Open Access
Research Article
Volume 29, 2022
Article Number 30
Number of page(s) 7
Published online 31 May 2022

© M. Šloufová et al., published by EDP Sciences, 2022

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Blastocystis sp. is a unicellular eukaryote colonizing the gastrointestinal tract of humans and various other species. Although discovered more than a century ago, its role in human health and disease has not been fully understood. Knowledge gaps remain in its epidemiology and interaction with the host, as well as factors affecting host colonization [3, 9, 26]. Blastocystis may be the most common intestinal human protist in the world, colonizing more than 1 billion people [1]. In some cohorts, the prevalence of Blastocystis sp. may reach 100% [5]. Based on small ribosomal subunit (SSU rRNA) gene analysis, at least 22 subtypes (ST) exist across mammalian and avian hosts [23]. Among these subtypes, ST1–ST9 and ST12 have been found in humans, with ST1–ST4 being commonly detected [26].

Despite the numerous surveys on Blastocystis sp., no consensus has been reached on the choice of method(s) for detection and differentiation of the protist (reviewed in Skotarczak [22]). Moreover, despite the development of molecular approaches, traditional microscopic examination of ova and parasites (O&P) and xenic culturing is still commonly used in laboratories to detect Blastocystis [12]. However, these methods require specialized technicians [12], are less sensitive, and do not provide subtype information [8, 24, 28]. Nevertheless, accurate detection and distinction of Blastocystis subtypes is essential to understand the transmission and the role of this protist in human health. Due to their high sensitivity and specificity, molecular methods such as conventional PCR (cPCR) or real-time PCR (qPCR) are often used [14, 22, 25]. In addition, next-generation sequencing (NGS) is gaining prominence in detection of Blastocystis and its subtypes [4, 17, 27].

The aim of this study was to compare (i) the sensitivity of cPCR and qPCR on a set of DNA samples obtained from stool samples of individuals with no gastrointestinal symptoms, and (ii) subtype diversity detected by cPCR and Sanger sequencing versus NGS.

Material and methods

Ethics statement

The studies involving human participants were reviewed and approved by Ethics Committee of the Biology Center of the Czech Academy of Sciences (reference number: 1/2017). Written informed consent to participate in this study was provided by the participants or their legal guardian/next of kin. All data were anonymized and processed according to valid laws of the Czech Republic (e.g., Act no. 101/2000 Coll and subsequent regulations). In case of the rat tissue used for testing of internal inhibition, we used samples from the experiment approved by the Committee on the Ethics of Animal Experiments of the Biology Centre of the Czech Academy of Sciences (České Budějovice, permit no. 33/2018) and by the Resort Committee of the Czech Academy of Sciences (Prague, Czech Republic) in strict accordance with Czech legislation (Act No. 166/1999 Coll. on veterinary care and on changes of some related laws, and Act No. 246/1992 Coll. on the protection of animals against cruelty), as well as the legislation of the European Union.


In this study, we used 288 DNA samples obtained from fresh stool samples from a cohort created during a previous survey on the prevalence and diversity of Blastocystis in a gut-healthy human population in the Czech Republic (for more details on the collection and DNA extraction see Lhotská et al. [8]). We also used data on the positivity rate of Blastocystis sp. resulting from cPCR [8] for comparison with qPCR results obtained in the present study. Here, we applied the diagnostic qPCR protocol published in the study by Stensvold et al. [25]. The primers target the SSU rDNA fragment of 118 bp, which is detected by a Taqman probe. Samples were processed using a LightCycler LC 480 I (Roche, Basel, Switzerland) with a 96-well block. The cycling conditions consisted of primary denaturation (95 °C/10 min) and 37 × (95 °C/15 s, 60 °C/30 s, 72 °C/30 s). The results of qPCR on Blastocystis were then compared with the results of conventional PCR (from Lhotská et al. [8]) using McNemar’s test with Yates’s correction (0.5). Statistical analysis was performed using the software SciStatCalc 2013 (

