BACKGROUND: Infection with feline immunodeficiency virus (FIV) causes an immunosuppressive disease whose consequences are less severe if cats are co-infected with an attenuated FIV strain (PLV). We use virus diversity measurements, which reflect replication ability and the virus response to various conditions, to test whether diversity of virulent FIV in lymphoid tissues is altered in the presence of PLV. Our data consisted of the 3' half of the FIV genome from three tissues of animals infected with FIV alone, or with FIV and PLV, sequenced by 454 technology. RESULTS: Since rare variants dominate virus populations, we had to carefully distinguish sequence variation from errors due to experimental protocols and sequencing. We considered an exponential-normal convolution model used for background correction of microarray data, and modified it to formulate an error correction approach for minor allele frequencies derived from high-throughput sequencing. Similar to accounting for over-dispersion in counts, this accounts for error-inflated variability in frequencies - and quite effectively reproduces empirically observed distributions. After obtaining error-corrected minor allele frequencies, we applied ANalysis Of VAriance (ANOVA) based on a linear mixed model and found that conserved sites and transition frequencies in FIV genes differ among tissues of dual and single infected cats. Furthermore, analysis of minor allele frequencies at individual FIV genome sites revealed 242 sites significantly affected by infection status (dual vs. single) or infection status by tissue interaction. All together, our results demonstrated a decrease in FIV diversity in bone marrow in the presence of PLV. Importantly, these effects were weakened or undetectable when error correction was performed with other approaches (thresholding of minor allele frequencies; probabilistic clustering of reads). We also queried the data for cytidine deaminase activity on the viral genome, which causes an asymmetric increase in G to A substitutions, but found no evidence for this host defense strategy. CONCLUSIONS: Our error correction approach for minor allele frequencies (more sensitive and computationally efficient than other algorithms) and our statistical treatment of variation (ANOVA) were critical for effective use of high-throughput sequencing data in understanding viral diversity. We found that co-infection with PLV shifts FIV diversity from bone marrow to lymph node and spleen.

Bioinformatics Institute School of Biological Sciences University of Auckland Auckland 1142 New Zealand

Current address Institute of Molecular Genetics Academy of Sciences of the Czech Republic Videnska 1083 Prague 14000 Czech Republic

Department of Biology The Pennsylvania State University University Park PA 16802 USA

Department of Computer Science and Engineering The Pennsylvania State University University Park PA 16802 USA

Department of Statistics The Pennsylvania State University University Park PA 16802 USA

Department of Veterinary and Biomedical Sciences The Pennsylvania State University University Park PA 16802 USA

The Huck Institutes of the Life Sciences The Pennsylvania State University University Park PA 16802 USA

Zobrazit více v PubMed

Poss M, Rodrigo AG, Gosink JJ, Learn GH, de Vange PD, Martin HL, Jr, et al. Evolution of envelope sequences from the genital tract and peripheral blood of women infected with clade A human immunodeficiency virus type 1. J Virol. 1998;72:8240–51. PubMed PMC

Nickle DC, Jensen MA, Shriner D, Brodie SJ, Frenkel LM, Mittler JE, et al. Evolutionary indicators of human immunodeficiency virus type 1 reservoirs and compartments. J Virol. 2003;77:5540–6. doi: 10.1128/JVI.77.9.5540-5546.2003. PubMed DOI PMC

Salemi M, Burkhardt BR, Gray RR, Ghaffari G, Sleasman JW, Goodenow MM. Phylodynamics of HIV-1 in lymphoid and non-lymphoid tissues reveals a central role for the thymus in emergence of CXCR4-using quasispecies. PLoS One. 2007;2:e950. doi: 10.1371/journal.pone.0000950. PubMed DOI PMC

Blackard JT. HIV compartmentalization: a review on a clinically important phenomenon. Curr HIV Res. 2012;10:133–42. doi: 10.2174/157016212799937245. PubMed DOI

Burkhard MJ, Dean GA. Transmission and immunopathogenesis of FIV in cats as a model for HIV. Curr HIV Res. 2003;1:15–29. doi: 10.2174/1570162033352101. PubMed DOI

VandeWoude S, Apetrei C. Going wild: lessons from naturally occurring T-lymphotropic lentiviruses. Clin Microbiol Rev. 2006;19:728–62. doi: 10.1128/CMR.00009-06. PubMed DOI PMC

Elder JH, Lin YC, Fink E, Grant CK. Feline immunodeficiency virus (FIV) as a model for study of lentivirus infections: parallels with HIV. Curr HIV Res. 2010;8:73–80. doi: 10.2174/157016210790416389. PubMed DOI PMC

Bendinelli M, Pistello M, Lombardi S, Poli A, Garzelli C, Matteucci D, et al. Feline immunodeficiency virus: an interesting model for AIDS studies and an important cat pathogen. Clin Microbiol Rev. 1995;8:87–112. PubMed PMC

