Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples

New applications of DNA and RNA sequencing are expanding the field of biodiversity discovery and ecological monitoring, yet questions remain regarding precision and efficiency. Due to primer bias, the ability of metabarcoding to accurately depict biomass of different taxa from bulk communities remains unclear, while PCR‐free whole mitochondrial genome (mitogenome) sequencing may provide a more reliable alternative. Here, we used a set of documented mock communities comprising 13 species of freshwater macroinvertebrates of estimated individual biomass, to compare the detection efficiency of COI metabarcoding (three different amplicons) and shotgun mitogenome sequencing. Additionally, we used individual COI barcoding and de novo mitochondrial genome sequencing, to provide reference sequences for OTU assignment and metagenome mapping (mitogenome skimming), respectively. We found that, even though both methods occasionally failed to recover very low abundance species, metabarcoding was less consistent, by failing to recover some species with higher abundances, probably due to primer bias. Shotgun sequencing results provided highly significant correlations between read number and biomass in all but one species. Conversely, the read–biomass relationships obtained from metabarcoding varied across amplicons. Specifically, we found significant relationships for eight of 13 (amplicons B1FR‐450 bp, FF130R‐130 bp) or four of 13 (amplicon FFFR, 658 bp) species. Combining the results of all three COI amplicons (multiamplicon approach) improved the read–biomass correlations for some of the species. Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding. However, for large‐scale ecological studies, metabarcoding currently remains the most commonly used approach for diversity assessment.     

Toward accurate species‐level metabarcoding of arthropod communities from the tropical forest canopy

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Sorting specimen‐rich invertebrate samples with cost‐effective NGS barcodes: Validating a reverse workflow for specimen processing

Biologists frequently sort specimen‐rich samples to species. This process is daunting when based on morphology, and disadvantageous if performed using molecular methods that destroy vouchers (e.g., metabarcoding). An alternative is barcoding every specimen in a bulk sample and then presorting the specimens using DNA barcodes, thus mitigating downstream morphological work on presorted units. Such a “reverse workflow” is too expensive using Sanger sequencing, but we here demonstrate that is feasible with an next‐generation sequencing (NGS) barcoding pipeline that allows for cost‐effective high‐throughput generation of short specimen‐specific barcodes (313 bp of COI; laboratory cost <$0.50 per specimen) through next‐generation sequencing of tagged amplicons. We applied our approach to a large sample of tropical ants, obtaining barcodes for 3,290 of 4,032 specimens (82%). NGS barcodes and their corresponding specimens were then sorted into molecular operational taxonomic units (mOTUs) based on objective clustering and Automated Barcode Gap Discovery (ABGD). High diversity of 88–90 mOTUs (4% clustering) was found and morphologically validated based on preserved vouchers. The mOTUs were overwhelmingly in agreement with morphospecies (match ratio 0.95 at 4% clustering). Because of lack of coverage in existing barcode databases, only 18 could be accurately identified to named species, but our study yielded new barcodes for 48 species, including 28 that are potentially new to science. With its low cost and technical simplicity, the NGS barcoding pipeline can be implemented by a large range of laboratories. It accelerates invertebrate species discovery, facilitates downstream taxonomic work, helps with building comprehensive barcode databases and yields precise abundance information.     

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

DNA metabarcoding can contribute to improving cost‐effectiveness and accuracy of biological assessments of aquatic ecosystems, but significant optimization and standardization efforts are still required to mainstream its application into biomonitoring programmes. In assessments based on freshwater macroinvertebrates, a key challenge is that DNA is often extracted from cleaned, sorted and homogenized bulk samples, which is time‐consuming and may be incompatible with sample preservation requirements of regulatory agencies. Here, we optimize and evaluate metabarcoding procedures based on DNA recovered from 96% ethanol used to preserve field samples and thus including potential PCR inhibitors and nontarget organisms. We sampled macroinvertebrates at five sites and subsampled the preservative ethanol at 1 to 14 days thereafter. DNA was extracted using column‐based enzymatic (TISSUE) or mechanic (SOIL) protocols, or with a new magnetic‐based enzymatic protocol (BEAD), and a 313‐bp COI fragment was amplified. Metabarcoding detected at least 200 macroinvertebrate taxa, including most taxa detected through morphology and for which there was a reference barcode. Better results were obtained with BEAD than SOIL or TISSUE, and with subsamples taken 7–14 than 1–7 days after sampling, in terms of DNA concentration and integrity, taxa diversity and matching between metabarcoding and morphology. Most variation in community composition was explained by differences among sites, with small but significant contributions of subsampling day and extraction method, and negligible contributions of extraction and PCR replication. Our methods enhance reliability of preservative ethanol as a potential source of DNA for macroinvertebrate metabarcoding, with a strong potential application in freshwater biomonitoring.     

