Christian Lopezguerra (1) and Gavin M. Douglas (2, 3)

(1) Department of Plant and Microbial Biology; (2) Department of Biological Sciences; (3) Bioinformatics Research Center, North Carolina State University, USA

Climate change and anthropogenic stressors are driving rapid biodiversity loss and dynamic shifts in species ranges (Outhwaite et al. 2022). Partially in response to the decline in biodiversity, the European Reference Genome Atlas (ERGA) has been generating high-quality accessible genome resources, allowing for a more collaborative network and assisting conservation efforts.

One recent target was the violet carpenter bee (Xylocopa violacea; Figure 1), one of the many insects that have shown a recent expansion in their range within Europe. This species is a key pollinator and is therefore of great interest for ecological and agricultural purposes. In addition, anticancer research with melittin variants present in the venom of the violet carpenter bee shows potential (Erkoc et al. 2022; von Reumont et al. 2022). However, genetic analyses have been limited by the prior contig-level assembly of the genome (Koludarov et al. 2023). Developing a high-quality, annotated reference genome for the carpenter bee was the goal of Nash and colleagues’ (2024) research, as part of the European Reference Genome Atlas initiative.

Figure 1: Violet carpenter bee (in Margarida, Spain). Copyright Susanne Vogel, a photographer who made this available on iNaturalist.com. Distributed under a CC-BY 4.0 license.

The authors coupled long and short-read sequencing techniques to create an improved assembly. In particular, they used both short-read RNA-seq and long-read Iso-Seq for gene annotation. They also used Hi-C sequencing to capture chromosome conformational information to aid scaffolding. Their final assembly contains 1,300 scaffolds and has a BUSCO completeness level of 99.75% (Manni et al. 2021), aligning with the standards of the European Reference Genome Atlas. The authors generated a 1.02 gigabase assembly, which was much larger than the expected size of 672 megabases based on k-mer content. The authors partially explain the difference by the high repeat content in the genome, particularly specific 109-mer and 217-mer repeats. Due to this high repeat content, the authors could not assemble full chromosomes but instead produced 17 pseudo-chromosomes comprised of 481.4 megabases (in addition to all other unlocalized scaffolds). 

This high-quality reference genome will be valuable for future studies on population and functional genomics of carpenter bees (Xylocopa). Indeed, this is the first high-quality annotated pseudo-chromosomal genome assembly of the genus Xylocopa, which includes hundreds of other species. It will enable improved investigation into genomic signatures associated with shifting populations. More generally, this reference genome will be useful for comparative analyses with other Hymenoptera species.

References

Erkoc P, von Reumont BM, Lüddecke T, Henke M, Ulshöfer T, Vilcinskas A, Fürst R, Schiffmann S (2022) The pharmacological potential of novel melittin variants from the honeybee and solitary bees against inflammation and cancer. Toxins, 14, 818. https://doi.org/10.3390/toxins14120818

Koludarov I, Velasque M, Senoner T, Timm T, Greve C, Hamadou AB, Gupta DK, Lochnit G, Heinzinger M, Vilcinskas A, Gloag R, Harpur BA, Podsiadlowski L, Rost B, Jackson TNW, Dutertre S, Stolle E, von Reumont BM (2023) Prevalent bee venom genes evolved before the aculeate stinger and eusociality. BMC Biology, 21, 229. https://doi.org/10.1186/s12915-023-01656-5

Manni M, Berkeley MR, Seppey M, Simão FA, Zdobnov EM (2021) BUSCO update: Novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Molecular Biology and Evolution, 38, 4647–4654. https://doi.org/10.1093/molbev/msab199

Nash WJ, Man A, McTaggart S, Baker K, Barker T, Catchpole L, Durrant A, Gharbi K, Irish N, Kaithakottil G, Ku D, Providence A, Shaw F, Swarbreck D, Watkins C, McCartney AM, Formenti G, Mouton A, Vella N, von Reumont BM, Vella A, Haerty W (2024) The genome sequence of the Violet Carpenter Bee, Xylocopa violacea (Linnaeus, 1785): a hymenopteran species undergoing range expansion. Heredity, 133, 381–387. https://doi.org/10.1038/s41437-024-00720-2

