Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Detection of lymphoproliferative disease virus in Iowa Wild Turkeys (Meleagris gallopavo): Comparison of two sections of the proviral genome

  • Kelsey C. Smith ,

    Contributed equally to this work with: Kelsey C. Smith, Julie A. Blanchong

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft

    smith2kc@gmail.com

    Affiliation Department of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, United States of Ameria

  • Julie A. Blanchong

    Contributed equally to this work with: Kelsey C. Smith, Julie A. Blanchong

    Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – original draft

    Affiliation Department of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, United States of Ameria

Abstract

An accurate diagnostic test is an essential aspect of successfully monitoring and managing wildlife diseases. Lymphoproliferative Disease Virus (LPDV) is an avian retrovirus that was first identified in domestic turkeys in Europe and was first reported in a Wild Turkey (Meleagris gallopavo) in the United States in 2009. It has since been found to be widely distributed throughout North America. The majority of studies have utilized bone marrow and PCR primers targeting a 413-nucleotide sequence of the gag gene of the provirus to detect infection. While prior studies have evaluated the viability of other tissues for LPDV detection (whole blood, spleen, liver, cloacal swabs) none to date have studied differences in detection rates when utilizing different genomic regions of the provirus. This study examined the effectiveness of another section of the provirus, a 335-nucleotide sequence starting in the U3 region of the LTR (Long Terminal Repeat) and extending into the Matrix of the gag region (henceforth LTR), for detecting LPDV. Bone marrow samples from hunter-harvested Wild Turkeys (n = 925) were tested for LPDV with the gag gene and a subset (n = 417) including both those testing positive and those where LPDV was not detected was re-tested with LTR. The positive percent agreement (PPA) was 97.1% (68 of 70 gag positive samples tested positive with LTR) while the negative percent agreement (NPA) was only 68.0% (236 of 347 gag negative samples tested negative with LTR). Cohen’s Kappa (κ = 0.402, Z = 10.26, p<0.0001) and the McNemar test (OR = 55.5, p<0.0001) indicated weak agreement between the two gene regions. We found that in Iowa Wild Turkeys use of the LTR region identified LPDV in many samples in which we failed to detect LPDV using the gag region and that LTR may be more appropriate for LPDV surveillance and monitoring. However, neither region of the provirus resulted in perfect detection and additional work is necessary to determine if LTR is more reliable in other geographic regions where LPDV occurs.

Introduction

Wildlife disease surveillance is important for multiple reasons: disease can negatively impact biodiversity, human health, domestic animal and livestock health, and economic stability [1]. Surveillance can aid not only with mitigation, but also with preventing the spread of disease to new areas. To successfully monitor and manage wildlife diseases, it is essential to have an accurate method of detection, otherwise there is a risk of inaccurately estimating factors such as prevalence, virulence, and transmission [2]. Imperfect diagnostic tests can also hinder our ability to predict spread [2] and result in the allocation of resources to inefficient management plans [3].

Lymphoproliferative disease virus (LPDV) is an avian retrovirus first identified during the 1970’s in Europe and Israel, and again in North America in 2009 [4]. While its entire geographic distribution has yet to be determined, to date it has been identified in Wild Turkeys (Meleagris gallopavo) along the East coast [57], as far West as Colorado [4, 8], as far south as Texas [9] and in several Canadian provinces: Manitoba, Ontario, and Quebec [10, 11]. Although previous outbreaks in Europe and Israel were in domestic turkeys, in the United States, natural infection has only been identified in Wild Turkeys [4]. Compared to their domestic counterparts, that experienced heightened levels of internal lesions and mortality [12], prior North American studies utilizing hunter-harvested turkeys have indicated that infection in wild birds is typically asymptomatic [4, 8, 10, 11, 13], although mortalities have been observed [4]. Clinical symptoms, when present, are typically non-specific, such as lethargy or anorexia [12]. To date, little is known of the transmission mechanism [4], population-level effects, and impacts on poults (chicks) [11].