DNA metabarcoding quantifies the relative biomass of arthropod taxa in songbird diets: Validation with camera‐recorded diets

Ecological research is often hampered by the inability to quantify animal diets. Diet composition can be tracked through DNA metabarcoding of fecal samples, but whether (complex) diets can be quantitatively determined with metabarcoding is still debated and needs validation using free‐living animals. This study validates that DNA metabarcoding of feces can retrieve actual ingested taxa, and most importantly, that read numbers retrieved from sequencing can also be used to quantify the relative biomass of dietary taxa. Validation was done with the hole‐nesting insectivorous Pied Flycatcher whose diet was quantified using camera footage. Size‐adjusted counts of food items delivered to nestlings were used as a proxy for provided biomass of prey orders and families, and subsequently, nestling feces were assessed through DNA metabarcoding. To explore potential effects of digestion, gizzard and lower intestine samples of freshly collected birds were subjected to DNA metabarcoding. For metabarcoding with Cytochrome Oxidase subunit I (COI), we modified published invertebrate COI primers LCO1490 and HCO1777, which reduced host reads to 0.03%, and amplified Arachnida DNA without significant changing the recovery of other arthropod taxa. DNA metabarcoding retrieved all commonly camera‐recorded taxa. Overall, and in each replicate year (N = 3), the relative scaled biomass of prey taxa and COI read numbers correlated at R = .85 (95CI:0.68–0.94) at order level and at R = .75 (CI:0.67–0.82) at family level. Similarity in arthropod community composition between gizzard and intestines suggested limited digestive bias. This DNA metabarcoding validation demonstrates that quantitative analyses of arthropod diet is possible. We discuss the ecological applications for insectivorous birds.     

Towards routine DNA metabarcoding of macroinvertebrates using bulk samples for freshwater bioassessment: Effects of debris and storage conditions on the recovery of target taxa

1. Macroinvertebrates are commonly sampled for bioassessment of freshwater ecosystems. However, current bioassessment protocols involve laborious sorting of the animals from the debris (sample matrix) and morphological identification, where species level identifications are often difficult. DNA metabarcoding has the potential to improve bioassessment by reducing the time taken to process samples and improve the accuracy and speed of macroinvertebrate species identification.
2. In this study, we evaluated DNA metabarcoding of macroinvertebrate samples, which include macroinvertebrates and the debris collected in the sample nets, to test if bulk, unsorted samples can be used to assess macroinvertebrate diversity. First, we tested if the sample matrix prevented the detection of six target macroinvertebrate taxa when DNA metabarcoding. Second, we tested if sample storage influenced the detection of the same six target macroinvertebrates. We also explored different levels of replication at the sample, sub-sample, and polymerase chain reaction levels and compared the overall macroinvertebrate families detected using DNA metabarcoding to those identified morphologically.
3. We found that the presence of the sample matrix did not interfere with or inhibit the detection of the six target macroinvertebrate taxa. Furthermore, we found that the various sample storage methods did not affect target macroinvertebrate detection. The reliability of detection of the target macroinvertebrates improved as hierarchical levels of replication were combined. We found strong overlap between the detection of overall macroinvertebrate family diversity when comparing DNA metabarcoding to morphological identification.
4. Extracting DNA from the bulk macroinvertebrate samples that included the sample matrix and using this for DNA metabarcoding could improve bioassessment by removing the need for laborious sorting of samples. Furthermore, DNA metabarcoding detection of the six target taxa was not dependent on sample storage of up to 1 year in 95% ethanol, at room temperature or after heating. DNA metabarcoding had the advantage of identifying macroinvertebrate species, but good DNA barcode libraries are needed for widespread species identifications. Further investigation should focus on including multiple samples with different macroinvertebrate composition and densities to refine and standardise bulk sample processing protocols, and on building comprehensive DNA barcode libraries for aquatic macroinvertebrates.