Outhwaite CL, McCann P, Newbold T (2022) Agriculture and climate change are reshaping insect biodiversity worldwide. Nature, 605, 97–102. https://doi.org/10.1038/s41586-022-04644-x

von Reumont BM, Dutertre S, Koludarov I (2022) Venom profile of the European carpenter bee Xylocopa violacea: Evolutionary and applied considerations on its toxin components. Toxicon: X, 14, 100117. https://doi.org/10.1016/j.toxcx.2022.100117

The study of genomic variability within and between populations, as well as among species, relies on comparative analyses of homologous positions—sites that share a common evolutionary origin. Homology is inferred through sequence similarity (Reeck et al. 1987). However, the ability to detect homologous regions can be compromised when sequence mismatches accumulate due to mutations, especially when analyzing short DNA fragments, as in short-read sequencing (Li et al. 2008). In the genomic era, accurately mapping homologous DNA fragments to a reference genome is essential for obtaining precise estimates of genetic variability and evolutionary inferences (e.g., Li et al. 2008; Ellegren 2014). However, short-read, high-throughput sequencing often introduces mapping bias, disproportionately favoring the reference allele. This bias distorts allele frequency estimates, ancestry proportions, and genotype likelihoods, impacting downstream analyses (e.g., Günther & Nettelblad 2019; Martiniano et al. 2020).

Mapping bias is particularly problematic in ancient DNA studies, where post-mortem damage exacerbates sequencing errors. DNA fragmentation limits read length, while deamination, causing G to A and C to U transitions, increases mismatches and further complicates homology identification (Dabney & Pääbo 2013). These degradation processes contribute to the misidentification of true variants, confounding evolutionary inferences. Various strategies have been developed to mitigate mapping bias, including the commonly used approach, called pseudo-haploid data, that randomly picks a single read at each analyzed position for each  individual, thereby retaining a single allele at each polymorphic site (Günther & Nettelblad 2019; Barlow et al. 2020). 

Günther et al. (2025) introduce a novel method to correct mapping bias using a genotype likelihood-based approach, incorporating a mapping bias ratio to adjust for reference allele overrepresentation. The method specifically targets known single nucleotide polymorphisms (SNPs) because in population genomic analysis of ancient DNA data, low coverage and post-mortem damage often hinder the ability to identify novel SNPs in most individuals. The analysis focuses on DNA fragmentation, assuming that deamination effects are minimal when considering ascertained SNPs. The proposed method was compared against existing approaches, including pseudo-haploid data and standard genotype likelihood-based probabilistic methods. The evaluation was performed using both empirical and simulated data. For empirical data, low-coverage sequencing data from the 1000 Genomes Project (Finnish in Finland, Japanese in Tokyo, Yoruba in Ibadan, Nigeria populations) was analyzed, while for simulated data, ancient DNA-like datasets were generated using ms-prime (Kelleher et al. 2016), modeling different sequencing depths, divergence times, and reference genome choices. The study assesses the impact of mapping bias on the ratio of reference versus non-reference allele mapping, the accuracy of SNP allele frequency estimates relative to true frequencies, the deviation and variance between estimated and true allele frequencies, population differentiation and the estimation of admixture proportions using supervised and unsupervised methods, considering both genotype likelihoods and genotype calls.

Günther et al. (2025) bring to light that all methods analyzed exhibit minor but systematic reference allele bias. The new corrected genotype likelihood method outperforms the standard genotype likelihood approach in correlating with true allele frequencies, although the pseudo-haploid method still provides the most accurate estimates. Mapping bias also affects ancestry estimation, leading to admixture proportion errors of up to 4%, though this effect is smaller than the 10% discrepancy observed across different inference methods.

The work performed by Günther et al. (2025) provides a rigorous and innovative evaluation of mapping bias in the context of ascertained SNPs, introducing a probabilistic approach that improves bias correction. Unlike non-probabilistic methods such as pseudo-haploid data, the genotype likelihood framework leverages all sequencing reads for each analyzed SNP, and can incorporate additional bias corrections, enhancing its applicability across different sequencing conditions. While probabilistic approaches offer clear advantages in bias correction, they can be less intuitive to interpret compared to traditional genotype calling methods. This study highlights that mapping bias is pervasive across all methods, influencing evolutionary inferences such as selection signals and population differentiation. Although the improvements in allele frequency recovery may seem modest, the genome-wide impact of mapping bias is significant, especially in ancient DNA studies, making bias correction essential for robust evolutionary analyses.