Retroviruses function by integrating their RNA genome into host DNA, so as DNA replicates, the virus does as well [14, 15]. Viral RNA is transcribed into DNA via reverse transcriptase and is then integrated into the host’s genome. Organization of the LPDV provirus is as follows: 5’-LTR-gag-pro-pol-env-LTR-3’ [4, 16]. The complete proviral genome of the first LPDV case in North America (12/AR/2009) was 7,432 nucleotides long including LTRs [4]. Virus expression and replication first occur in bone marrow, then distribute to other lymphoid tissues [8, 16]. In a prior study by Thomas et al. [8] it was found that bone marrow was the most efficient tissue for diagnosing LPDV in turkeys obtained from hunter-harvest, compared to spleen and liver.

Diagnosis of LPDV is typically through polymerase chain reaction (PCR) utilizing DNA obtained from bone marrow, although whole blood and cloacal swabs have also been found to be a suitable alternative in live birds [13, 17]. When testing for LPDV, the partial p31/ partial capsid region of the gag gene is widely used among researchers [4, 8, 10, 11, 13]. However, this region may not consistently detect infection due to variability among viral strains across the distribution of turkeys (Renshaw R., Cornell University, personal communication). An exploratory examination of LPDV detection in samples collected from turkeys in both the eastern and western distribution of their range suggested that a different section of the LPDV provirus beginning in the U3 region of the Long Terminal Repeat and extending into the gag Matrix (henceforth referred to as LTR) may be more accurate at detecting infected birds (Renshaw R., Cornell University, personal communication). Long terminal repeats are an essential element of retroviruses, containing components essential for integration and transcription of the provirus [18], gene expression, and insertional mutagenesis [19]. Studies of other retroviruses have also found that PCR primers targeting different regions of the proviral genome had varying detection rates [20, 21].

With Wild Turkey populations suspected to be declining (as indicated by observation of declines in spring harvest numbers) across the United States due to unknown causes [22], some natural resource managers are interested in expanding our understanding of LPDV and its potential role in declines. To do so, it is important to use the best available diagnostic test. The goal of this study was to determine if there are differences in LPDV detection rates when testing the same set of samples with the gag and LTR sections of the provirus and whether using LTR leads to the detection of more LPDV positive Wild Turkeys in Iowa than are detected using gag.

Methods

Sample collection

Hunter-harvested Wild Turkey tarsi were collected between 2019 and 2021 (n = 1022) in cooperation with the Iowa Department of Natural Resources (IADNR). The county and location of harvest was provided for each bird. Samples were also provided by the IADNR State Wildlife Veterinarian (submitted for necropsy) and from road-killed turkeys. Upon receipt, tarsi were stored in a -20°C or -80°C freezer until processing. Because samples were collected from hunter-harvested or road-killed animals the Iowa State University Intuitional Animal Care and Use Committee (IACUC) did not require an IACUC protocol for this study.

Bone marrow and DNA extraction

A 10% bleach solution followed by water and ethanol was used to clean and flame sterilize equipment prior to each use to prevent cross-contamination when removing bone marrow from tarsi. Legs were cleaved, then forceps and probes used to extract bone marrow. Approximately 25mg was aliquoted into a 1.5mL microcentrifuge tube for DNA extraction; samples were refrigerated until extraction. Remaining tissue was stored in a separate tube and frozen at -20°C or -80°C.

The DNeasy Blood & Tissue Kit (Qiagen) was used to extract DNA from bone marrow using the manufacturer’s protocol, with the following modification: elution of DNA was performed with 100μL of AE buffer instead of 200μL to increase final DNA concentration. If a small quantity of bone marrow was extracted (i.e., approximately half the amount of bone marrow typically used or less), samples were instead eluted with 50μL. A Denovix DS-11 spectrophotometer (NanoDrop Technologies) was used to quantify the amount of DNA extracted. A working sample for PCR was then created by diluting samples with sterile water to a standard concentration of 50ng/μL to ensure consistency across samples. Some samples (approximately 40%) had too small an amount of bone marrow to create the standard concentration working sample and were left undiluted (concentration of undiluted samples ranged from 8.01 ng/μL to 49.85ng/μL).