     

Genetic monitoring of open ocean biodiversity: An evaluation of DNA metabarcoding for processing continuous plankton recorder samples

DNA metabarcoding is an efficient method for measuring biodiversity, but the process of initiating long‐term DNA‐based monitoring programmes, or integrating with conventional programs, is only starting. In marine ecosystems, plankton surveys using the continuous plankton recorder (CPR) have characterized biodiversity along transects covering millions of kilometres with time‐series spanning decades. We investigated the potential for use of metabarcoding in CPR surveys. Samples (n = 53) were collected in two Southern Ocean transects and metazoans identified using standard microscopic methods and by high‐throughput sequencing of a cytochrome c oxidase subunit I marker. DNA increased the number of metazoan species identified and provided high‐resolution taxonomy of groups problematic in conventional surveys (e.g., larval echinoderms and hydrozoans). Metabarcoding also generally produced more detections than microscopy, but this sensitivity may make cross‐contamination during sampling a problem. In some samples, the prevalence of DNA from large plankton such as krill masked the presence of smaller species. We investigated adding a fixed amount of exogenous DNA to samples as an internal control to allow determination of relative plankton biomass. Overall, the metabarcoding data represent a substantial shift in perspective, making direct integration into current long‐term time‐series challenging. We discuss a number of hurdles that exist for progressing DNA metabarcoding from the current snapshot studies to the requirements of a long‐term monitoring programme. Given the power and continually increasing efficiency of metabarcoding, it is almost certain this approach will play an important role in future plankton monitoring.     

Coalescing molecular evolution and DNA barcoding

The DNA barcoding concept (Woese et al. 1990 ; Hebert et al. 2003 ) has considerably boosted taxonomy research by facilitating the identification of specimens and discovery of new species. Used alone or in combination with DNA metabarcoding on environmental samples (Taberlet et al. 2012 ), the approach is becoming a standard for basic and applied research in ecology, evolution and conservation across taxa, communities and ecosystems (Scheffers et al. 2012 ; Kress et al. 2015 ). However, DNA barcoding suffers from several shortcomings that still remain overlooked, especially when it comes to species delineation (Collins & Cruickshank 2012 ). In this issue of Molecular Ecology, Barley & Thomson ( 2016 ) demonstrate that the choice of models of sequence evolution has substantial impacts on inferred genetic distances, with a propensity of the widely used Kimura 2‐parameter model to lead to underestimated species richness. While DNA barcoding has been and will continue to be a powerful tool for specimen identification and preliminary taxonomic sorting, this work calls for a systematic assessment of substitution models fit on barcoding data used for species delineation and reopens the debate on the limitation of this approach.     

Metabarcoding a diverse arthropod mock community

Although DNA metabarcoding is an attractive approach for monitoring biodiversity, it is often difficult to detect all the species present in a bulk sample. In particular, sequence recovery for a given species depends on its biomass and mitome copy number as well as the primer set employed for PCR. To examine these variables, we constructed a mock community of terrestrial arthropods comprised of 374 species. We used this community to examine how species recovery was impacted when amplicon pools were constructed in four ways. The first two protocols involved the construction of bulk DNA extracts from different body segments (Bulk Abdomen, Bulk Leg). The other protocols involved the production of DNA extracts from single legs which were then merged prior to PCR (Composite Leg) or PCR‐amplified separately (Single Leg) and then pooled. The amplicons generated by these four treatments were then sequenced on three platforms (Illumina MiSeq, Ion Torrent PGM and Ion Torrent S5). The choice of sequencing platform did not substantially influence species recovery, although the Miseq delivered the highest sequence quality. As expected, species recovery was most efficient from the Single Leg treatment because amplicon abundance varied little among taxa. Among the three treatments where PCR occurred after pooling, the Bulk Abdomen treatment produced a more uniform read abundance than the Bulk Leg or Composite Leg treatment. Primer choice also influenced species recovery and evenness. Our results reveal how variation in protocols can have substantial impacts on perceived diversity unless sequencing coverage is sufficient to reach an asymptote.     

Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

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Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias

Studies of insect assemblages are suited to the simultaneous DNA‐based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR‐amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR‐amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR‐amplified the blend using five primer sets, targeting either COI or 16S, with high‐throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers.     

Next‐generation monitoring of aquatic biodiversity using environmental DNA metabarcoding

Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present in the environment. In this study, we tested whether an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90–0.99) vs. 0.58 (CI = 0.50–0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA‐based approach has the potential to become the next‐generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.     

DNA metabarcoding reveals that 200‐μm‐size‐fractionated filtering is unable to discriminate between planktonic microbial and large eukaryotes

Microeukaryotic plankton (0.2–200 μm) are critical components of aquatic ecosystems and key players in global ecological processes. High‐throughput sequencing is currently revolutionizing their study on an unprecedented scale. However, it is currently unclear whether we can accurately, effectively and quantitatively depict the microeukaryotic plankton communities using traditional size‐fractionated filtering combined with molecular methods. To address this, we analysed the eukaryotic plankton communities both with, and without, prefiltering with a 200 μm pore‐size sieve –by using SSU rDNA‐based high‐throughput sequencing on 16 samples with three replicates in each sample from two subtropical reservoirs sampled from January to October in 2013. We found that ~25% reads were classified as metazoan in both size groups. The species richness, alpha and beta diversity of plankton community and relative abundance of reads in 99.2% eukaryotic OTUs showed no significant changes after prefiltering with a 200 μm pore‐size sieve. We further found that both >0.2 μm and 0.2–200 μm eukaryotic plankton communities, especially the abundant plankton subcommunities, exhibited very similar, and synchronous, spatiotemporal patterns and processes associated with almost identical environmental drivers. The lack of an effect on community structure from prefiltering suggests that environmental DNA from larger metazoa is introduced into the smaller size class. Therefore, size‐fractionated filtering with 200 μm is insufficient to discriminate between the eukaryotic plankton size groups in metabarcoding approaches. Our results also highlight the importance of sequencing depth, and strict quality filtering of reads, when designing studies to characterize microeukaryotic plankton communities.     

Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material

DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high‐throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co‐occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field‐collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population‐level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives.     

Estimating belowground plant abundance with DNA metabarcoding

Most work on plant community ecology has been performed above ground, neglecting the processes that occur in the soil. DNA metabarcoding, in which multiple species are computationally identified in bulk samples, can help to overcome the logistical limitations involved in sampling plant communities belowground. However, a major limitation of this methodology is the quantification of species’ abundances based on the percentage of sequences assigned to each taxon. Using root tissues of five dominant species in a semi‐arid Mediterranean shrubland (Bupleurum fruticescens, Helianthemum cinereum, Linum suffruticosum, Stipa pennata and Thymus vulgaris), we built pairwise mixtures of relative abundance (20%, 50% and 80% biomass), and implemented two methods (linear model fits and correction indices) to improve estimates of root biomass. We validated both methods with multispecies mixtures that simulate field‐collected samples. For all species, we found a positive and highly significant relationship between the percentage of sequences and biomass in the mixtures (R² = .44–.66), but the equations for each species (slope and intercept) differed among them, and two species were consistently over‐ and under‐estimated. The correction indices greatly improved the estimates of biomass percentage for all five species in the multispecies mixtures, and reduced the overall error from 17% to 6%. Our results show that, through the use of post‐sequencing quantification methods on mock communities, DNA metabarcoding can be effectively used to determine not only species’ presence but also their relative abundance in field samples of root mixtures. Importantly, knowledge of these aspects will allow us to study key, yet poorly understood, belowground processes.     

