Biology subjects

Ronquist, F.

Publications and source records attributed to Ronquist, F..

16 recordsLinked to original sources

bioRxiv2026

Accuracy of occurrence and abundance estimates from insect metabarcoding

1. DNA metabarcoding--high-throughput sequencing of barcode regions from bulk samples--has become a key tool for insect biodiversity assessment. Yet, how methodological choices affect the accuracy of metabarcoding data remains insufficiently explored. In this paper, we ask: (1) How does the lysis method (non-destructive lysis vs. destructive homogenization) affect community recovery? (2) How comprehensively does metabarcoding capture species richness? (3) To what extent can spike-ins improve abundance estimates? (4) How accurately can species abundances be estimated? 2. We evaluated the accuracy of insect metabarcoding using 4,749 bulk samples from a large-scale biodiversity survey subjected to mild lysis. Of these samples, 856 were also homogenized, allowing a systematic comparison of the effect of alternative treatments. To potentially improve abundance estimates, we added six biological spike-ins (i.e., foreign insects) to all samples, and two synthetic spike-ins (artificial DNA fragments) to the homogenization treatment. In addition, we established the contents of 15 samples by individually barcoding all specimens, enabling direct assessment of occurrence and abundance estimates. 3. Our results revealed consistent differences between destructive and non-destructive treatments. While both methods reliably detected the majority of species, small and soft-bodied taxa were more often recovered after mild lysis than after homogenization, while the reverse was true for heavily sclerotized, hairy, and large taxa. Using biological spike-ins for calibration reduced the variance in read numbers per specimen considerably, especially in homogenized samples, while synthetic spike-ins were less effective. In a Bayesian analysis, where species data were matched to the best-fitting spike-in calibration curve, accurate abundance estimates (+/-1 individual) were obtained for 72.9% of species occurrences. 4. Our results show that it is possible to obtain reasonably accurate abundance estimates from metabarcoding data, and that mild lysis and homogenization result in different taxon-specific biases in terms of occurrence data, with neither method outperforming the other. Accuracy is improved by homogenization rather than mild lysis of samples, and by the use of biological rather than synthetic spike-ins. Together, these findings provide a major step towards robust, quantitative biodiversity monitoring using DNA-metabarcoding.

zoology↗

bioRxiv2024

HAPP: High-Accuracy Pipeline for Processing deep metabarcoding data

We introduce HAPP, a high-accuracy pipeline for processing deep metabarcoding data, leveraging data richness to enhance the signal-to-noise-ratio. Starting with denoised amplicon sequence variants, the pipeline consists of four steps: (1) additional chimera removal, using UCHIME and a strict sample-based approach; (2) taxonomic annotation, combining k-mer matching (SINTAX) to a reference library with phylogenetic placement (EPA-NG) on a reference tree; (3) OTU clustering using SWARM, an open-source algorithm with precision and recall comparable to RESL used in circumscribing BOLD BINs; and (4) noise filtering (NUMTs and sequencing errors), using a new algorithm introduced here, NEEAT, which combines "echo" signals across samples with detection of unusual evolutionary signatures among clusters with similar DNA sequences. HAPP computations are parallelized across taxa, making analyses tractable on very large datasets. The performance of HAPP was validated through extensive benchmarks, involving CO1 data from BOLD and Malaise trap data, demonstrating significant improvements over the state of the art.

bioinformatics↗

bioRxiv2024

High-throughput biodiversity surveying sheds new light on the brightest of insect taxa

Sampling of species-rich taxa followed by DNA metabarcoding is quickly becoming a popular high-throughput method for biodiversity inventories. Unfortunately, we know little about its accuracy and efficiency, as the results mostly pertain to poorly-known organism groups in underexplored environments or regions of the world. Here we ask what an extensive sampling effort based on Malaise trapping and metabarcoding can tell us about the lepidopteran fauna of Sweden - one of the best-understood insect taxa in one of the most-surveyed countries of the world. Specifically, we deployed 197 Malaise traps for a single year across Sweden in a systematic sampling design, then metabarcoded the resulting 4,749 bulk samples, and compared the results to existing data sources. We detected more than half (1,535) of the 2,990 lepidopteran species ever recorded as occurring in Sweden, and 323 species not reported during the sampling period by other data providers. Full-length barcoding of individual specimens confirmed three new species for the country and extensive range extensions for two species. It also corroborated eight genetically distinct COI variants that may represent new species to science, one of which has since been described. Most of the new records are for small and inconspicuous species and poorly surveyed regions, suggesting that they represent previously overlooked components of the fauna. Our findings, corroborated by independent metagenomic analyses, show that DNA metabarcoding can be a highly efficient and accurate method of biodiversity sampling, to the extent that it can generate significant new discoveries even for the most well-known of insect faunas.