PCR

PCR using primers developed by Allison et al. [4] amplifying the p31 and a part of the capsid domains within the virus’ gag gene was conducted to test samples for LPDV. PCR was conducted following the protocol described in Alger et al. [13] with slight modifications to the PCR mix and reaction conditions, as follows. Products were amplified with a Mastercycler EP Gradient (Eppendorf) in a 20μL reaction consisting of 10μL HotStarTaq Plus Master Mix (Qiagen), 1μL of each 10μM primer (forward: 5’-ATGAGGACTTGTTAGATTGGTTAC-3’, reverse: 5’-TGATGGCGTCAGGGCTATTTG-3’ [4]), 6μL water, and 2μL DNA (concentration ranging from 8.01–50.0ng/μL following standardization). Reaction conditions included a denaturation step at 95°C for 5 min, followed by denaturation at 95°C for 30 sec, annealing at 54°C for 30 sec, and extension at 72°C for 1 min for 34 cycles, ending with extension at 72°C for 10 min.

A negative and positive control was included in each PCR reaction, where the negative control contained water rather than DNA template. Positive controls were spleen/liver tissues from New York turkeys that were confirmed LPDV positive through DNA sequencing. Initial positive controls were of limited quantity, so a subset of samples that tested positive were purified with the QIAquick PCR Purification Kit (Qiagen) to isolate DNA for use as additional positive controls; of these, four were sequenced for confirmation of LPDV infection. Agarose gel electrophoresis was used to visualize PCR products, where the presence of a 413 bp band matching that of the positive control was used to determine if a sample was positive for LPDV infection (Gel 1 in S1 File). Infection was confirmed through sequencing using the forward primer for a subset (50%) of positive samples.

To compare the detection rates between the two sections of the provirus (gag and LTR), 45% of samples that tested gag positive and 45% of samples that tested gag negative were randomly selected and tested with LTR. The amplification protocol for testing with LTR was similar to that of the gag gene but the annealing temperature was increased to 56°C to reduce non-specific binding. Primers designed to amplify a large portion of the 5’ LTR (starting in the U3 region) and extending into the Matrix domain of the gag gene were used (forward: 5’-GGGCACGGGATTGGCTT-3’; reverse:– 5’-AAACGCTCAATACACGACACAAC-3’, Renshaw R., Cornell University, personal communication). Results were visualized through agarose gel electrophoresis following the same protocol as with the gag gene (Gel 2 in S1 File). A subset of samples that tested positive with LTR (some of which were gag positive and some of which were gag negative) were sequenced with the forward LTR primer for confirmation of LPDV infection (6%).

Sensitivity and specificity analysis

The total number of samples that tested gag+/LTR+, gag+/LTR-, gag-/LTR-, and gag-/LTR+ was determined to compare the detection rate of LPDV with the LTR segment of the provirus against that of the gag gene (reference test). In order to examine where results from the gag and LTR regions were in agreement (i.e., a sample is diagnosed as positive by both methods or negative by both methods), the Positive Percent Agreement (PPA) and Negative Percent Agreement (NPA) were calculated. Although the standard among researchers, results from this study (as described below) indicated that detection of LPDV with the gag gene was imperfect. The use of imperfect reference tests during the calculation of sensitivity and specificity introduces bias and may result in the underestimation of true values [23]. In cases such as this, an alternative is to calculate the PPA and NPA [24, 25]. Rather than indicating how often a novel test (LTR in this study) is correct or incorrect, PPA and NPA describe how often the novel test is in agreement or disagreement with the reference test. Calculations are performed in the same manner as sensitivity and specificity, where PPA is the portion of gag positive samples that also tested positive with LTR out of the total number of gag positives and NPA is the portion of gag negative samples that also tested negative with LTR out of the total number of gag negatives.