Positive samples from qPCR were subjected to amplicon NGS to determine Blastocystis subtypes: an informative fragment of SSU rDNA (~450 bp) was amplified, indexed and sequenced on a MiSeq instrument with the Reagent Kit v2, 2 × 250 bp (Illumina, San Diego, CA, USA); this was performed according to the method by Maloney et al. (2019) [11] with minor modifications in Cinek et al. [4] (for more detail see Supplementary data 1). These results were compared with the results on subtype diversity described in Lhotská et al. [8] based on Sanger sequencing. Fecal protist load was estimated based on a quantification curve generated from a dilution series of cultured Blastocystis ST3, which was set in the range of 100 to 105 cells per one qPCR reaction: 100–101 – mild fecal protist load; 102–103 – moderate fecal protist load; 104–105 – high fecal protist load (Supplementary data 2). Blastocystis cell counts from culture were calculated using a Bürker’s chamber and then serially diluted to obtain aliquots containing 100, 101, 102, 103, 104, and 105 cells, which were subsequently subjected to DNA extraction according to Lhotská et al. [8]. All negative samples were checked for PCR inhibition using addition of foreign DNA (obtained from tissue of experimental rats) and a specific qPCR protocol (commercial primers and Taqman probe for detection of the rat gene for beta-2 microglobulin; ThermoFisher Scientific, Waltham, MA, USA).


In this study, the prevalence of Blastocystis was determined by qPCR and subsequently compared with the results from cPCR obtained in our previous study Lhotská et al. [8]. In the set of 288 stool samples from the gut-healthy volunteers, the qPCR revealed a prevalence of 29% (83/288; Table 1) compared to cPCR with the prevalence 24% (71/288). Real-time PCR revealed 12 more positive samples (Table 1), our results indicate that qPCR is a more sensitive method for detecting Blastocystis in stool samples than cPCR (p < 0.05; χ2 = 8.26; Table 2). There was a discrepancy between these methods for two samples that qPCR evaluated as negative and cPCR as positive (Table 1). No internal inhibition was detected in any of the samples.

Table 1

Comparison of the sensitivity of conventional PCR (cPCR) and qPCR from the entire dataset of human samples (n = 288). Evaluation of the success of Blastocystis detection by next-generation sequencing (NGS) only in a set of qPCR-positive samples (n = 83).

Table 2

Comparison of results of qPCR (Stensvold et al., 2012) and conevntional PCR [cPCR] (Sciclune et al., 2006) in detection of Blastocystis sp. using McNemar test (p < 0.004; χ2 = 8.265).

We established a quantification curve (100–105 of cells/1 qPCR reaction) to evaluate the Blastocystis fecal load in positive samples and to extrapolate different colonization intensities from ct values (ct values are displayed for each sample in Table 1). In more than half of the samples positive in qPCR (52/83), colonization intensities reached 105 or more, with the range of ct values ranging from 15 to 20 (Table 3). Fecal protist load 103–104 (range of ct values between 21 and 27) was found in 13 samples, and 101–102 (range of ct values between 28 and 32) in 18 samples (Table 3). In the samples positive only in qPCR (n = 12), a very low fecal protist load was found, i.e., 101–102 (Table 3).

Table 3

Evaluation of fecal load of Blastocystis in human samples based on the established quantification curve (set in the range of 100 to 105 cells per 1 qPCR reaction).

Subtype diversity for all 83 qPCR-positive samples was evaluated by NGS, which detected subtypes in 69 samples (69/83; Tables 1 and 4). In case of the presence of one subtype in a sample, the NGS results were consistent with our previous results based on Sanger sequencing [8]. In fact, the major benefit of NGS appears to be in its ability to detect mixed colonizations of different subtypes in one sample. Mixed colonizations were found in five more cases compared to Sanger sequencing, specifically the subtype colonization mix: ST1 + ST7, ST1 + ST3, ST2 + ST3 (2×), ST3 + ST7 (Table 4). In the case of 12 samples positive only in qPCR with low fecal protist load, NGS detected subtypes in only five samples, namely ST2, ST5, ST3 (2×) and ST4 (Table 4).

Table 4

Comparison of Blastocystis subtype data in a set of 83 qPCR-positive samples obtained by Sanger sequencing (results obtained in previous study Lhotská et al., 2020) and next-generation sequencing (NGS).


