weather conditions, drought and other consequences of global warming, modern breeds selected to perform under constant and temperate conditions are being challenged. The possibility of tapping into the reservoir of genetic variation held by traditional, locally adapted breeds offers an important option for breeding robust livestock. The best way to characterise genetic diversity is through modern molecular methods, based on whole genome sequencing and subsequent advanced population analyses, which has been demonstrated for domesticated and wild chicken (Qanbari et al. 2019).

But are local breed conservation programmes up to the task? In their article, Bortoluzzi and colleagues show that well-designed and professionally managed conservation programmes for local chicken breeds are effective in maintaining genetic diversity. Their article is based on a comparison of two examples of conservation programmes for local chicken breeds: the Barbezieux and the Gasconne, which originated from comparably sized founder populations and for which WGS data were available in a biobank at two timepoints, 2003 and 2013, representing 10 generations. While the conservation programme for the former was continuous, that for the latter was interrupted and later started from scratch with a small number of sires and dams.

The greater loss of genomic diversity in the Gasconne than in the Barbezieux shown in this article may therefore be unsurprising, but the authors provide a range of evidence for this using their population genomics toolbox. The less well-managed breed, Gasconne, shows a lower genome-wide heterozygosity, higher lengths of runs of homozygosity, higher levels of genomic inbreeding, a smaller effective population size and a higher genetic load in terms of predicted deleterious mutations. 

The sample sizes available for population genetic analyses are typically small for local breeds, which is difficult to change as the populations are very small at any given time. It is therefore all the more important to make the most out of it, and Bortoluzzi and co-authors approach the issue from several angles that help support their claim, using WGS data and the latest genomic resources.

In addition to their analyses, the authors provide clear and valuable advice for the management of such conservation programmes. Their analysis of signatures of selection suggests that, apart from adult fertility, not much selection has been taking place. However, the authors emphasise that clear selection objectives other than maintaining the breed, such as production and product quality, can help conservation efforts by providing better guidelines for managing the programme and increasing the availability of resources for conservation programmes when the products of these local breeds become successful. 

In summary, Bortoluzzi et al. (2024) have provided a clear, well-written account of the impact of conservation programme management on the genetic diversity of local chicken breeds, using the most up-to-date genomic resources and analysis methods. As such, this article makes a significant and valuable contribution to the maintenance of genomic resources in livestock, providing approaches and lessons that will hopefully be adopted by other such initiatives.

            
References

Bortoluzzi C, Restoux G, Rouger R, Desnoues B, Petitjean F, Bosse M, Tixier-Boichard M (2024) Trends in genome diversity of small populations under a conservation program: a case study of two French chicken breeds. bioRxiv, ver. 2 peer-reviewed and recommended by PCI Genomics. https://doi.org/10.1101/2024.02.22.581528

Godde CM, Mason-D’Croz D, Mayberry DE, Thornton PK, Herrero M (2021) Impacts of climate change on the livestock food supply chain; a review of the evidence. Global Food Security 28:100488. https://doi.org/10.1016/j.gfs.2020.100488

Qanbari S, Rubin C-J, Maqbool K, Weigend S, Weigend A, Geibel J, Kerje S, Wurmser C, Peterson AT, IL Brisbin Jr., Preisinger R, Fries R, Simianer H, Andersson L (2019) Genetics of adaptation in modern chicken. PLOS Genetics, 15, e1007989. https://doi.org/10.1371/journal.pgen.1007989

Martínez-Redondo and colleagues (2024) present MATEdb2, which provides the scientific community with Metazoa proteomes that have been predicted and annotated in a standardised way. The authors improved the taxon representation from the earlier MATEdb and their current database has a strong focus on Arthropoda, Annelida, and Mollusca. In particular, for the latter two groups not many high-quality reference genomes are available. Standardisation of the prediction and annotation process in a reproducible pipeline, as integrated in MATEdb2, is of great value, in particular to infer phylogenies as correctly as possible. Thus, I am sure that MATEdb2 will be an excellent go-to resource for phylogenomic studies, as well as for probing the biology of new, obscure species, especially marine ones.

                                    
The manuscript was evaluated by two experts in the field of orthology search and orthology databases, and computational biology. The authors diligently implemented the modifications suggested by both referees and I am gladly recommending the manuscript at this point.

                
References
Martínez-Redondo GI, Vargas-Chávez C, Eleftheriadi K, Benítez-Álvarez L, Vázquez-Valls M, Fernández R (2024) MATEdb2, a collection of high-quality metazoan proteomes across the Animal Tree of Life to speed up phylogenomic studies. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2024.02.21.581367

Transposable elements (TEs) are mobile genetic elements with an intrinsic mutagenic potential that influences the physiology of any cell type, whether somatic or germinal. Measuring TE expression is a fundamental prerequisite for analysing the processes leading to the activity of TE-derived sequences. This applies to both old and recent TEs, as even if they are deficient in mobilisation, transcription of TE sequences alone can impact neighbouring gene expression and other cellular activities.

In terms of TE physiology, transcription is crucial for mobilisation activity. The transcription of some TEs can be tissue-specific and associated with splicing events, as exemplified by the P-element isoforms in the fruit fly (Laski et al. 1986). Regarding host cell physiology, TE transcripts can include nearby exons, with or without splicing, and such chimeric transcripts can significantly alter gene activity. Thus, quantitative and qualitative analyses must be conducted to assess TE function and how they can modify genomic activities. Yet, due to the polymorphic, interspersed, and repetitive nature of TE sequences, the quantitative and qualitative analysis of TE transcript levels using short-read sequencing remains challenging (Lanciano and Cristofari 2020).