zoology↗

bioRxiv2024

Biotic and abiotic drivers of ecosystem functioning differ between a temperate and a tropical region

Any single ecosystem will provide many ecosystem functions. Whether these functions tend to increase in concert or trade off against each other is a question of much current interest. Equally topical are the drivers behind ecosystem function rates. Yet, we lack large-scale systematic studies that investigate how abiotic factors can directly or indirectly -- via effects on biodiversity -- drive ecosystem functioning. In this study, we assessed the impact of climate, landscape and biotic community on ecosystem functioning and multifunctioning in the temperate and tropical zone, and investigated potential trade-offs among ecosystem functions in both zones. To achieve this, we measured a diverse set of insect-related ecosystem functions -- including herbivory, seed dispersal, predation, decomposition and pollination -- at 50 sites across Madagascar and 171 sites across Sweden, and characterized the insect community at each site using Malaise traps. We used structural equations models to infer causality of the effects of climate, landscape, and biodiversity on ecosystem functioning. For the temperate zone, we found that abiotic factors were more important than biotic factors in driving ecosystem functioning, while in the tropical zone, effects of biotic drivers were most pronounced. In terms of trade-offs among functions, in the temperate zone, only seed dispersal and predation were positively correlated, while all other functions were uncorrelated. By contrast, in the tropical zone, most ecosystem functions increased in concert, highlighting that tropical ecosystems can simultaneously provide a diverse set of functions. These correlated functions in Madagascar could for the most part be explained by similar responses to local climate, landscape, and biota. Our study suggests that the functioning of temperate and tropical ecosystems differs fundamentally in patterns and drivers. Without a better understanding of these differences, it will be impossible to correctly predict shifts in ecosystem functioning in response to environmental disturbances. To identify global patterns and drivers of ecosystem functioning, we will next need replicate sampling across biomes - as here achieved for two regions, thus paving the road and setting the baseline expectations.

ecology↗

bioRxiv2023

Skyline fossilized birth-death model is robust to violations of sampling assumptions in total-evidence dating

Several total-evidence dating studies under the fossilized birth-death (FBD) model have produced very old age estimates, which are not supported by the fossil record. This phenomenon has been termed "deep root attraction (DRA)". For two specific data sets, involving divergence time estimation for the early radiations of ants, bees and wasps (Hymenoptera) and of placental mammals (Eutheria), it has been shown that the DRA effect can be greatly reduced by accommodating the fact that extant species in these trees have been sampled to maximize diversity, so called diversified sampling. Unfortunately, current methods to accommodate diversified sampling only consider the extreme case where it is possible to identify a cut-off time such that all splits occurring before this time are represented in the sampled tree but none of the younger splits. In reality, the sampling bias is rarely this extreme, and may be difficult to model properly. Similar modeling challenges apply to the sampling of the fossil record. This raises the question of whether it is possible to find dating methods that are more robust to sampling biases. Here, we show that the skyline FBD (SFBD) process, where the diversification and fossil-sampling rates can vary over time in a piecewise fashion, provides age estimates that are more robust to inadequacies in the modeling of the sampling process and less sensitive to DRA effects. In the SFBD model we consider, rates in different time intervals are either considered to be independent and identically distributed, or assumed to be autocorrelated following an Ornstein-Uhlenbeck (OU) process. Through simulations and reanalyses of the Hymenoptera and Eutheria data, we show that both variants of the SFBD model unify age estimates under random and diversified sampling assumptions. The SFBD model can resolve DRA by absorbing the deviations from the sampling assumptions into the inferred dynamics of the diversification process over time. Although this means that the inferred diversification dynamics must be interpreted with caution, taking sampling biases into account, we conclude that the SFBD model represents the most robust approach available currently for addressing DRA in total-evidence dating.

