Molecular Ecology Resources最新文献

{"title":"EasyCen: A Lightweight Framework for Centromere Localisation and Repeat-Organisation Profiling in Telomere-to-Telomere Genomes","authors":"Yunyun Lv,&nbsp;Yanping Li,&nbsp;Jia Li,&nbsp;Xidong Mu","doi":"10.1111/1755-0998.70176","DOIUrl":"10.1111/1755-0998.70176","url":null,"abstract":"<p>Accurate identification of centromeres in telomere-to-telomere (T2T) genomes remains difficult due to the rapid evolution of centromeric repeats and their lack of conserved sequence features. In this study, we present EasyCen, a lightweight sequence-based framework for centromere identification and repeat-architecture profiling across various eukaryotes. Rather than relying on repeat annotation or homology, EasyCen recognises centromeres based on recurrent positional features of repetitive DNA. Besides centromere localisation, EasyCen incorporates a repeat-pair profiling module for exploratory characterisation of internal repeat organisation. Benchmarking on <i>Arabidopsis thaliana</i> and <i>Mus musculus</i> showed high accuracy (typically &gt; 85% coordinate overlap with published annotations) and substantially reduced runtime. Cross-species analysis revealed a ‘beads-on-a-string’-like repeat pattern in both mouse and human centromeres, associated with GC- and CpG-rich subdomains. EasyCen performs effectively without pre-existing repeat libraries, making it particularly useful for large, repeat-rich, or non-model genomes. Our analyses further suggest that certain organisational features of centromeric repeats may recur across diverse eukaryotic lineages despite rapid sequence turnover.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148366198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Gene Copies to Cell Numbers: Advancing Quantitative Approaches in Protistan Ecology Using Digital PCR","authors":"Megan Gross,&nbsp;Ulrike Koll,&nbsp;Bettina Sonntag,&nbsp;Thorsten Stoeck","doi":"10.1111/1755-0998.70177","DOIUrl":"10.1111/1755-0998.70177","url":null,"abstract":"<p>Quantifying abundances of unicellular eukaryotes (protists) remains a central challenge in microbial ecology, as methodological differences can strongly influence abundance estimates and ecological interpretation. Although molecular tools have thus far greatly improved our understanding of protists, high rRNA gene copy numbers limit quantitative inferences. Digital PCR (dPCR) has emerged as a promising tool for absolute quantification, yet its application for unicellular eukaryotes and its comparability to established cell-based methods remain insufficiently explored. Here, we develop species-specific dPCR assays for two important freshwater ciliates (<i>Urotricha castalia</i> and <i>Urotricha pseudofurcata</i>) and establish gene copy number correction factors to enable highly accurate quantitative abundance estimates. We assess assay performance using controlled laboratory experiments and apply the approach to environmental samples, directly benchmarking dPCR against catalyzed reporter deposition-FISH (CARD-FISH). Under controlled conditions, dPCR and CARD-FISH yielded comparable accuracy, with dPCR showing superior precision. In field applications, method-dependent differences emerged, reflecting both methodological constraints and biological variability. Notably, dPCR provided an overall higher sensitivity, enabling robust detection of low-abundance taxa. Our results highlight dPCR as a scalable and sensitive approach that, when combined with appropriate correction strategies, represents a significant step towards more reliable molecular quantification of protists. At the same time, differences between methods underscore the value of integrating molecular and microscopy-based approaches. We propose that combining dPCR with tools such as CARD-FISH can offer complementary insights into protist population dynamics. Such integrative frameworks provide a powerful path forward for improving abundance estimates and advancing quantitative microbial ecology.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148366172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Pan-Genome of 1107 Spotted Sea Bass Accessions Reveals Gene Evolution Patterns During Domestication Selection.","authors":"Chong Zhang, Cong Liu, Jinxi Hua, Hailiang Wang, Lingyu Wang, Yonghang Zhang, Yani Dong, Hao Li, Tong Chen, Xinlin Yang, Xin Qi, Haishen Wen, Kaiqiang Zhang, Qing Wang, Yanfei Zhao, Yun Li","doi":"10.1111/1755-0998.70180","DOIUrl":"10.1111/1755-0998.70180","url":null,"abstract":"<p><p>Spotted sea bass (Lateolabrax maculatus) is an ecologically and economically important species that supports a large-scale aquaculture industry in China. However, most farmed populations have not undergone systematic breeding programs and are