Statistical analysis

While useful in determining where results from gag and LTR were in agreement, PPA and NPA are not statistical assessments. To statistically compare results from gag and LTR, Cohen’s kappa and the McNemar test were used. Cohen’s kappa was used to statistically examine how often the results were in agreement (i.e., samples tested positive with both gag and LTR or negative with both gag and LTR). Cohen’s kappa is a statistical test measuring the agreement between two different raters or tests that describes the overall agreement between the two tests while accounting for agreement due to chance [26]. Cohen’s kappa tests the null hypothesis that any agreement is due to chance (κ = 0) against the alternative hypothesis that agreement is not a result of chance (κ ≠ 0) [27]. The ‘Kappa’ function from the R package ‘vcd’ was used for computations [28, 29] and was run as unweighted because there were two nominal variables. Cohen’s kappa value was interpreted according to the scale suggested by McHugh: 0–0.20, none; 0.21–0.39, minimal; 0.40–0.59, weak; 0.60–0.79, moderate; 0.80–0.90, strong; above 0.90, almost perfect agreement [26].

Another method of comparing results from gag and LTR is with the McNemar test, which tests agreement between proportions of the discordant cells in a contingency table [30]. This test looks at where diagnostic tests disagree rather than overall agreement using the null hypothesis that both types of disagreement are equally likely against the alternative that they are not equally likely. The McNemar test was used to examine how often diagnosis with LTR differed from gag and if those differences were proportional (i.e., whether there were equal or unequal numbers of gag+/LTR- and gag-/LTR+). Of the four versions of the McNemar test (classical, continuity corrected, exact, and mid-P), evidence suggests that mid-P provides the best combination of the higher power seen in classical tests and the reduced type I error rate seen in corrected tests [30, 31]. The function ‘exact2x2’ from the R package ‘exact2x2’ was used to perform the McNemar test [29, 32, 33]. Data were treated as paired and the mid-p value was used. The McNemar odds ratio (OR) obtained from analysis is calculated by dividing the number of gag-/LTR+ by the number of gag+/LTR- and represents how much more likely a result of gag-/LTR+ is than gag+/LTR- [34]. The OR may be interpreted according to the following: < 1, less likely; = 1, equally likely; > 1, more likely. Significance levels for both Cohen’s Kappa and the McNemar test were set at α ≤ 0.05. All analyses were performed in R (version 4.1.1).

Results

Extracted DNA ranged in concentration from 8.01ng/μL to 1275.26ng/μL prior to standardization. A total of 925 samples were of sufficient quality for testing and had unambiguous results with the gag gene. Of these, LPDV was undetected in 772 samples and 153 tested positive using the gag gene (S1 Data). Infection status appeared to be unrelated to DNA concentration, with samples of both low and high DNA concentrations testing LPDV positive using both gag and LTR. A subset (n = 417)– 45% of gag positive and 45% of gag negative samples–was randomly selected for paired testing with LTR (Table 1). The subset of samples that tested positive with LTR that were sequenced with LTR primers all most closely matched LPDV sequences in the National Center for Biotechnology Information (NCBI) BLAST database (pairwise identity and percent identical ranged from 93.4% to 99.0%), confirming detection of LPDV with LTR. Gag and LTR sequences were deposited in GenBank under the accession numbers OR026188- OR026260 and OR026261-OR026271, respectively.

thumbnail
Table 1. Pairwise comparison of LPDV detected (+) and undetected (-) samples using the gag and LTR sections of the provirus.