evolutionary biology↗

bioRxiv2022

Phylogenomic Analysis of Protein-Coding Genes Resolves Complex Gall Wasp Relationships

The phylogeny of gall wasps (Cynipidae) and their parasitic relatives has attracted considerable attention in recent years. The family is now widely recognized to fall into thirteen natural lineages, designated tribes, but the relationships among them have remained elusive. This has stymied any progress in understanding how cynipid gall inducers evolved from insect parasitoids, and what role inquilinism (development as a herbivore inside galls induced by other cynipids) might have played in this transition. A recent analysis of ultraconserved elements (UCEs) represents the first attempt at resolving these questions using phylogenomics. Here, we present the first analysis based on protein-coding sequences from genome and transcriptome assemblies. To address potential problems due to model misfit, we focus on models that accommodate site-specific amino-acid profiles and that are less sensitive than standard models to long-branch attraction. Our results show that the Cynipidae as previously circumscribed are not monophyletic. Specifically, the Paraulacini and a clade formed by Diplolepidini + Pediaspidini both fall outside a core clade (Cynipidae s. str.), which is more closely related to Figitidae. This result is robust to the exclusion of long-branch taxa that could potentially mislead the analysis, and it is consistent with the UCE analysis. Given this, we propose that the Cynipidae be divided into three families: the Paraulacidae, Diplolepididae and Cynipidae (s. str.). Our results suggest that the Eschatocerini are the sister group of the remaining Cynipidae (s. str.). Within the latter, our results are consistent with the UCE analysis but place two additional tribes: (1) the Aylacini (s. str.), more closely related to the oak gall wasps (Cynipini) and some of their inquilines (Ceroptresini) than to other herb gallers (Aulacideini and Phanacidini); and (2) the Qwaqwaiini, likely the sister group to Synergini (s. str.) + Rhoophilini. Several alternative scenarios for the evolution of cynipid life histories are compatible with the relationships suggested by our analysis, but all are complex and require multiple shifts between parasitoids, inquilines and gall inducers. Linking the different types of life-history transitions to specific genomic signatures may be one of the best ways of differentiating among these alternative scenarios. Our study represents the first step towards enabling such analyses.

evolutionary biology↗

bioRxiv2022

Optimizing insect metabarcoding using replicated mock communities

Metabarcoding (high-throughput sequencing of marker gene amplicons) has emerged as a promising and cost-effective method for characterizing insect community samples. Yet, the methodology varies greatly among studies and its performance has not been systematically evaluated to date. In particular, it is unclear how accurately metabarcoding can resolve species communities in terms of presence-absence, abundances, and biomass. Here we use mock community experiments and a simple probabilistic model to evaluate the performance of different metabarcoding protocols. Specifically, we ask four questions: (Q1) How consistent are the recovered community profiles across replicate mock communities?; (Q2) How does the choice of lysis buffer affect the recovery of the original community?; (Q3) How are community estimates affected by differing lysis times and homogenization?; and (Q4) Is it possible to obtain adequate species abundance estimates through the use of biological spike-ins? We show that estimates are quite variable across community replicates. In general, a mild lysis protocol is better at reconstructing species lists and approximate counts, while homogenization is better at retrieving biomass composition. Tiny insects are more likely to be detected in lysates, while some tough species require homogenization to be detected. Results are less consistent across biological replicates for lysates than for homogenates. Some species are associated with strong PCR amplification bias, which complicates the reconstruction of species counts. Yet, with adequate spike-in data, species abundance can be determined with roughly 40% standard error for homogenates, and with roughly 50% standard error for lysates, under ideal conditions. In the latter case, however, this often requires species-specific reference data, while spike-in data generalizes better across species for homogenates. We conclude that a non-destructive, mild lysis approach shows the highest promise for presence/absence description of the community, while also allowing future morphological or molecular work on the material. However, homogenization protocols perform better for characterizing community composition, in particular in terms of biomass.

ecology↗

bioRxiv2021

Large-scale Integrative Taxonomy (LIT): resolving the data conundrum for dark taxa

