Biology subjects

Gargiulo, R.

Publications and source records attributed to Gargiulo, R..

4 recordsLinked to original sources

bioRxiv2026

Towards genetic indicators in ectomycorrhizal fungi: estimating the effective population size

Ectomycorrhizal (EM) fungi are vital to forest ecosystems, supporting tree growth and survival. However, their inclusion in conservation policy and action remains limited and little is known about the status of their genetic diversity, which is essential for their long-term survival and adaptation. The Global Biodiversity Framework adopted a genetic indicator based on the effective population size, Ne, to monitor genetic diversity in all species. To date, it is still uncertain how Ne, a key parameter, can be reliably assessed in species with complex life history traits. Ectomycorrhizal fungi are a highly diverse group of taxa displaying haplodiplontic life cycles with partially clonal reproduction. Here, we review the literature to understand how these life history traits might affect Ne and its estimation in six species of EM fungi. We estimated Ne in 19 populations using eight genetic and genomic datasets from selected studies. We compared Ne estimates using Linkage Disequilibrium (LD) and Sibship Frequency (SF) methods. We tested how Ne estimates change due to partial clonality and genetic structure gradients and whether the number of genetic markers influence the precision of the estimates. We show a systematic bias in Ne estimations when large clones are present and when populations are not correctly delimited. We found both methods are not robust to these factors, which makes them unreliable for conservation assessment purposes in EM fungi. This study provides new perspectives for further research into the links between life history traits and the effective population size of ectomycorrhizal fungi.

genetics↗

bioRxiv2026

High nitrogen deposition is associated with phosphorus-efficient ectomycorrhizas in Europe's Scots pine forests

Atmospheric inorganic nitrogen (N) deposition has been linked to increased tree phosphorus (P) deficiency and shifts in ectomycorrhizal (ECM) fungal community composition across Europe, but the underlying mechanisms remain poorly understood due to the scarcity of species-level studies of fungal physiology at large spatial scales. Here, we characterized ECM communities in nine Scots pine (Pinus sylvestris L.) stands across Europes largest N deposition gradient to gain mechanistic insight into N-driven ECM community shifts, by assessing morpho-physiological traits (i.e. soil exploration types and ECM root-tip level exoenzyme activities involved in organic N and P acquisition) on individual ectomycorrhizas. Our data revealed high functional variation in foraging strategies across species and sites, including within dominant ECM genera (Cortinarius, Elaphomyces, Lactarius, Piloderma, Russula). Shifts in community-level exoenzyme activities along the N deposition gradient were consistent with increasing P limitation, with a buffering effect of phosphomonoesterase activity on host nutritional status (i.e. reduced foliar N:P). These trends were mainly driven by interspecific differences in enzymatic profiles and species turnover along the gradient, rather than intraspecific variation within widespread species. Dominant low-biomass species in high N sites (e.g. E. citrinopapillatus, L. subdulcis, R. ochroleuca) were efficient P-foragers, with some displaying high oxidative activity, potentially hampering soil carbon storage under elevated N loads. These findings highlight the role of ECM species-specific traits in mediating ecosystem processes and can help understand the future of pine forests under chronic N pollution, with potential implications for applied forestry.

ecology↗

bioRxiv2026

MycorrhizaTracer: A BIOINFORMATIC PIPELINE FOR FUNGI AND PLANT CLASSIFICATION OF SANGER DNA SEQUENCES

Processing Sanger DNA sequences remains a routine yet technically demanding step in many biodiversity and ecological studies, particularly when barcoding large numbers of environmental samples. Manual inspection and editing of trace files, DNA sequence alignment, and classification using taxonomic reference databases is time-consuming, inconsistent, and prone to error. These challenges are compounded in studies involving degraded samples, in-house DNA sequencing, under-described taxa, or when investigators have limited access to computational tools. We present MycorrhizaTracer, an open-source, fully automated pipeline for processing and taxonomically classifying large batches of Sanger sequencing chromatograms. We have optimized it for fungal and plant taxa, but it is adaptable across the tree of life. The pipeline performs quality trimming, consensus generation from bidirectional reads, taxonomic classification via BLAST, clustering, optional salvaging of low-quality sequences, and functional annotation of fungal taxa. Designed for scalability and ease of use, MycorrhizaTracer can process thousands of DNA chromatograms in a matter of hours without the need for an HPC. Accuracy and ecological relevance are ensured by features such as gene region-specific taxonomic filtering and sequence-based clustering of unclassified reads. By streamlining trace-to-taxon workflows, MycorrhizaTracer reduces the burden of manual curation, supports reproducibility, and enables efficient recovery of biodiversity data from Sanger sequences - particularly in field-based or resource-limited research contexts.

bioinformatics↗

bioRxiv2023

Estimation of contemporary effective population size in plant populations: limitations of genomic datasets

Effective population size (Ne) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate Ne have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium, in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software programme based on the linkage disequilibrium method, GONE, looks particularly promising to estimate contemporary and recent-historical Ne (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating Ne using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect Ne estimation using the linkage disequilibrium method, such as the occurrence of population structure. We show how accuracy and precision of Ne estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the Ne estimates obtained in GONE for the last generations with the contemporary Ne estimates obtained in the programmes currentNe and NeEstimator.

evolutionary biology↗