https://doi.org/10.1371/journal.pone.0296856.t001

The positive percent agreement (PPA) was 97.1% (68/70) and the negative percent agreement (NPA) was 68.0% (236/347), indicating greater disagreement with LTR for samples testing gag negative than samples testing gag positive (Table 2). Cohen’s kappa (κ = 0.402) was significant (Z = 10.26, p < 0.0001), falling between the categories of minimal and weak agreement between the results from gag and LTR (Table 2). The McNemar mid-p test was also significant (OR = 55.5, p < 0.0001), indicating the number of gag positive/LTR negative and gag negative/LTR positive samples was disproportionate, and that there were significantly more samples that tested positive with LTR and negative with gag. (Table 2).

thumbnail
Table 2. Evaluation of LTR as a diagnostic test for LPDV infection against the standard (gag) using positive percent agreement (PPA), negative percent agreement (NPA), Cohen’s kappa, and McNemar’s odds ratio (OR).

https://doi.org/10.1371/journal.pone.0296856.t002

Discussion

This study was performed to examine differences in detection rates when testing Iowa Wild Turkeys for LPDV with the gag and LTR sections of the provirus, therefore assessing the utility of LTR for detection of LPDV. The data demonstrated that there was high agreement in results between gag and LTR in samples that were gag positive, with both testing positive in 97.1% of gag positive samples. However, there was a high level of disagreement for samples that were gag negative, with both testing negative in only 68.0% of gag negative samples. LTR resulted in the identification of an additional 111 samples as LPDV positive. Sequencing confirmed that LTR was detecting the presence of LPDV in turkeys. These results show that, at least in Wild Turkeys in Iowa, the LTR section of the LPDV provirus is able to detect infected individuals including those testing negative with the gag gene, and that testing with the gag gene results in false negatives. Although LTR did detect more positive animals than gag in this study, it did not detect all cases. One of the two gag positive but LTR undetected cases was sequenced with gag primers to confirm LPDV infection and that the disagreement was not due to lab error.

The high mutation rate in viruses can lead to large amounts of genetic variation [35, 36], which is exhibited in LPDV by the many different strains identified across studies based on the gag gene [4, 8, 10, 11, 3739]. PCR is used to detect LPDV infections by using primers that bind to a specific region of the provirus that has been inserted into the turkey genome, but may fail to detect the virus even when it is present when there are high levels of variation that lead to mismatches between primers and the binding region of the sample [35]. Because of this, diagnostic methods that are successful in one geographic region may be less successful in another geographic region. As a virus spreads among individuals, mutations will occur, creating increasing amounts of diversity between nucleotide sequences as the infection spreads. The results of this study suggest that the LTR section may be a more conservative region of the LPDV provirus and thus less likely to contain genetic variation that would negatively affect primer binding success in comparison to the gag gene (Renshaw R., Cornell University, personal communication).

This study included only samples from Iowa Wild Turkeys, which represents a small part of the Wild Turkey range and the distribution of LPDV that has been documented to date [411]. Because of the geographic limitation of this study, it is not yet clear if LTR performs similarly well at detecting LPDV in Wild Turkeys in other geographic regions. Another limitation is that a relatively small number of gag positive samples were tested with LTR. A larger sample size might provide a more accurate estimate of LTR’s false negative rate. Further, while sequenced samples consistently matched LPDV sequences in the NCBI BLAST database and re-testing samples reinforced confidence in positive results, not all gag or LTR tested samples were sequenced, thus there is the possibility of false positives.

Future research could include testing for LPDV with LTR in additional regions covering the rest of the Wild Turkey’s range to determine if LTR performs similarly in other geographic regions, or if its ability to detect additional positive turkeys is restricted to the Midwest. Testing could also be conducted in subspecies other than Eastern Wild Turkeys. Other sections of the LPDV provirus or whole genome sequencing could also be considered for viability as a diagnostic test, as could other types of PCR depending on sample type (e.g., real-time, reverse-transcriptase). While nucleotide conservation was previously found to be similar across the four viral genes of LPDV (gag, pro, pol, env), pol was found to have the highest level of conservation (90.1%), compared to gag (88.3%), pro (88.3%), and env (86.6%) [4]. This might suggest pol as another viable option for testing. Further, a recent study of LPDV in Wild Turkeys in Texas employed quantitative PCR (qPCR) and the env gene for surveillance [9]. Universal primers have been developed for other viruses and could provide another possible option for future research [35].