characterised by undocumented empirical selection. Understanding genetic diversity dynamics and gene evolution patterns for farmed populations is critical for designing appropriate breeding strategies. Here, we assembled a chromosome-level reference genome using HiFi and Hi-C sequencing technologies, resulting in a highly contiguous assembly with a total size of 636.65 Mb and a scaffold N50 of 27.27 Mb. Furthermore, we performed population genomic analyses using 1107 representative wild and farmed individuals. Significant genetic differentiation and reduced genetic diversity were observed in farmed populations relative to wild populations. Pan-genome of 1107 accessions further captured 86.48 Mb of non-reference novel sequences (NRNS) and 206 novel genes absent from the reference genome. Gene presence/absence variation (PAV) analysis revealed that farmed populations harbour fewer genes than wild counterparts, implying gene loss and negative selection during the domestication process. Lost genes were enriched in functions related to immune response and nervous system development, highlighting wild populations as important genetic resources for future breeding programs. Notably, selection signatures and comparative PAV analyses across independent farmed populations revealed parallel domestication effects at both SNP and gene PAV levels, suggesting similar selective pressures despite varied aquaculture practices and domestication histories. Our study provides the first pan-genome of spotted sea bass that deciphers genetic diversity dynamics and gene evolution patterns during domestication selection and establishes valuable genomic resources for sustainable genetic improvement of this species.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":"e70180"},"PeriodicalIF":5.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148576235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic Data Describe Population Structure but Struggle to Estimate Directed Connectivity Networks.","authors":"Camille Sant, Didier Forcioli, Cécile Fauvelot, Jean-Olivier Irisson","doi":"10.1111/1755-0998.70174","DOIUrl":"10.1111/1755-0998.70174","url":null,"abstract":"<p><p>The movement of individuals between fragmented populations, known as population connectivity, plays a crucial role in population persistence, genetic structure and, ultimately, the definition of a species distribution range. Advances in molecular biology have made genomic data readily accessible, even for non-model species, and they are increasingly used to estimate connectivity networks through diverse methods, including gene flow inference, clustering of individuals, and parentage assignment. Yet, no systematic study has evaluated the reliability of these different approaches in accurately estimating connectivity networks. To address this gap, we generated 3240 simulated SNP datasets based on a simple connectivity network of three virtual populations linked by unidirectional migration of known intensity. We then applied a range of analytical tools to these datasets to infer connectivity and evaluated their ability to accurately reconstruct the underlying connectivity network. We compared the accuracy of connectivity network estimates across methods and evaluated how four key parameters (population sizes, migration rates, and the sampling efforts of both individuals and SNPs) influenced their performance. Worryingly, we found that, across all methods, reliable estimates were achievable only under a narrow and largely unrealistic set of conditions: either complete individual sampling (100%) or moderate sampling (30%) coupled with low migration rates (< 10%). With lower sampling proportions (10% of individuals), as is often the case in current practice, none of the tested methods consistently recovered the true connectivity network. Among the tested methods, BA3-SNPs emerged as the most reliable overall, although other approaches may be preferable in cases of highly differentiated populations or very high proportions of sampled individuals. Crucially, this study highlights that increasing the number of SNPs to several thousands, as is often done in population genomic studies of non-model organisms, does not compensate for low proportions of sampled individuals, contrary to common assumptions. These findings raise a strong cautionary flag: without substantially high individual sampling efforts, there is a high risk of drawing misleading conclusions about connectivity, potentially leading to flawed ecological and management decisions. Our results therefore call for a careful reconsideration of current standards in the design of population genomic studies on non-model organisms aimed at inferring connectivity networks.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":"e70174"},"PeriodicalIF":5.