To compare the sensitivity between the two PCR-based approaches for detection of Blastocystis, we used a dataset of 288 human stool samples obtained in the study by Lhotská et al. [8]. Revealing 12 more positive samples, qPCR was the most sensitive method for detection of Blastocystis. The overall prevalence of Blastocystis by qPCR and cPCR was 29% and 24% (Lhotská et al. [8]), respectively. Surprisingly, it appears that this is the very first study comparing the sensitivity between the commonly used cPCR protocol [20] and qPCR [25] for the detection of Blastocystis sp. Previously, some studies showed higher sensitivity of qPCR in comparison with classical methods such as direct-light microscopy or xenic in vitro culture [14, 15, 25]. The study by Nourrisson et al. [14] compared four qPCR protocols for detection of Blastocystis sp. and found that they differed in specificity and sensitivity. Furthermore, the authors recommend the qPCR protocol Stensvold et al. [25] for diagnostic purposes and to add another method for subtype identification.

Despite higher sensitivity, qPCR scored two samples as negative, while conventional PCR scored them positive; these two samples were positive for ST3 and ST8. The two false-negative results by qPCR might be due to the degradation of DNA in the samples due to long-term storage and repeated freeze-thawing cycles of their aliquots. These DNA samples were tested again by cPCR, one sample appears to be negative and one (ST8) showed much less intensive amplicon in the electrophoresis. Alternatively, the qPCR protocol might have limited sensitivity for example for ST8, which was not used in the validation panel by Stensvold et al. [25], who developed the method. However, the applicability of the primers and probe was validated in silico using the alignment in the article’s Figure 1 [25] with a 100% match to ST8, which means that, at least in theory, the assay should be able to pick up this subtype. In addition, no inhibition was revealed in any sample during inhibition control using the foreign DNA.

The advantage of qPCR-based diagnostic approach is the ability to estimate the fecal load of Blastocystis in colonized humans based on an established quantification curve. Our results in individuals with healthy intestines (i.e., without inflammatory diseases) showed a high fecal Blastocystis load in more than half of the samples. This fecal load ranged in values of order from 105 to 106 cells per one qPCR reaction. In the 12 samples scored as positive only by qPCR, low fecal protist load was detected (101–102 cells per sample). A very recent study by Cinek et al. [4] quantified Blastocystis in feces of asymptomatic children and adolescents. However, more studies on both healthy humans and patients with inflammatory of functional bowel diseases are warranted [13]. A comparison of fecal Blastocystis loads between healthy and sick individuals could fundamentally contribute to understanding the role of Blastocystis sp. in the human gut ecosystem and could be important for experimental studies testing the effect of Blastocystis sp. on gut inflammation [2]. It is important to note that the quantification curve for assessing fecal Blastocystis load might be biased by different copy number of the SSU rRNA gene in individual subtypes and life stages of Blastocystis. This could slightly reduce the accuracy of quantification data. However, such data for Blastocystis and its subtypes are not yet available. Nevertheless, an approximate determination of Blastocystis fecal load can reveal trends between different human cohorts.

In epidemiological studies on Blastocystis sp. in humans, the identification of its subtypes plays an important role [6, 8, 16, 21]. Because different Blastocystis subtypes colonize different hosts and apparently differ in geographical distribution, surveys aimed at subtype determination might help reveal transmission pathways and potential sources of specific subtypes in a particular area. To date, most studies used Sanger sequencing for subtype identification [7, 8, 18], which may have limitations in detecting mixed subtype colonizations. Here, we subjected all 83 qPCR-positive samples to NGS analysis to determine subtypes. We found that subtype diversity was largely consistent with the results of Sanger sequencing by Lhotská et al. [8], in which Sanger sequencing was used. In 12 samples identified as positive only by qPCR, the NGS revealed subtypes only in five samples which was probably caused by low fecal load of Blastocystis. The remaining seven samples were confirmed by Sanger sequencing from qPCR amplicons (118 bp), however, without information about subtypes.

Although epidemiological studies usually describe colonization of an individual with only one subtype of Blastocystis sp. [8, 19, 21], mixed subtype colonization appears to be more common [17, 22, 29]. This situation is in part caused by limitations of some of the current molecular tools, which preferentially amplify the predominant subtypes present in a sample [11]. Here, the NGS-based approach showed higher sensitivity in determining mixed subtype colonization than a combination of methods, such as conventional PCR and Sanger sequencing (for more details see Lhotská et al. [8]). While Lhotská et al. [8] revealed a single case of mixed infection, NGS detected five more cases of mixed colonisation.