Increasing ecological inference from high throughput sequencing of fungi in the environment through a tagging approach

High throughput sequencing methods are widely used in analyses of microbial diversity, but are generally applied to small numbers of samples, which precludes characterization of patterns of microbial diversity across space and time. We have designed a primer-tagging approach that allows pooling and subsequent sorting of numerous samples, which is directed to amplification of a region spanning the nuclear ribosomal internal transcribed spacers and partial large subunit from fungi in environmental samples. To test the method for phylogenetic biases, we constructed a controlled mixture of four taxa representing the Chytridiomycota, Zygomycota, Ascomycota and Basidiomycota. Following cloning and colony restriction fragment length polymorphism analysis, we found no significant difference in representation in 19 of the 23 tested primers. We also generated a clone library from two soil DNA extracts using two primers for each extract and compared 456 clone sequences. Community diversity statistics and contingency table tests applied to counts of operational taxonomic units revealed that the two DNA extracts differed significantly, while the pairs of tagged primers from each extract were indistinguishable. Similar results were obtained using UniFrac phylogenetic comparisons. Together, these results suggest that the pig-tagged primers can be used to increase ecological inference in high throughput sequencing projects on fungi.     

DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match

DNA metabarcoding enables efficient characterization of species composition in environmental DNA or bulk biodiversity samples, and this approach is making significant and unique contributions in the field of ecology. In metabarcoding of animals, the cytochrome c oxidase subunit I (COI) gene is frequently used as the marker of choice because no other genetic region can be found in taxonomically verified databases with sequences covering so many taxa. However, the accuracy of metabarcoding datasets is dependent on recovery of the targeted taxa using conserved amplification primers. We argue that COI does not contain suitably conserved regions for most amplicon-based metabarcoding applications. Marker selection deserves increased scrutiny and available marker choices should be broadened in order to maximize potential in this exciting field of research.     

DNA条形码参考数据集构建和序列分析相关的新兴技术

近年来DNA条形码技术迅速发展, 产生的条形码的数量及其应用范围都呈指数性增长, 现已广泛用于物种鉴定、食性分析、生物多样性评估等方面。本文重点总结并讨论了构建条形码参考数据库和序列聚类相关的信息分析的技术和方法, 包括: 基于高通量测序(high throughput sequencing, HTS)平台以高效并较低的成本获取条形码序列的方法; 同时还介绍了从原始测序序列到分类操作单元(operational taxonomic units, OTUs)过程中的一些计算逻辑以及被广泛采用的软件和技术。这是一个较新并快速发展的领域, 我们希望本文能为读者提供一个梗概, 了解DNA条形码技术在生物多样性研究应用中的方法和手段。     

Environmental DNA metabarcoding primers for freshwater fish detection and quantification: In silico and in tanks

Environmental DNA (eDNA) techniques refer to utilizing the organisms’ DNA extracted from environment samples to genetically identify target species without capturing actual organisms. eDNA metabarcoding via high‐throughput sequencing can simultaneously detect multiple fish species from a single water sample, which is a powerful tool for the qualitative detection and quantitative estimates of multiple fish species. However, sequence counts obtained from eDNA metabarcoding may be influenced by many factors, of which primer bias is one of the foremost causes of methodological error. The performance of 18 primer pairs for COI, cytb, 12S rRNA, and 16S rRNA mitochondrial genes, which are all frequently used in fish eDNA metabarcoding, were evaluated in the current study. The ribosomal gene markers performed better than the protein‐coding gene markers during in silico screening, resulting in higher taxonomic coverage and appropriate barcode lengths. Four primer pairs—AcMDB07, MiFish‐U, Ve16S1, and Ve16S3—designed for various regions of the 12S and 16S rRNA genes were screened for tank metabarcoding in a case study targeting six freshwater fish species. The four primer pairs were able to accurately detect all six species in different tanks, while only MiFish‐U, Ve16S1, and Ve16S3 revealed a significant positive relationship between species biomass and read count for the pooled tank data. The positive relationship could not be found in all species within the tanks. Additionally, primer efficiency differed depending on the species while primer preferential species varied in different fish assemblages. This case study supports the potential for eDNA metabarcoding to assess species diversity in natural ecosystems and provides an alternative strategy to evaluate the performance of candidate primers before application of eDNA metabarcoding in natural ecosystems.     

Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).