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13409678/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148596893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imputation in the Wild: Genome-Wide Robustness and Fine-Scale Limitations of Low-Coverage Genomes in Endangered Species.","authors":"Lucía Mayor-Fidalgo, Enrico Bazzicalupo, Laia Pérez-Sorribes, Laura Soriano, José A Godoy","doi":"10.1111/1755-0998.70179","DOIUrl":"10.1111/1755-0998.70179","url":null,"abstract":"<p><p>Low-coverage whole-genome sequencing (lcWGS) combined with genotype imputation is increasingly being used to generate large genomic datasets at reduced cost, offering a promising alternative for conservation genomics. Here, we use the Iberian lynx (Lynx pardinus), a species with extremely low genetic diversity, genetically differentiated populations, and recent admixture, as a case study to evaluate the performance of imputed lcWGS data for population genomic inferences. We performed a leave-one-out imputation approach with 50 individuals sequenced to high coverage to assess imputation accuracy under different reference panel compositions, sequencing depths, and imputation strategies. We then compared inbreeding, admixture, and demographic history inferences derived from high-coverage and imputed datasets under highly concordant imputation scenarios (r² > 0.98; NRD rate < 0.05). Imputation accuracy substantially improved when using a mixed-ancestry reference panel, a multi-target imputation setting, and an adjusted effective population size parameter, particularly at low sequencing coverages. Genome-wide estimates of inbreeding and ancestry were largely robust. In contrast, fine-scale local genomic patterns were more sensitive to lower levels of imputation accuracy: long runs of homozygosity and ancestry tracts were reliably recovered, whereas shorter segments, which reflect older demographic events, were more error-prone. Consistent with these patterns, recent demographic trajectories were accurately reconstructed, while older effective population size estimates showed greater uncertainty. Overall, our results highlight the importance of validating and optimizing imputation performance in species with complex demographic histories and support lcWGS followed by imputation as a reliable framework for the study of recent demographic events in endangered species.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":"e70179"},"PeriodicalIF":5.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13402980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148589854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effects of Post-Divergence Gene Flow on Simultaneous Divergence Time Testing.","authors":"Michael A Tofflemire, Kevin J Burns, Jeet Sukumaran","doi":"10.1111/1755-0998.70185","DOIUrl":"10.1111/1755-0998.70185","url":null,"abstract":"<p><p>Estimating simultaneous divergence across multiple taxonomic groups from genetic data is a common approach in phylogeographical studies, providing insight into the historical and evolutionary factors shaping species diversification. However, the robustness of divergence time estimates across multiple co-distributed species or population pairs in the face of post-divergence gene flow is often left unaddressed. Here, we use a simulation-based approach to test the robustness of estimating simultaneous divergence within a full-likelihood Bayesian framework when the model assumptions of no gene flow are violated. We generated simulated datasets of multiple population pairs with varying migration rates and estimate shared divergence times with the software package Ecoevolity, comparing them with estimates from population pairs experiencing no migration. Our goal was to identify the threshold at which migration rates begin to bias divergence time estimates, providing insight into the robustness of full-likelihood Bayesian methods under more complex demographic scenarios. We found that simultaneous divergence is incorrectly supported across a broad range of parameter space when assumptions are violated. We suggest that future empirical studies that use simultaneous divergence testing explicitly test for gene flow, or at the very least, explicitly consider the presence, absence, and implications of gene flow in their systems as part of their investigations. We assert that this result-biased support for simultaneous divergence-is just a specific example of a general behaviour when the statistical assumptions of the model are not met or there is insufficient power given the data. We additionally recommend that future studies reorient their research framework to focus on trying to demonstrate non-simultaneous divergence in systems. As such, support for simultaneous divergence between groups should be interpreted as failure to resolve non-simultaneous divergence rather than evidence of true simultaneous divergence.