Successfully monitoring and managing LPDV in Wild Turkey populations requires an accurate method of detection [2, 3]. Detection methods with a high rate of false negatives might result in an underestimation of prevalence and incorrectly identifying risk factors or areas of concern [2]. If LTR performs similarly in other geographic regions, it would suggest that LPDV prevalence might be higher than has previously been reported. By correctly identifying positive cases, additional risk factors may come to light, or previously identified variables may prove to be less significant than initially believed, allowing for better predictions. Identifying risk factors can help identify areas potentially at risk and identifying areas with high numbers of cases might suggest areas to target for future studies on LPDV. This in turn can lead to more efficient management and a better allocation of resources [3].

Supporting information

S1 Data. CSV file containing the Wild Turkey LPDV infection status dataset.

https://doi.org/10.1371/journal.pone.0296856.s001

(CSV)

Acknowledgments

We would like to thank Randall Renshaw from Cornell University who shared his hypothesis about differences in LPDV detectability using gag vs LTR that led us to conduct this study and for providing samples for use as positive controls. We thank the Iowa Department of Natural Resources staff and hunters for their assistance in obtaining samples from harvested Wild Turkeys.

References

  1. 1. Belant JL, Deese AR. Importance of wildlife disease surveillance. Hum Wildl Interact. 2010;4(2):165–9.
  2. 2. Lachish S, Gopalaswamy AM, Knowles SCL, Sheldon BC. Site-occupancy modelling as a novel framework for assessing test sensitivity and estimating wildlife disease prevalence from imperfect diagnostic tests: Occupancy models for disease prevalence estimates. Methods Ecol Evol. 2012 Apr;3(2):339–48.
  3. 3. Paterson JT, Butler C, Garrott R, Proffitt K. How sure are you? A web-based application to confront imperfect detection of respiratory pathogens in bighorn sheep. PLoS One. 2020 Sep 8;15(9):e0237309. pmid:32898140
  4. 4. Allison AB, Kevin Keel M, Philips JE, Cartoceti AN, Munk BA, Nemeth NM, et al. Avian oncogenesis induced by lymphoproliferative disease virus: A neglected or emerging retroviral pathogen? Virology. 2014 Feb;450–451:2–12. pmid:24503062
  5. 5. Alger K, Bunting E, Schuler K, Whipps CM. Risk factors for and spatial distribution of lymphoproliferative disease virus (LPDV) in wild turkeys (Meleagris gallopavo) in New York state, USA. J Wildl Dis. 2017 Jul;53(3):499–508. pmid:28328350
  6. 6. Shea SA, Gonnerman M, Blomberg E, Sullivan K, Milligan P, Kamath PL. Pathogen survey and predictors of lymphoproliferative disease virus infection in wild turkeys (Meleagris gallopavo). J Wildl Dis. 2022 Jul 25;58(3). pmid:35704504
  7. 7. Kreh CD, Palamar MB. Prevalence of lymphoproliferative disease virus in wild turkeys (Melagris gallopavo) in North Carolina. Wildl Soc Bull. 2022 May;46(2).
  8. 8. Thomas JM, Allison AB, Holmes EC, Phillips JE, Bunting EM, Yabsley MJ, et al. Molecular surveillance for lymphoproliferative disease virus in wild turkeys (Meleagris gallopavo) from the Eastern United States. Waldenström J, editor. PLoS One. 2015 Apr 21;10(4):e0122644. pmid:25897755