New, rapid, accurate, scalable, and cost-effective species discovery and delimitation methods are needed for tackling "dark taxa", that we here define as clades for which <10% of all species are described and the estimated diversity exceeds 1000 species. Species delimitation for these taxa should be based on multiple data sources ("integrative taxonomy") but collecting multiple types of data risks impeding a discovery process that is already too slow. We here develop explicit methods to avoid this by applying Large-scale Integrative Taxonomy (LIT). Preliminary species hypotheses are generated based on inexpensive data that are obtained quickly and cost-effectively in a technical exercise. The validation step is then based on a more expensive type of data that are only obtained for specimens selected based on objective criteria. We here use this approach to sort 18 000 scuttle flies (Diptera: Phoridae) from Sweden into 315 preliminary species hypotheses based on NGS barcode (313bp) clusters. These clusters were subsequently tested with morphology and used to develop quantitative indicators for predicting which barcode clusters are in conflict with morphospecies. For this purpose, we first randomly selected 100 clusters for in-depth validation with morphology. Afterwards, we used a linear model to demonstrate that the best predictors for conflict between barcode clusters and morphology are maximum p-distance within the cluster and cluster stability across different clustering thresholds. A test of these indicators using the 215 remaining clusters reveals that these predictors correctly identify all clusters that conflict with morphology. The morphological validation step in our study involved only 1 039 specimens (5.8% of all specimens), but a newly proposed simplified protocol would only require the study of 915 (5.1%: 2.5 specimens per species), as we show that clusters without signatures of incongruence can be validated by only studying two specimens representing the most divergent haplotypes. To test the generality of our results across different barcode clustering techniques, we establish that the levels of conflict are similar across Objective Clustering (OC), Automatic Barcode Gap Discovery (ABGD), Poisson Tree Processes (PTP) and Refined Single Linkage (RESL) (used by Barcode of Life Data System (BOLD) to assign Barcode Index Numbers (BINs)). OC and ABGD achieved a maximum congruence score with morphology of 89% while PTP was slightly less effective (84%). RESL could only be tested for a subset of the specimens because the algorithm is not public. BINs based on 277 of the original 1 714 haplotypes were 86% congruent with morphology while the values were 89% for OC, 74% for PTP, and 72% for ABGD.

evolutionary biology↗

bioRxiv2021

Evolution of butterfly-plant networks over time, as revealed by Bayesian inference of host repertoire

The study of herbivorous insects underpins much of the theory that concerns the evolution of species interactions. In particular, Pieridae butterflies and their host plants have served as a model system for studying evolutionary arms-races. To learn more about the coevolution of these two clades, we reconstructed ancestral ecological networks using stochastic mappings that were generated by a phylogenetic model of host-repertoire evolution. We then measured if, when, and how two ecologically important structural features of the ancestral networks (modularity and nestedness) evolved over time. Our study shows that as pierids gained new hosts and formed new modules, a subset of them retained or recolonized the ancestral host(s), preserving connectivity to the original modules. Together, host-range expansions and recolonizations promoted a phase transition in network structure. Our results demonstrate the power of combining network analysis with Bayesian inference of host-repertoire evolution to understand changes in complex species interactions over time.

ecology↗

bioRxiv2020

Probabilistic programming: a powerful new approach to statistical phylogenetics

Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabilistic graphical models, but this formalism can only partly express phylogenetic problems. Here we show that universal probabilistic programming languages (PPLs) solve the expressivity problem, while still supporting automated generation of efficient inference algorithms. To prove the latter point, we develop automated generation of sequential Monte Carlo (SMC) algorithms for PPL descriptions of arbitrary biological diversification (birth-death) models. SMC is a new inference strategy for these problems, supporting both parameter inference and efficient estimation of Bayes factors that are used in model testing. We take advantage of this in automatically generating SMC algorithms for several recent diversification models that have been difficult or impossible to tackle previously. Finally, applying these algorithms to 40 bird phylogenies, we show that models with slowing diversification, constant turnover and many small shifts generally explain the data best. Our work opens up several related problem domains to PPL approaches, and shows that few hurdles remain before these techniques can be effectively applied to the full range of phylogenetic models.

evolutionary biology↗

bioRxiv2020

The effect of ethanol concentration on the preservation of insects for biodiversity studies