From a diagnostic point-of-view, our results support the fact that qPCR is the most suitable method for detecting the presence of Blastocystis. NGS alone cannot achieve qPCR sensitivity, mainly due to the known signal crosstalk between individual samples in a sequencing run (e.g., [10]). Although this issue can be alleviated by using unique dual indexing, it cannot be eliminated. Therefore, very low read counts do not necessarily indicate presence of the organism. Thus, the role of NGS in Blastocystis diagnostics is primarily in the determination of its subtypes and disentangling mixed colonizations. Of the 83 total qPCR-positive samples, the NGS revealed subtypes in 69 samples.


To understand the epidemiology of Blastocystis sp., it is necessary to establish a gold standard method for detection and subtype differentiation. A review of the Blastocystis literature so far suggests that detection and differentiation has not yet been harmonized [22]. The findings of the present study showed that qPCR is a suitable tool for the highly sensitive detection of Blastocystis sp., and the NGS approach enables accurate assessment of subtype diversity, in particular, mixed subtype colonization. We believe that the combination of these two approaches will be beneficial for future epidemiological surveys and surveillance studies on Blastocystis.

Conflict of interest

The authors declare that they have no conflict of interest.


We thank Oldřiška Kadlecová, Andrea Kašparová, Kristýna Brožová, and Kateřina Poláčková for laboratory assistance. This work was supported financially by grants from the Human Frontiers Science Programme (RGY0078/2015) and from the Czech Science Foundation (22-04837S) to K.J. Pomajbíková, by a grant from the Student Grant Agency (SGA) at the Faculty of Science of the University of South Bohemia to M. Šloufová (in 2021), and by the Ministry of Health of the Czech Republic, a project for the conceptual development of research organization, University Hospital Motol, Prague (00064203) to OC.