  9. 9. Cox F, Hardin J, Dittmar R, Edwards D. Molecular surveillance for lymphoproliferative disease virus and reticuloendotheliosis virus in Rio Grande Wild Turkeys (Meleagris gallopavo intermedia) in Texas, USA. J Wildl Dis. 2022 Nov;58(4):909–913. pmid:36305745
  10. 10. MacDonald AM, Jardine CM, Bowman J, Susta L, Nemeth NM. Detection of lymphoproliferative disease virus in Canada in a survey for viruses in Ontario wild turkeys (Meleagris gallopavo). J Wildl Dis. 2019 Jan 1;55(1):113–122. pmid:30124393
  11. 11. MacDonald AM, Barta JR, McKay M, Lair S, Le Net R, Baldwin F, et al. Lymphoproliferative disease virus in wild turkeys (Meleagris gallopavo) from Manitoba and Quebec, Canada. Avian Dis. 2019 Jun 11;63(3):506. pmid:31967435
  12. 12. Biggs PM, McDougall JS, Frazier JA, Milne BS. Lymphoproliferative disease of turkeys I. clinical aspects. Avian Pathol. 1978 Jan;7(1):131–9. pmid:18770365
  13. 13. Alger K, Bunting E, Schuler K, Jagne J, Whipps CM. Diagnosing lymphoproliferative disease virus in live wild turkeys (Meleagris gallopavo) using whole blood. J Zoo Wildl Med. 2015 Dec;46(4):806–14. pmid:26667537
  14. 14. Cloyd MW. Human Retroviruses. In: Baron S, editor. Medical Microbiology [Internet]. 4th ed. Galveston, TX: University of Texas Medical Branch at Galveston; 1996 [cited 2020 Jan 9]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK7934/
  15. 15. Weiss RA. Retrovirus classification and cell interactions. J Antimicrob Chemother. 1996 May 1;37(suppl B):1–11. pmid:8818825
  16. 16. Gazit A, Yaniv A. Lymphoproliferative disease virus of turkeys (Retroviridae). In: Granoff A, Webster RG, editors. Encyclopedia of Virology [Internet]. 2nd ed. Elsevier; 1999 [cited 2020 Jan 6]. p. 911–5. Available from: https://linkinghub.elsevier.com/retrieve/pii/B0122270304001746
  17. 17. Shea SA, Gonnerman MB, Blomberg EJ, Sullivan KM, Kamath PL. Detecting lymphoproliferative disease virus in wild turkeys using cloacal swabs. Wildl Soc Bull. 2022;46(2):e1280.
  18. 18. Benachenhou F, Sperber GO, Bongcam-Rudloff E, Andersson G, Boeke JD, Blomberg J. Conserved structure and inferred evolutionary history of long terminal repeats (LTRs). Mob DNA. 2013 Dec;4(1):5. pmid:23369192
  19. 19. Gak E, Yaniv A, Sherman L, Ianconescu M, Tronick SR, Gazit A. Lymphoproliferative disease virus of turkeys: sequence analysis and transcriptional activity of the long terminal repeat. Gene. 1991 Mar;99(2):157–62. pmid:2022329
  20. 20. Marinho RC, Martins GR, Souza KCD, Júnior RQB, Teixeira MFDS. Detection of maedi-visna virus from sheep bronchoalveolar lavage by nested PCR evaluation of different primers pairs. Acta Sci Vet. 2016 Jan 16;44(1):6.
  21. 21. Marinho RC, Martins GR, Souza KCD, Sousa ALM, Silva STC, Nobre JA, et al. Duplex nested-PCR for detection of small ruminant lentiviruses. Braz J Microbiol. 2018 Nov;49:83–92. pmid:30249525
  22. 22. Eriksen RE, Brown TA, Scott KB, Hughes TW, Akridge MD, Penner CS. Status and distribution of wild turkeys in the United States: 2014 status. In: Miller DA, editor. Proceedings of the Eleventh National Wild Turkey Symposium. Tuscon, Arizona: The National Wild Turkey Federation; 2016. p. 7–18.