Terwee JA, Yactor JK, Sondgeroth KS, Vandewoude S. Puma lentivirus is controlled in domestic cats after mucosal exposure in the absence of conventional indicators of immunity. J Virol. 2005;79:2797–806. doi: 10.1128/JVI.79.5.2797-2806.2005. PubMed DOI PMC

VandeWoude S, Hageman CA, O’Brien SJ, Hoover EA. Nonpathogenic lion and puma lentiviruses impart resistance to superinfection by virulent feline immunodeficiency virus. J Acquir Immune Defic Syndr. 2002;29:1–10. doi: 10.1097/00042560-200201010-00001. PubMed DOI

Terwee JA, Carlson JK, Sprague WS, Sondgeroth KS, Shropshire SB, Troyer JL, et al. Prevention of immunodeficiency virus induced CD4+ T-cell depletion by prior infection with a non-pathogenic virus. Virology. 2008;377:63–70. doi: 10.1016/j.virol.2008.03.037. PubMed DOI PMC

Zheng X, Carver S, Troyer RM, Terwee JA, VandeWoude S. Prior virus exposure alters the long-term landscape of viral replication during feline lentiviral infection. Viruses. 2011;3:1891–908. doi: 10.3390/v3101891. PubMed DOI PMC

Padhi A, Ross H, Terwee J, Vandewoude S, Poss M. Profound differences in virus population genetics correspond to protection from CD4 decline resulting from feline lentivirus coinfection. Viruses. 2010;2:2663–80. doi: 10.3390/v2122663. PubMed DOI PMC

Hoffmann C, Minkah N, Leipzig J, Wang G, Arens MQ, Tebas P, et al. DNA bar coding and pyrosequencing to identify rare HIV drug resistance mutations. Nucleic Acids Res. 2007;35:e91. doi: 10.1093/nar/gkm435. PubMed DOI PMC

Barzon L, Lavezzo E, Militello V, Toppo S, Palu G. Applications of next-generation sequencing technologies to diagnostic virology. Int J Mol Sci. 2011;12:7861–84. doi: 10.3390/ijms12117861. PubMed DOI PMC

Radford AD, Chapman D, Dixon L, Chantrey J, Darby AC, Hall N. Application of next-generation sequencing technologies in virology. J Gen Virol. 2012;93:1853–68. doi: 10.1099/vir.0.043182-0. PubMed DOI PMC

Eriksson N, Pachter L, Mitsuya Y, Rhee SY, Wang C, Gharizadeh B, et al. Viral population estimation using pyrosequencing. PLoS Comput Biol. 2008;4:e1000074. doi: 10.1371/journal.pcbi.1000074. PubMed DOI PMC

Willerth SM, Pedro HA, Pachter L, Humeau LM, Arkin AP, Schaffer DV. Development of a low bias method for characterizing viral populations using next generation sequencing technology. PLoS One. 2010;5:e13564. doi: 10.1371/journal.pone.0013564. PubMed DOI PMC

Wright CF, Morelli MJ, Thebaud G, Knowles NJ, Herzyk P, Paton DJ, et al. Beyond the consensus: dissecting within-host viral population diversity of foot-and-mouth disease virus by using next-generation genome sequencing. J Virol. 2011;85:2266–75. doi: 10.1128/JVI.01396-10. PubMed DOI PMC

Henn MR, Boutwell CL, Charlebois P, Lennon NJ, Power KA, Macalalad AR, et al. Whole genome deep sequencing of HIV-1 reveals the impact of early minor variants upon immune recognition during acute infection. PLoS Pathog. 2012;8:e1002529. doi: 10.1371/journal.ppat.1002529. PubMed DOI PMC

Zagordi O, Bhattacharya A, Eriksson N, Beerenwinkel N. ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data. BMC bioinformatics. 2011;12:119. doi: 10.1186/1471-2105-12-119. PubMed DOI PMC

Prabhakara S, Malhotra R, Acharya R, Poss M. Mutant-Bin: Unsupervised Haplotype Estimation of Viral Population Diversity Without Reference Genome. J Comput Biol. 2013;20:453–63. doi: 10.1089/cmb.2012.0174. PubMed DOI

Shendure J, Ji H. Next-generation DNA sequencing. Nat Biotechnol. 2008;26:1135–45. doi: 10.1038/nbt1486. PubMed DOI

Romano CM, Lauck M, Salvador FS, Lima CR, Villas-Boas LS, Araujo ES, et al. Inter- and intra-host viral diversity in a large seasonal DENV2 outbreak. PLoS One. 2013;8:e70318. doi: 10.1371/journal.pone.0070318. PubMed DOI PMC

Wang C, Mitsuya Y, Gharizadeh B, Ronaghi M, Shafer RW. Characterization of mutation spectra with ultra-deep pyrosequencing: application to HIV-1 drug resistance. Genome Res. 2007;17:1195–201. doi: 10.1101/gr.6468307. PubMed DOI PMC