References
 
Barlow A, Hartmann S, Gonzalez J, Hofreiter M, Paijmans JLA. (2020) Consensify: A method for generating pseudohaploid genome sequences from palaeogenomic datasets with reduced error rates. Genes;11(1):50. https://doi.org/10.3390/genes11010050 
 
Dabney J, Meyer M, Pääbo S. (2013) Ancient DNA damage. Cold Spring Harb Perspect Biol. 5(7):a012567. https://doi.org/10.1101/cshperspect.a012567 

Ellegren H. (2014) Genome sequencing and population genomics in non-model organisms. Trends Ecol Evol. 29(1):51-63. https://doi.org/10.1016/j.tree.2013.09.008 

Günther T, Nettelblad C. (2019) The presence and impact of reference bias on population genomic studies of prehistoric human populations. PLoS Genet.15(7):e1008302. https://doi.org/10.1371/journal.pgen.1008302 

Günther T., Goldberg A., Schraiber J. G.  (2025) Estimating allele frequencies, ancestry proportions and genotype likelihoods in the presence of mapping bias. bioRxiv, ver. 5 peer-reviewed and recommended by PCI Genomics https://doi.org/10.1101/2024.07.01.601500 

Kelleher J., Etheridge A. M., McVean G. (2016) Efficient coalescent simulation and genealogical analysis for large sample sizes. PLoS computational biology, 12(5):e1004842. https://doi.org/10.1371/journal.pcbi.1004842

Li H, Ruan J, Durbin R. (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res. 18(11):1851-8. https://doi.org/10.1101/gr.078212.108 

Reeck GR, de Haën C, Teller DC, Doolittle RF, Fitch WM, Dickerson RE, et al. (1987) "Homology" in proteins and nucleic acids: a terminology muddle and a way out of it. Cell. 50 (5): 667. https://doi.org/10.1016/0092-8674(87)90322-9 

Oriowo et al. (2024) offer a thorough and meticulously conducted study that makes a substantial contribution to our understanding of the Eurasian minnow (Phoxinus phoxinus), particularly in terms of its genetic diversity, structural variations, and evolutionary adaptations. The authors have achieved an impressive feat by generating an annotated haplotype-phased, chromosome-level genome assembly (2n = 50). This was accomplished through the integration of high-fidelity long reads with chromosome conformation capture data (Hi-C), resulting in a highly complete and accurate genome assembly. The assembly is characterized by a haploid size of 940 Megabase pairs (Mbp) for haplome one and 929 Mbp for haplome two, with scaffold N50 values of 36.4 Mb and 36.6 Mb, respectively. These metrics, alongside BUSCO scores of 96.9% and 97.2%, highlight the high quality of the genome, making it a robust foundation for further genetic exploration and analyses.

The study’s findings are both novel and significant, providing deep insights into the genetic architecture of P. phoxinus. The authors report heterozygosity rate of 1.43% and a high repeat content of approximately 54%, primarily consisting of DNA transposons. These transposons play a crucial role in genome rearrangements and variations, contributing to the species' adaptability and evolution (Bourque et al. 2018). The research also identifies substantial structural variations within the genome, including insertions, deletions, inversions, and translocations (Oriowo et al. 2024). Beyond these findings, the genome annotation is exceptionally comprehensive, containing 30,980 mRNAs and 23,497 protein-coding genes. The study’s gene family evolution analysis, which compares the P. phoxinus proteome to that of ten other teleost species, reveals immune system gene families that favor histone-based disease prevention mechanisms over NLR-based immune responses. This provides new insight into the evolutionary strategies that have emerged in P. phoxinus, enabling its survival in its environment. Moreover, the demographic analysis conducted in the study reveals historical fluctuations in the effective population size of P. phoxinus, likely correlated with past climatic changes, offering insights into the species' evolutionary history.

This annotated and phased reference genome not only serves as a crucial resource for resolving taxonomic complexities within the genus Phoxinus but also highlights the importance of haplotype-phased assemblies in understanding genetic diversity, particularly in species characterized by high heterozygosity. The authors have delivered a study that is methodologically sound, richly detailed, and highly relevant to the field. The study represents a valuable and impactful contribution to the scientific community, offering resources and knowledge that will likely inform future research in the field.