  1. Andersen LOB, Stensvold CR. 2016. Blastocystis in health and disease: are we moving from a clinical to a public health perspective? Journal of Clinical Microbiology, 54, 524–528. [CrossRef] [PubMed] [Google Scholar]
  2. Billy V, Lhotská Z, Jirků M, Kadlecová O, Frgelevocá L, Wegener Parfrey L, Jirků-Pomajbíková K. 2021. Blastocystis colonization alters the gut microbiome and in some cases, promotes faster recovery from induced colitis. Frontiers in Microbiology, 12, 641483. [CrossRef] [PubMed] [Google Scholar]
  3. Chabé M, Lokmer A, Ségurel L. 2017. Gut protozoa: friends or foes of the human gut microbiota? Trends in Parasitology, 33, 925–934. [Google Scholar]
  4. Cinek O, Polačková K, Odeh R, Alassaf A, Kramná L, Ibekwe MAU, Majaliwa ES, Ahmadov G, Elmahi BME, Mekki H, Oikarinen S, Lebl J, Abdullah MA. 2021. Blastocystis in the faeces of children from six distant countries: prevalence, quantity, subtypes and the relation to the gut bacteriome. Parasites & Vectors, 14, 399. [CrossRef] [PubMed] [Google Scholar]
  5. El Safadi D, Gaayeb L, Meloni D, Cian A, Poirier P, Wawrzyniak I, Delbac F, Dabboussi F, Delhaes L, Seck M, Hamze M, Riveau G, Viscogliosi E. 2014. Children of senegal river basin show the highest prevalence of Blastocystis sp. ever observed worldwide. BMC Infection Diseseas, 14, 399. [CrossRef] [Google Scholar]
  6. El Safadi D, Cian A, Nourrisson C, Pereira B, Morelle C, Bastien P, Bellanger AP, Botterel F, Candolfi E, Desoubeaux G, Lachaud L, Morio F, Pomares C, Rabodonirina M, Wawrzyniak I, Delbac F, Gantois N, Certad G, Delhaes L, Poirier P, Viscogliosi E. 2016. Prevalence, risk factors for infection and subtype distribution of the intestinal parasite Blastocystis sp. from a large-scale multi-center study in France. BMC Infection Diseases, 16, 451. [CrossRef] [Google Scholar]
  7. Haghighi L, Talebnia SE, Mikaeili F, Asgari Q, Gholizadeh F, Zomorodian K. 2020. Prevalence and subtype identification of Blastocystis isolated from human in Shiraz city, southern Iran. Clinical Epidemiology and Global Health, 8, 840–844. [CrossRef] [Google Scholar]
  8. Lhotská Z, Jirků M, Hložková O, Brožová K, Jirsová D, Stensvold CR, Kolísko M, Jirků-Pomajbíková K. 2020. A study on the prevalence and subtype diversity of the intestinal protist Blastocystis sp. in a gut-healthy human population in the Czech republic. Frontiers in Cellular and Infectious Microbiology, 10, 544335. [CrossRef] [Google Scholar]
  9. Lukeš J, Stensvold CR, Jirků-Pomajbíková K, Wegener Parfrey L. 2015. Are human intestinal eukaryotes beneficial or commensals? PLoS Pathogens, 11, e1005039. [CrossRef] [PubMed] [Google Scholar]
  10. MacConaill LE, Burns RT, Nag A, Coleman HA, Slevin MK, Giorda K, Light M, Lai K, Jarosz M, McNeil MS, Ducar MD, Meyerson M, Thorner AR. 2018. Unique, dual-indexed sequencing adapters with UMIs effectively eliminate index cross-talk and significantly improve sensitivity of massively parallel sequencing. BMC Genomics, 19, 30. [CrossRef] [PubMed] [Google Scholar]
  11. Maloney JG, Molokin A, Santin M. 2019. Next generation amplicon sequencing improves detection of Blastocystis mixed subtype infections. Infection, Genetics and Evolution, 73, 119–125. [CrossRef] [PubMed] [Google Scholar]
  12. McHardy IH, Wu M, Shimizu-Cohen R, Roger Couturier M, Humphries RM (2014) Detection of intestinal protozoa in the clinical laboratory. Journal of Clinical Microbiology, 52, 712–720. [CrossRef] [PubMed] [Google Scholar]
  13. Nourrisson C, Scanzi J, Pereira B, NkoudMongo C, Wawrzyniak I, Cian A, Viscogliosi E, Livrelli V, Delbac F, Dapoigny M, Poirier P. 2014. Blastocystis is associated with decrease of fecal microbiotaprotective bacteria: comparative analysis between patients with irritable bowel syndrome and control subjects. PLoS One, 9, e111868. [CrossRef] [PubMed] [Google Scholar]
  14. Nourrisson C, Brunet J, Flori P, Moniot M, Bonnin V, Delbac F, Poirier P. 2020. Comparison of DNA extraction methods and real-time PCR assays for the detection of Blastocystis sp. in stool specimens. Microorganisms, 8, 1768. [CrossRef] [Google Scholar]
  15. Poirier P, Wawrzyniak I, Albert A, El Alaoui H, Delbac F, Livrelli V. 2011. Development and evaluation of a real-time PCR assay for detection and quantification of Blastocystis parasites in human stool samples: prospective study of patients with hematological malignancies. Journal of Clinical Microbiology, 49, 975–983. [CrossRef] [PubMed] [Google Scholar]
  16. Popruk S, Adao DEV, Rivera WL. 2021. Epidemiology and subtype distribution of Blastocystis in humans: a review. Infection, Genetics and Evolution, 95, 105085. [CrossRef] [PubMed] [Google Scholar]
  17. Rojas-Velázquez L, Maloney JG, Molokin A, Morán P, Serrano-Vázquez A, González E, Pérez-Juárez H, Ximénez C, Santin M. 2019. Use of next-generation amplicon sequencing to study Blastocystis genetic diversity in a rural human population from Mexico. Parasites & Vectors, 12, 566. [CrossRef] [PubMed] [Google Scholar]
  18. Scanlan PD, Stensvold CR, Cotter PD. 2015. Development and application of a Blastocystis subtype-specific PCR assay reveals that mixed-subtype infections are common in a healthy human population. Applied and Environmental Microbiology, 81, 4071–4076. [CrossRef] [PubMed] [Google Scholar]
  19. Scanlan PD, Knight R, Song SJ, Ackermann G, Cotter PD. 2016. Prevalence and genetic diversity of Blastocystis in family units living in the United States. Infection, Genetics and Evolution, 45, 95–97. [CrossRef] [PubMed] [Google Scholar]
  20. Scicluna SM, Tawari B, Clark CG. 2006. DNA barcoding of Blastocystis. Protist, 157, 77–85. [Google Scholar]
  21. Seyer A, Karasartova D, Ruh E, Güreser AS, Turgal E, Imir T, Taylan-Ozkan A. 2017. Epidemiology and prevalence of Blastocystis spp. in North Cyprus. American Journal of Tropical Medicine and Hygiene, 96, 1164–1170. [Google Scholar]
  22. Skotarczak B. 2018. Genetic diversity and pathogenicity of Blastocystis. Annals of Agricultural and Environmental Medicine, 25, 411–416. [CrossRef] [PubMed] [Google Scholar]
  23. Stensvold CR, Clark CG. 2020. Pre-empting pandora’s box: Blastocystis subtypes revisited. Trends in Parasitology, 36, 229–232. [CrossRef] [PubMed] [Google Scholar]
  24. Stensvold CR, Arendrup MC, Jespersgaard C, Mølbak K, Nielsen HV. 2007. Detecting Blastocystis using parasitologic and DNA-based methods: a comparative study. Diagnotic Microbiology and Infectious Disease, 59, 303–307. [CrossRef] [Google Scholar]
  25. Stensvold CR, Ahmed UN, Andersen LOB, Nielsen HV. 2012. Development and evaluation of a genus-specific, probe-based, internal-process-controlled real-time PCR assay for sensitive and specific detection of Blastocystis spp. Journal of Clinical Microbiology, 50, 1847–1851. [CrossRef] [PubMed] [Google Scholar]
  26. Stensvold CR, Tan KSW, Clark CG. 2020. Blastocystis. Trends in Parasitology, 36, 315–316. [CrossRef] [PubMed] [Google Scholar]
  27. Stensvold CR, Jirků Pomajbíková K, Wegener Tams K, Jokelainen P, Berg RPKD, Marving E, Petersen RF, Andersen LOB, Angen O, Nielsen HV. 2021. Parasitic intestinal protists of zoonotic relevance detected in pigs by metabarcoding and real-time PCR. Microorganisms, 9, 1189. [CrossRef] [PubMed] [Google Scholar]
  28. Tan KSW. 2008. New insights on classification, identification, and clinical relevance of Blastocystis spp. Clinical Microbiology Reviews, 21, 639–665. [CrossRef] [PubMed] [Google Scholar]
  29. Vega L, Herrera G, Munoz M, Patarroyo MA, Maloney JG, Santin M, Ramírez JD. 2021. Gut microbiota profiles in diarrheic patients with co-occurrence of Clostridioides difficile and Blastocystis. PLoS One, 16, e0248185. [CrossRef] [PubMed] [Google Scholar]