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":"e70185"},"PeriodicalIF":5.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13401500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148589835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Environmental DNA and Bulk DNA Metabarcoding for Assessing Terrestrial Arthropod Diversity Across Three Habitat Types on Guam","authors":"Pritam Banerjee,&nbsp;Samantha Al-Bayer,&nbsp;Jerilyn Calaor,&nbsp;Sven Weber,&nbsp;Natalie R. Graham,&nbsp;Jeremy C. Andersen,&nbsp;Evan P. Economo,&nbsp;Susan Kennedy,&nbsp;Henrik Krehenwinkel,&nbsp;Rosemary G. Gillespie,&nbsp;George K. Roderick,&nbsp;Haldre S. Rogers,&nbsp;Kenneth P. Puliafico","doi":"10.1111/1755-0998.70172","DOIUrl":"https://doi.org/10.1111/1755-0998.70172","url":null,"abstract":"<p>DNA-based methods offer a rapid and cost-effective way for detecting species occurrence and monitoring biodiversity; among them, bulk DNA metabarcoding is well-established, and recently developed environmental DNA (eDNA)-based methods offer a non-lethal alternative. With a goal to develop suitable methods for assessing insect biodiversity for understudied island ecosystems where DNA reference libraries are incomplete, we compared established bulk DNA metabarcoding methods with eDNA across three replicated terrestrial ecosystem types (degraded forest, limestone forest, and grassland) on the island of Guam. Using two mitochondrial COI primer pairs, we performed bulk DNA metabarcoding of standard entomological collection methods (Malaise traps, pan traps, and vegetation beating), and compared the assessment of biodiversity with that from different eDNA sources (flowers, leaves, tree trunks, and spider webs). In our samples, eDNA and bulk DNA metabarcoding both detected a large proportion of overall taxa (OTUs, 86.6% and 60.3%, respectively). Although bulk DNA metabarcoding detected significantly more taxa, eDNA proved to be a reasonable non-lethal alternative. As expected, because of limitations in existing reference databases for understudied systems, species-level identification was achieved for only a few OTUs. Overall, the sampling approach was the dominant driver of arthropod diversity, explaining ~17% of the observed variation, while habitat type accounted for ~4%. Thus, each sampling approach captured some unique diversity and contributed to the complementary effect of maximizing detection. For rapid biodiversity surveys of terrestrial arthropods, we recommend integrating metabarcoding approaches, and in sensitive ecosystems where specimen capture is undesirable, eDNA offers a powerful non-lethal alternative to monitor diversity and community change.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Practical Framework for GT-Seq Panel Optimization","authors":"Chandika RG,&nbsp;Caitlin N. Ott-Conn,&nbsp;Peter T. Euclide,&nbsp;Julie A. Blanchong,&nbsp;Angela Schmoldt,&nbsp;Randy W. DeYoung,&nbsp;Daniel P. Walsh,&nbsp;Wes A. Larson,&nbsp;Emily K. Latch","doi":"10.1111/1755-0998.70169","DOIUrl":"https://doi.org/10.1111/1755-0998.70169","url":null,"abstract":"<p>Genotyping-in-thousands by sequencing (GT-seq) panels are powerful tools in ecological, evolutionary and conservation genomics, yet the optimization process critical for robust and reproducible genotyping remains poorly formalized. Here, we present an iterative workflow for GT-seq panel optimization that emphasizes systematic refinement, quality control and structured decision-making to improve panel performance across diverse populations and study contexts. We illustrate this framework through the development and optimization of a GT-seq panel for white-tailed deer, a widely distributed and ecologically important North American species. From an initial set of 1200 candidate SNPs selected from a commercial microarray (OVSNP60, containing 72,728 SNPs) and prioritized for high heterozygosity, primers were designed for 646 loci. The final optimized panel contains 508 high-performing markers retained after iterative removal of overamplifying primer pairs, adjustment of primer concentrations, PCR conditions and bioinformatic filtering. The overall proportion of SNPs with more than 70% genotype rate increased from 25.5% in the first optimization round to 87.8% in the final round. Consequently, the overall genotype rate increased from 39.4% to 84%. We also identify key quality-control checkpoints and practical criteria to guide panel refinement and ensure consistent performance. By prioritizing optimization as an integral component of GT-seq panel development, this work provides a reproducible framework for generating robust, high-throughput genotyping tools in non-model species and underscores the importance of iterative refinement to maximize data quality and utility.