1. Traditionally, insects collected for scientific purposes have been dried and pinned, or preserved in 70 % ethanol. Both methods preserve taxonomically informative exoskeletal structures well but are suboptimal for preserving DNA. Highly concentrated ethanol (95 - 100 %), preferred as a DNA preservative, has generally been assumed to make specimens brittle and prone to breaking. However, systematic studies on the correlation between ethanol concentration and specimen preservation are lacking. 2. We tested how preservative ethanol concentration in combination with different sample handling regimes affect the integrity of seven insect species representing four orders, and differing substantially in the level of sclerotization. After preservation and treatments (various levels of disturbance), we counted the number of appendages (legs, wings, antennae, heads) that specimens had lost. Additionally, we assessed the preservation of DNA after long-term storage by comparing the ratio of PCR amplicon copy numbers to an added artificial standard. 3. We found that high ethanol concentrations indeed induce brittleness in insects. However, the magnitude and nature of the effect varied strikingly among species. In general, ethanol concentrations at or above 90 % made the insects more brittle, but for species with robust, thicker exoskeletons, this did not translate to an increased loss of appendages. Neither freezing nor drying the insects after immersion in ethanol had a negative effect on the retention of appendages. We also found that DNA preserves less well at lower ethanol concentrations when stored at room temperature for an extended period. However, the magnitude of the effect varies among species; the concentrations at which the number of COI amplicon copies relative to the standard was significantly decreased compared to 95 % ethanol ranged from 90 % to as low as 50 %. 4. While higher ethanol concentrations positively affect long-term DNA preservation, there is a clear trade-off between preserving insects for morphological examination and genetic analysis. The optimal ethanol concentration for the latter is detrimental for the former, and vice versa. These trade-offs need to be considered in large insect biodiversity surveys and other projects aiming to combine molecular work with traditional morphology-based characterization of collected specimens.

ecology↗

bioRxiv2019

Using Parsimony-Guided Tree Proposals to Accelerate Convergence in Bayesian Phylogenetic Inference

Sampling across tree space is one of the major challenges in Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) algorithms. Standard MCMC tree moves consider small random perturbations of the topology, and select from candidate trees at random or based on the distance between the old and new topologies. MCMC algorithms using such moves tend to get trapped in tree space, making them slow in finding the globally most probable trees (known as convergence) and in estimating the correct proportions of the different types of them (known as mixing). Here, we introduce a new class of moves, which propose trees based on their parsimony scores. The proposal distribution derived from the parsimony scores is a quickly computable albeit rough approximation of the conditional posterior distribution over candidate trees. We demonstrate with simulations that parsimony-guided moves correctly sample the uniform distribution of topologies from the prior. We then evaluate their performance against standard moves using six challenging empirical datasets, for which we were able to obtain accurate reference estimates of the posterior using long MCMC runs, a mix of topology proposals, and Metropolis coupling. On these datasets, ranging in size from 357 to 934 taxa and from 1,740 to 5,681 sites, we find that single chains using parsimony-guided moves usually converge an order of magnitude faster than chains using standard moves. They also exhibit better mixing, that is, they cover the most probable trees more quickly. Our results show that tree moves based on quick and dirty estimates of the posterior probability can significantly outperform standard moves. Future research will have to show to what extent the performance of such moves can be improved further by finding better ways of approximating the posterior probability, taking the trade-off between accuracy and speed into account.

evolutionary biology↗

bioRxiv2019

Completing Linnaeus’s Inventory of the Swedish Insect Fauna: Only 5000 Species Left

