ABSTRACT Age information is fundamental in population biology. In fisheries management, robust and effective stock assessment models depend on accurate estimates of fecundity, survival rates, and other life‐history traits, many of which vary with age. Consequently, reliable age determination is essential for understanding population dynamics and supporting informed management and conservation decisions. Age in fish is generally estimated by counting otolith growth rings, a labor‐ and time‐intensive approach that requires lethal sampling and highly specialized, species‐specific expertise. To supplement current otolith‐based aging efforts, we developed a DNA methylation approach for aging Atlantic Halibut. We conducted whole‐genome methylation sequencing on 106 wild‐caught individuals with otolith‐derived age estimates, ranging from 4 to 29. CpG loci were evaluated as candidate age predictors using elastic net regression and a generalized additive model, with the latter allowing for the incorporation of non‐linear relationships between CpG methylation and age. Age‐associated loci identified by elastic net regression were primarily located in likely subtelomeric and intronic regions. Importantly, inclusion of older individuals in the data set led to changes in the selected CpG sites but not in their respective chromosomal regions, suggesting that it is the methylation patterns in the chromosomes, rather than specific CpG sites, that correlate with age. The sex‐separated generalized additive model (GAM) performed better than the elastic net regression as it exhibited the lowest per‐age median error (MAE < 1 year, or < 2% of the average Atlantic Halibut lifespan). Our framework for epigenetic clock calibration allows for robust, system‐specific clock calibration, which can be used for other non‐model organisms under exploitation and conservation concern.
ABSTRACT Accurate species assignments using (e)DNA (meta)barcoding depend on the reliability of DNA barcode reference libraries. Manual curation can help resolve pseudo‐discordances and identify incongruences, but it is time‐consuming and increasingly difficult to scale as reference sequence data continue to expand. We explored the potential of automated approaches to support the curation of DNA barcode records within discordant Barcode Index Numbers (BINs). Records were mined from the Barcode of Life Data System (BOLD) for marine fish species occurring in the Eastern Atlantic and adjacent waters, and features describing taxonomic consistency, morphospecies‐BIN congruence, and associated metadata were extracted. Within a subset comprising 52,207 records, 3055 species names, and 1138 discordant BINs, each record was manually classified as supported or inconclusive using the taxonomic and metadata information associated with the records as a heuristic guide. We compared a simple rule‐based approach with logistic regression, extreme gradient boosting (XGBoost) and artificial neural networks (ANNs). The rule‐based approach achieved accuracies ranging from 80.4% to 90.9% across the evaluated thresholds. Logistic regression achieved the highest overall accuracy (92.1%), followed closely by ANN (91.7%) and XGBoost (91.4%). These results support the use of machine‐learning approaches to assist the triage of discordant records by helping identify cases that warrant closer human inspection. Such approaches could be integrated into a human‐in‐the‐loop framework that retains manual assessment where taxonomic judgement is required, while helping to scale the screening and curation of rapidly growing DNA barcode reference libraries.
ABSTRACT Environmental DNA (eDNA) metabarcoding is an emerging method that promises to expedite and improve biodiversity surveys by identifying species from the genetic material they shed into the environment. eDNA methods offer many advantages over conventional specimen‐based surveys, but their effectiveness hinges on reference libraries, which for highly biodiverse regions such as the Ecuadorian Amazon are too often incomplete, inconsistently curated and disconnected from morphological voucher specimens needed to reliably identify and revise taxa. To address this gap, we collected approximately 5000 fish specimens and 1500 tissues of an estimated 311 morphologically defined species from Ecuador's Aguarico, Napo and Pastaza river basins, and built a new, rigorously curated, museum voucher–backed 12S reference library spanning 748 barcodes from over 303 species across 12 orders, 46 families and 171 genera. When tested against unknown haplotypes from concurrently collected eDNA samples, the library nearly doubled the proportion identified to species (40.0%, vs. 21.3% using GenBank). It also enabled the empirical estimation of new species‐level barcode thresholds: 0.4% for the full‐length barcode, 0.9% for a general vertebrate mini‐barcode, and 0.6% for a fish‐specific mini‐barcode. By linking museum vouchers, updated taxonomy, and operational scalability, this reference library helps transform eDNA metabarcoding from an exciting possibility to a practical tool for understanding, monitoring and safeguarding Amazonian freshwater biodiversity.
ABSTRACT Species identification is essential for conservation, forest management, and understanding ecological and evolutionary dynamics, such as adaptive introgression and maintenance of species boundaries in hybridizing taxa. Species‐discriminatory marker sets have been shown to be more accurate than morphological identification, especially in hybridizing species complexes, and provide a more affordable alternative to genome‐wide analyses. However, to our knowledge, no species complex exists for which several marker sets are available, let alone have been compared to each other. Moreover, it remains unclear how well marker sets can be applied to additional, closely related species. Here, we compared two independently developed SNP sets, one derived from amplicon sequencing and one from whole‐genome sequencing, for three morphologically similar and hybridizing European white oak species sensu lato ( Quercus robur , Q. petraea , and Q. pubescens ). We applied the SNP sets to 560 samples, including samples of known pure ancestry, controlled crosses, natural populations, and four additional white oak species. Congruency between SNP sets was very high, but species assignment was slightly more accurate for the reference samples used in the development of the respective SNP set. Ancestry coefficients for first‐generation hybrids were more precise with the SNP set based on whole‐genome data. In a natural population, there was limited congruency between SNP sets in quantifying admixture. Notably, the SNP sets were able to identify up to two additional white oak species. Our study highlights the great potential of species‐discriminatory SNP sets in science and practice, while demonstrating that ascertainment bias should not be neglected, and accurate introgression assessments may require genome‐wide analyses.
ABSTRACT The spruce bark beetle Dendroctonus rufipennis (Family: Curculionidae; Subfamily Scolytinae) is a major forest insect pest throughout the transcontinental range of spruce species ( Picea spp.) in North America. Here, we present an annotated, near chromosome‐level, genome assembly of 271 Mb, with 86% of the assembly contained in 16 pseudochromosomes and containing 17,778 predicted gene models. We also annotated 13 protein‐coding genes, 2 rRNAs, and 22 tRNAs in its 19,637 bp mitochondrial genome. In addition, we present the annotated complete nuclear and mitochondrial genomes of an associated endoparasitic nematode, Contortylenchus sp. T'it'q'et (Order: Tylenchida; Family: Allantonematidae). Its nuclear genome assembly was 76.2 Mb, with 99.8% of the assembly contained in nine pseudochromosomes and containing 12,208 predicted gene models. We also annotated 12 protein‐coding genes, 2 rRNAs, and 22 tRNAs in its extremely AT‐rich, 15,509 bp mitochondrial genome. Population genomic analyses revealed broad consistencies with past microsatellite work, supporting the hypothesis of multiple range expansions from glacial refugia. Our analyses also identified alternate modes of population diversification which suggest that both neutral and non‐neutral processes may be shaping current population genetic structure across the spruce beetle range.