Morelli MJ, Wright CF, Knowles NJ, Juleff N, Paton DJ, King DP, et al. Evolution of foot-and-mouth disease virus intra-sample sequence diversity during serial transmission in bovine hosts. Vet Res. 2013;44:12. doi: 10.1186/1297-9716-44-12. PubMed DOI PMC

Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106. doi: 10.1186/gb-2010-11-10-r106. PubMed DOI PMC

Hashimoto TB, Edwards MD, Gifford DK. Universal count correction for high-throughput sequencing. PLoS Comput Biol. 2014;10:e1003494. doi: 10.1371/journal.pcbi.1003494. PubMed DOI PMC

Robinson MD, McCarthy DJ. Smyth GK: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40. doi: 10.1093/bioinformatics/btp616. PubMed DOI PMC

Zagordi O, Geyrhofer L, Roth V, Beerenwinkel N. Deep sequencing of a genetically heterogeneous sample: local haplotype reconstruction and read error correction. J Comput Biol. 2010;17:417–28. doi: 10.1089/cmb.2009.0164. PubMed DOI

Skums P, Dimitrova Z, Campo DS, Vaughan G, Rossi L, Forbi JC, et al. Efficient error correction for next-generation sequencing of viral amplicons. BMC bioinformatics. 2012;13 Suppl(10):S6. doi: 10.1186/1471-2105-13-S10-S6. PubMed DOI PMC

Beerenwinkel N, Gunthard HF, Roth V, Metzner KJ. Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data. Front Microbiol. 2012;3:329. doi: 10.3389/fmicb.2012.00329. PubMed DOI PMC

Bolstad BM. Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. Dissertation. University of California, Berkeley, Department of Statistics. 2004.

McGee M, Chen Z. Parameter estimation for the exponential-normal convolution model for background correction of affymetrix GeneChip data. Statistical applications in genetics and molecular biology. 2006; 5:Article24. PubMed

Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4:249–64. doi: 10.1093/biostatistics/4.2.249. PubMed DOI

Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 2003;31:e15. doi: 10.1093/nar/gng015. PubMed DOI PMC

Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19:185–93. doi: 10.1093/bioinformatics/19.2.185. PubMed DOI

Niklas N, Proll J, Danzer M, Stabentheiner S, Hofer K, Gabriel C. Routine performance and errors of 454 HLA exon sequencing in diagnostics. BMC bioinformatics. 2013;14:176. doi: 10.1186/1471-2105-14-176. PubMed DOI PMC

Poss M, Ross HA, Painter SL, Holley DC, Terwee JA, Vandewoude S, et al. Feline lentivirus evolution in cross-species infection reveals extensive G-to-A mutation and selection on key residues in the viral polymerase. J Virol. 2006;80:2728–37. doi: 10.1128/JVI.80.6.2728-2737.2006. PubMed DOI PMC

Bowker AH. A test for symmetry in contingency tables. J Am Stat Assoc. 1948;43:572–4. doi: 10.1080/01621459.1948.10483284. PubMed DOI

Stuart A. A test for homogeneity of the marginal distributions in a two-way classification. Biometrika. 1955;42:412–6. doi: 10.1093/biomet/42.3-4.412. DOI

Ababneh F, Jermiin LS, Ma C, Robinson J. Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences. Bioinformatics. 2006;22:1225–31. doi: 10.1093/bioinformatics/btl064. PubMed DOI

Hayward JJ, Rodrigo AG. Molecular epidemiology of feline immunodeficiency virus in the domestic cat (Felis catus) Vet Immunol Immunopathol. 2010;134:68–74. doi: 10.1016/j.vetimm.2009.10.011. PubMed DOI PMC

Chiu Y-L, Greene WC. The APOBEC3 cytidine deaminases: an innate defensive network opposing exogenous retroviruses and endogenous retroelements. Annu Rev Immunol. 2008;26:317–53. doi: 10.1146/annurev.immunol.26.021607.090350. PubMed DOI

Marin M, Rose KM, Kozak SL, Kabat D. HIV-1 Vif protein binds the editing enzyme APOBEC3G and induces its degradation. Nat Med. 2003;9:1398–403. doi: 10.1038/nm946. PubMed DOI

Conticello SG, Harris RS, Neuberger MS. The Vif protein of HIV triggers degradation of the human antiretroviral DNA deaminase APOBEC3G. Curr Biol. 2003;13:2009–13. doi: 10.1016/j.cub.2003.10.034. PubMed DOI

CLC Genomics Workbench [http://www.clcbio.com/products/clc-genomics-workbench/]

Bioconductor: Open Source Software for Bioinformatics [http://www.bioconductor.org/]

The R Project for Statistical Computing [http://www.r-project.org/]

SAS [http://www.sas.com/]