Despite more than 250 years of taxonomic research, we still have only a vague idea about the true size and composition of the faunas and floras of the planet. Many biodiversity inventories provide limited insight because they focus on a small taxonomic subsample or a tiny geographic area. Here, we report on the size and composition of the Swedish insect fauna, thought to represent roughly half of the diversity of multicellular life in one of the largest European countries. Our results are based on more than a decade of data from the Swedish Taxonomy Initiative and its massive inventory of the countrys insect fauna, the Swedish Malaise Trap Project The fauna is considered one of the best known in the world, but the initiative has nevertheless revealed a surprising amount of hidden diversity: more than 3,000 new species (301 new to science) have been documented so far. Here, we use three independent methods to analyze the true size and composition of the fauna at the family or subfamily level: (1) assessments by experts who have been working on the most poorly known groups in the fauna; (2) estimates based on the proportion of new species discovered in the Malaise trap inventory; and (3) extrapolations based on species abundance and incidence data from the inventory. For the last method, we develop a new estimator, the combined non-parametric estimator, which we show is less sensitive to poor coverage of the species pool than other popular estimators. The three methods converge on similar estimates of the size and composition of the fauna, suggesting that it comprises around 33,000 species. Of those, 8,600 (26%) were unknown at the start of the inventory and 5,000 (15%) still await discovery. We analyze the taxonomic and ecological composition of the estimated fauna, and show that most of the new species belong to Hymenoptera and Diptera groups that are decomposers or parasitoids. Thus, current knowledge of the Swedish insect fauna is strongly biased taxonomically and ecologically, and we show that similar but even stronger biases have distorted our understanding of the fauna in the past. We analyze latitudinal gradients in the size and composition of known European insect faunas and show that several of the patterns contradict the Swedish data, presumably due to similar knowledge biases. Addressing these biases is critical in understanding insect biomes and the ecosystem services they provide. Our results emphasize the need to broaden the taxonomic scope of current insect monitoring efforts, a task that is all the more urgent as recent studies indicate a possible worldwide decline in insect faunas.

ecology↗

bioRxiv2019

Bayesian inference of ancestral host-parasite interactions under a phylogenetic model of host repertoire evolution

Intimate ecological interactions, such as those between parasites and their hosts, may persist over long time spans, coupling the evolutionary histories of the lineages involved. Most methods that reconstruct the coevolutionary history of such associations make the simplifying assumption that parasites have a single host. Many methods also focus on congruence between host and parasite phylogenies, using cospeciation as the null model. However, there is an increasing body of evidence suggesting that the host ranges of parasites are more complex: that host ranges often include more than one host and evolve via gains and losses of hosts rather than through cospeciation alone. Here, we develop a Bayesian approach for inferring coevolutionary history based on a model accommodating these complexities. Specifically, a parasite is assumed to have a host repertoire, which includes both potential hosts and one or more actual hosts. Over time, potential hosts can be added or lost, and potential hosts can develop into actual hosts or vice versa. Thus, host colonization is modeled as a two-step process, which may potentially be influenced by host relatedness or host traits. We first explore the statistical behavior of our model by simulating evolution of host-parasite interactions under a range of parameters. We then use our approach, implemented in the program RevBayes, to infer the coevolutionary history between 34 Nymphalini butterfly species and 25 angiosperm families.

evolutionary biology↗

bioRxiv2019

Establishing insect community composition using metabarcoding of soil samples, and preservative ethanol and homogenate from Malaise trap catches: surprising inconsistencies between methods.

DNA metabarcoding allows the analysis of insect communities faster and more efficiently than ever before. However, metabarcoding can be conducted through several alternative approaches, and the consistency of results across methods has rarely been studied. We compare the results obtained by DNA metabarcoding of the same communities using two different markers - COI and 16S - and three different sampling methods - homogenized Malaise trap samples (homogenate), preservative ethanol from the same samples, and soil samples. Our results indicate that COI and 16S offer partly complementary information on Malaise trap samples, with each marker detecting a significant number of species not detected by the other. Different sampling methods offer highly divergent estimates of community composition. The community recovered from preservative ethanol of Malaise trap samples is quite distinct from that recovered from homogenate. Small and weakly sclerotized insects tend to be overrepresented in ethanol, with some exceptions that could be related to taxon-specific traits. For soil samples, highly degenerate COI primers pick up large amounts of non-target DNA and only 16S provides adequate analyses of insect diversity. However, even with 16S, very little overlap in MOTU content was found between the trap and the soil samples. Our results demonstrate that no metabarcoding approach is all-comprehensive in itself. For instance, DNA extraction from preservative ethanol is not a valid replacement for destructive bulk extraction but a complement. In future metabarcoding studies, both should ideally be used together to achieve comprehensive representation of the target community.

ecology↗

bioRxiv2018

New mitochondrial primers for metabarcoding of insects, designed and evaluated using in silico methods

Insect metabarcoding has been mainly based on PCR amplification of short fragments within the barcoding region of the gene COI. However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches (ECOPRIMERS and DEGEPRIME) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein-coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon-based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today.

bioinformatics↗