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"pr2-Wormifier: A Bioinformatics Pipeline to Create Custom Reference Databases for Improved Metabarcoding of Marine Protists","authors":"Stefanie Knell,&nbsp;Juliane Romahn,&nbsp;Miklós Bálint","doi":"10.1111/1755-0998.70168","DOIUrl":"10.1111/1755-0998.70168","url":null,"abstract":"<p>Metabarcoding of environmental and ancient environmental DNA (eDNA and sedaDNA) is a powerful approach for studying and monitoring marine communities. However, its effectiveness is limited by the availability of comprehensive and well-curated reference databases, particularly for protists. Here, we introduce pr2-wormifier, a bioinformatics pipeline designed to create customized and improved reference databases for 18S rRNA-based metabarcoding. This pipeline integrates sequences from PR² and NCBI with taxonomic information from the World Register of Marine Species (WoRMS) and AlgaeBase, allowing for refined taxonomic assignments at the genus and species levels. pr2-wormifier enables users to tailor reference databases to specific taxonomic groups or geographic regions, enhancing the resolution and accuracy of biodiversity assessments. We benchmarked the pipeline using a sedimentary ancient DNA dataset from the Baltic Sea, focusing on marine protists, especially ciliates and dinoflagellates. The customized database generated by pr2-wormifier identified more sequences at the genus and species levels than PR² alone, while maintaining taxonomic consistency and quality. Our results demonstrate that pr2-wormifier addresses common limitations of existing databases, such as low taxonomic resolution and missing taxa and facilitates more reliable classification in metabarcoding studies. By enabling the creation of locally relevant, taxonomically curated databases, pr2-wormifier offers a flexible and scalable solution for improving the identification of protists in environmental and paleoenvironmental research.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148300478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wild Pedigree exploreR (wpeR): Streamlined Analysis and Visualization of Wild Pedigrees in Time and Space","authors":"Gregor Simčič,&nbsp;Tomaž Skrbinšek","doi":"10.1111/1755-0998.70171","DOIUrl":"10.1111/1755-0998.70171","url":null,"abstract":"<p>Advances in non-invasive genetic sampling and long-term genetic monitoring programmes have enabled collection of large individual genotype datasets for many wildlife populations, often accompanied by rich field metadata that place the genotyped individuals in time and space. These datasets allow reconstruction of multigenerational pedigrees and have the potential to provide valuable insights into population demography, reproduction, dispersal, social structure and genetic processes. But while the tools for construction of pedigrees keep improving, their interpretation remains challenging. Integrating multigenerational pedigree data with field metadata creates significant complexity, yet specialized tools to facilitate the interpretation of such datasets remain scarce. Here we introduce wild pedigree exploreR (wpeR), an R package designed to simplify exploration, organization and interpretation of complex pedigrees. The package enables users to link reconstructed pedigrees with genetic sample metadata, enabling evaluation of biological plausibility of inferred relationships, but also allowing exploration of other characteristics of individuals and populations in spatial and temporal contexts. wpeR implements a linear workflow through which the pedigree data is imported, formatted, organized into families and integrated with field metadata. The resulting dataset can be visualized through temporal plots that track individuals and families over time, as well as with spatial outputs representing parent–offspring relationships and individual movement patterns as geographic features that can be either directly visualized on maps within R, or exported to be further explored with common GIS tools. wpeR allows exploration of lineage relationships within their ecological context, bridging the gap between statistically reconstructed pedigrees and their biological interpretation. It provides a scalable and flexible framework for analyzing these complex data, providing a practical tool for researchers and managers working with genetic monitoring datasets.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"26 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.70171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148300488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}