  23. 23. Valenstein PN. Evaluating Diagnostic Tests with Imperfect Standards. Am J Clin Pathol. 1990 Feb 1;93(2):252–8. pmid:2405632
  24. 24. McAdam AJ. Sensitivity and Specificity or Positive and Negative Percent Agreement? A Micro-Comic Strip. Burnham CAD, editor. J Clin Microbiol. 2017 Nov;55(11):3153–4. pmid:29066563
  25. 25. McHugh LC, Snyder K, Yager TD. The effect of uncertainty in patient classification on diagnostic performance estimations. PLoS One. 2019 May 22;14(5):e0217146. pmid:31116772
  26. 26. McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012 Oct 15;22(3):276–82. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900052/ pmid:23092060
  27. 27. Hallgren KA. Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial. Tutor Quant Methods Psychol. 2012;8(1):23–34. pmid:22833776
  28. 28. Meyer D, Zeileiz A, Hornik K. vcd: Visualizing Categorical Data. Version 1.4.9 [software]. 2021. Available from: https://cran.r-project.org/web/packages/vcd/index.html
  29. 29. R Core Team. R: A Language and Environment for Statistical Computing. Version 4.1.1 [software]. Vienna, Austria: R Foundation for Statistical Computing; 2021. Available from: https://www.R-project.org/
  30. 30. Pembury Smith MQR, Ruxton GD. Effective use of the McNemar test. Behav Ecol Sociobiol. 2020 Nov;74(11):133.
  31. 31. Fagerland MW, Lydersen S, Laake P. The McNemar test for binary matched-pairs data: mid-p and asymptotic are better than exact conditional. BMC Med Res Methodol. 2013 Dec;13(1):91. pmid:23848987
  32. 32. Fay M. Two-sided Exact Tests and Matching Confidence Intervals for Discrete Data. R J. 2010;2(1):53–8.
  33. 33. Fay MP, Hunsberger SA, Nason M, Gabriel E, Lumbard K. Exact2x2: Exact Tests and Confidence Intervals for 2x2 Tables. Version 1.6.6 [software]. 2021. Available from: https://cran.r-project.org/web/packages/exact2x2/index.html
  34. 34. Cleophas TJ, Zwinderman AH. McNemar’s Odds Ratios. In: Clinical Data Analysis on a Pocket Calculator: Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing [Internet]. Cham: Springer International Publishing; 2016. p. 275–8. Available from: https://doi.org/10.1007/978-3-319-27104-0_49
  35. 35. Rubio L, Galipienso L, Ferriol I. Detection of Plant Viruses and Disease Management: Relevance of Genetic Diversity and Evolution. Front Plant Sci. 2020;11. pmid:32765569
  36. 36. Xu S, Stapley J, Gablenz S, Boyer J, Appenroth KJ, Sree KS, et al. Low genetic variation is associated with low mutation rate in the giant duckweed. Nat Commun. 2019 Mar 18;10(1):1243. pmid:30886148
  37. 37. Shea SA. Retroviral Infection Dynamics in Maine’s Wild Turkeys. Ph.D Dissertation, University of Maine. 2021. Available from: https://digitalcommons.library.umaine.edu/cgi/viewcontent.cgi?article=4568&context=etd
  38. 38. Alger K. Lymphoproliferative disease virus (LPDV) in wild turkeys (Meleagris gallopavo) in New York State: Diagnostic methods, prevalence, and spatial distribution of a newly discovered pathogen. M.Sc. Thesis, State University of New York. 2015.
  39. 39. Smith KC. Lymphoproliferative disease virus (LPDV) in Iowa’s Wild Turkeys (Meleagris gallopavo).M.Sc. Thesis, Iowa State University. 2022. Available from: https://www.proquest.com/openview/b95c0d0e689d528c34c679578d3112c8/1