References

Bourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, Imbeault M, Izsvák Z, Levin HL, Macfarlan TS, Mager DL, Feschotte C (2018) Ten things you should know about transposable elements. Genome Biology, 19, 199. https://doi.org/10.1186/s13059-018-1577-z

Oriowo TO, Chrysostomakis I, Martin S, Kukowka S, Brown T, Winkler S, Myers EW, Böhne A, Stange M (2024) A chromosome-level, haplotype-resolved genome assembly and annotation for the Eurasian minnow (Leuciscidae: Phoxinus phoxinus) provide evidence of haplotype diversity. bioRxiv, ver. 6 peer-reviewed and recommended by PCI Genomics https://doi.org/10.1101/2023.11.30.569369

When discussing the Earth BioGenome Project with scientists and potential funding agencies, one common question is: why sequence everything? Whether sequencing a subset would be more optimal is not an unreasonable question given what we know about the mathematics of importance and Pareto’s 80:20 principle, that 80% of the benefits can come from 20% of the effort. However, one must remember that this principle is an observation made in hindsight and selecting the most effective 20% of experiments is difficult. As an example, few saw great applied value in comparative genomic analysis of the archaea Haloferax mediterranei, but this enabled the discovery of CRISPR/Cas9 technology (1). When discussing whether or not to sequence all life on our planet, smaller countries such as the Faroe Islands are seldom mentioned. 
 
Mikalsen and co-authors (2) provide strong arguments to appreciate, investigate and steward genetic diversity, from a Faroese viewpoint, a fishery viewpoint, and a global viewpoint. As readers, we learn to cherish the Faroe Islands, the Faroese, and perhaps by extension all of nature and the people of the world. The manuscript describes the proposed Faroese participation in the European Reference Genome Atlas (ERGA) consortium through Gen@FarE – the Genome Atlas of Faroese Ecology. Gen@FarE aims to: i) generate high-quality reference genomes for all eukaryotes on the islands and in its waters; ii) establish population genetics of all species of commercial or ecological interest; and iii) establish a “databank” for all Faroese species with citizen science tools for participation.

In the background section of the manuscript, the authors argue that as caretakers of the earth (and responsible for the current rapid decrease in biodiversity), humanity must be aware of the biodiversity and existing genetic diversity, to protect these for future generations. Thus, it is necessary to have reference genomes for as many species as possible, enabling estimation of population sizes and gene flow between ecosystem locations. Without this the authors note that “…it is impossible to make relevant management plans for a species, an ecosystem or a geographical area…”. Gen@FarE is important. The Faroe nation has a sizable economic zone in the North Atlantic and large fisheries. In terms of biodiversity and conservation, the authors list some species endemic to other Faroe islands, especially sea birds. The article discusses ongoing marine environmental-DNA-based monitoring programs that started in 2018, and how new reference genome databases will help these efforts to track and preserve marine biodiversity. They point to the lack of use of population genomics information for Red List decisions on which species are endangered, and the need for these techniques to inform sustainable harvesting of fisheries, given collapses in critical food species such as Northwest Atlantic cod and herring. In one example, they highlight how the herring chromosome 12 inversion contains a “supergene” collection of tightly linked genes associated with ecological adaptation. Genetic tools may also help enable the identification and nurturing of feeding grounds for young individuals. Critically, the Faroe Islands have a significant role to play in protecting the millions of tons of seafood caught annually upon which humanity relies. As the authors note, population genomics based on high-quality reference sequences is “likely the best tool” to monitor and protect commercial fisheries. There is an important section discussing the role of interactions between visible and “invisible" species in the marine ecosystem on which we all depend. Examples of “invisible” species include a wide range of morphologically similar planktonic algae, and invasive species transported by ballast water or ship hulls.​ As biologists, I believe we forget that our population studies of life on the earth have so far been mostly in the dark. Gen@FarE is but one light that can be switched on. 

The authors conclude by discussing Gen@FarE plans for citizen science and education, perhaps the most important part of this project if humanity is to learn to cherish and care for the earth. Where initiatives such as the Human Genome Project did not need the collaborative efforts of the world for sample access, the Earth BioGenome Project most certainly does. In the same way, at a smaller scale, Gen@FarE requires the support and determination of the Faroese. 
 

References    

1          Mojica, F. J., Díez-Villaseñor, C. S., García-Martínez, J. & Soria, E. Intervening sequences of regularly spaced prokaryotic repeats derive from foreign genetic elements. J Mol Evol 60, 174-182 (2005).

2          Mikalsen, S-O., Hjøllum, J. í., Salter, I., Djurhuus, A. & Kongsstovu, S. í. The need of decoding life for taking care of biodiversity and the sustainable use of nature in the Anthropocene – a Faroese perspective. EcoEvoRxiv (2024), ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.32942/X21S4C

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