In this context, Rebollo et al. (2024) employed nanopore long-read sequencing to analyse cDNAs derived from Drosophila melanogaster germline RNAs. The authors constructed two long-read cDNA libraries from pooled ovaries and testes using a protocol to obtain full-length cDNAs and sequenced them separately. They carefully compared their results with their short-read datasets. Overall, their observations corroborate known patterns of germline-specific expression of certain TEs and provide initial evidence of novel spliced TE transcript isoforms in Drosophila.

Rebollo and colleagues have provided a well-documented and detailed analysis of their results, which will undoubtedly benefit the scientific community. They presented the challenges and limitations of their approach, such as the length of the transcripts, and provided a reproducible analysis workflow that will enable better characterisation of TE expression using long-read technology.

Despite the small number of samples and limited sequencing depth, this pioneering study strikingly demonstrates the potential of long-read sequencing for the quantitative and qualitative analysis of TE transcription, a technology that will facilitate a better understanding of the transposon landscape.

              
References

Lanciano S, Cristofari G (2020) Measuring and interpreting transposable element expression. Nature Reviews Genetics, 21, 721–736. https://doi.org/10.1038/s41576-020-0251-y

Laski FA, Rio DC, Rubin GM (1986) Tissue specificity of Drosophila P element transposition is regulated at the level of mRNA splicing. Cell, 44, 7–19. https://doi.org/10.1016/0092-8674(86)90480-0

Rebollo R, Gerenton P, Cumunel E, Mary A, Sabot F, Burlet N, Gillet B, Hughes S, Oliveira DS, Goubert C, Fablet M, Vieira C, Lacroix V (2024) Identification and quantification of transposable element transcripts using Long-Read RNA-seq in Drosophila germline tissues. bioRxiv, ver.4 peer-reviewed and recommended by PCI Genomics. https://doi.org/10.1101/2023.05.27.542554

Green algae of the genus Coccomyxa (family Trebouxiophyceae) are extremely diverse in their morphology, habitat (i.e., in marine, freshwater, and terrestrial environments) and lifestyle, including free-living and mutualistic forms. Coccomyxa viridis (strain SAG 216–4) is a photobiont in the lichen Peltigera aphthosa, which was isolated in Switzerland more than 70 years ago (cf. SAG, the Culture Collection of Algae at the University of Göttingen, Germany). Despite the high diversity and plasticity in Coccomyxa, integrative taxonomic analyses led Darienko et al. (2015) to propose clear species boundaries. These authors also showed that symbiotic strains that form lichens evolved multiple times independently in Coccomyxa.

Using state-of-the-art sequencing data and bioinformatic methods, including Pac-Bio HiFi and ONT long reads, as well as Hi-C chromatin conformation information, Kraege et al. (2024) generated a high-quality genome assembly for the Coccomyxa viridis strain SAG 216–4. They reconstructed 19 complete nuclear chromosomes, flanked by telomeric regions, totaling 50.9 Mb, plus the plastid and mitochondrial genomes. The performed quality controls leave no doubt of the high quality of the genome assemblies and structural annotations. An interesting observation is the lack of conserved synteny with the close relative Coccomyxa subellipsoidea, but further comparative studies with additional Coccomyxa strains will be required to grasp the genomic evolution in this genus of green algae. This project is framed within the ERGA pilot project, which aims to establish a pan-European genomics infrastructure and contribute to cataloging genomic biodiversity and producing resources that can inform conservation strategies (Formenti et al. 2022). This complete reference genome represents an important step towards this goal, in addition to contributing to future genomic analyses of Coccomyxa more generally.

References

Darienko T, Gustavs L, Eggert A, Wolf W, Pröschold T (2015) Evaluating the species boundaries of green microalgae (Coccomyxa, Trebouxiophyceae, Chlorophyta) using integrative taxonomy and DNA barcoding with further implications for the species identification in environmental samples. PLOS ONE, 10, e0127838. https://doi.org/10.1371/journal.pone.0127838

Formenti G, Theissinger K, Fernandes C, Bista I, Bombarely A, Bleidorn C, Ciofi C, Crottini A, Godoy JA, Höglund J, Malukiewicz J, Mouton A, Oomen RA, Paez S, Palsbøll PJ, Pampoulie C, Ruiz-López MJ, Svardal H, Theofanopoulou C, de Vries J, Waldvogel A-M, Zhang G, Mazzoni CJ, Jarvis ED, Bálint M, European Reference Genome Atlas Consortium (2022) The era of reference genomes in conservation genomics. Trends in Ecology & Evolution, 37, 197–202. https://doi.org/10.1016/j.tree.2021.11.008

Kraege A, Chavarro-Carrero EA, Guiglielmoni N, Schnell E, Kirangwa J, Heilmann-Heimbach S, Becker K, Köhrer K, WGGC Team, DeRGA Community, Schiffer P, Thomma BPHJ, Rovenich H (2024) High quality genome assembly and annotation (v1) of the eukaryotic terrestrial microalga Coccomyxa viridis SAG 216-4. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.07.11.548521