Cite this article as: Šloufová M, Lhotská Z, Jirků M, Petrželková KJ, Stensvold CR, Cinek O & Pomajbíková KJ. 2022. Comparison of molecular diagnostic approaches for the detection and differentiation of the intestinal protist Blastocystis sp. in humans. Parasite 29, 30.

Supplementary materials

Supplementary data 1: Detailed description of the next-generation sequencing protocol for Blastocystis. (Access here)

Supplementary data 2: Quantification curve used in qPCR diagnostic protocol for evaluation of the fecal Blastocystis load in human DNA samples (in LightCycler LC 480 I; Roche, Basel, Switzerland). The curve was set in the range of 100 to 105 cells per 1 qPCR reaction based on the Blastocystis ST3 culture. (Access here)

All Tables

Table 1

Comparison of the sensitivity of conventional PCR (cPCR) and qPCR from the entire dataset of human samples (n = 288). Evaluation of the success of Blastocystis detection by next-generation sequencing (NGS) only in a set of qPCR-positive samples (n = 83).

Table 2

Comparison of results of qPCR (Stensvold et al., 2012) and conevntional PCR [cPCR] (Sciclune et al., 2006) in detection of Blastocystis sp. using McNemar test (p < 0.004; χ2 = 8.265).

Table 3

Evaluation of fecal load of Blastocystis in human samples based on the established quantification curve (set in the range of 100 to 105 cells per 1 qPCR reaction).

Table 4

Comparison of Blastocystis subtype data in a set of 83 qPCR-positive samples obtained by Sanger sequencing (results obtained in previous study Lhotská et al., 2020) and next-generation sequencing (NGS).

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