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Volume 28 Issue 4
August 2013
    Citation: Yan Wang, Reda Rawi, Daniel Hoffmann, Binlian Sun, Rongge Yang. Inference of Global HIV-1 Sequence Patterns and Preliminary Feature Analysis .VIROLOGICA SINICA, 2013, 28(4) : 228-238.  http://dx.doi.org/10.1007/s12250-013-3348-z
    shu

    Inference of Global HIV-1 Sequence Patterns and Preliminary Feature Analysis

    cstr: 32224.14.s12250-013-3348-z
    • 1.

      AIDS and HIV Research Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China

    • 2.

      Research Group for Bioinformatics, Center for Medical Biology, University of Duisburg-Essen, Essen 45141, Germany

    • Corresponding author: Binlian Sun, sunbl@wh.iov.cn
      Rongge Yang, ryang@wh.iov.cn
    • Received Date: 04 June 2013
      Accepted Date: 26 July 2013
      Published Date: 27 July 2013
      Available online: 01 August 2013
    • The epidemiology of HIV-1 varies in different areas of the world, and it is possible that this complexity may leave unique footprints in the viral genome. Thus, we attempted to find significant patterns in global HIV-1 genome sequences. By applying the rule inference algorithm RIPPER (Repeated Incremental Pruning to Produce Error Reduction) to multiple sequence alignments of Env sequences from four classes of compiled datasets, we generated four sets of signature patterns. We found that these patterns were able to distinguish southeastern Asian from non- southeastern Asian sequences with 97.5% accuracy, Chinese from non-Chinese sequences with 98.3% accuracy, African from non-African sequences with 88.4% accuracy, and southern African from non-southern African sequences with 91.2% accuracy. These patterns showed different associations with subtypes and with amino acid positions. In addition, some signature patterns were characteristic of the geographic area from which the sample was taken. Amino acid features corresponding to the phylogenetic clustering of HIV-1 sequences were consistent with some of the deduced patterns. Using a combination of patterns inferred from subtypes B, C, and all subtypes chimeric with CRF01_AE worldwide, we found that signature patterns of subtype C were extremely common in some sampled countries (for example, Zambia in southern Africa), which may hint at the origin of this HIV-1 subtype and the need to pay special attention to this area of Africa. Signature patterns of subtype B sequences were associated with different countries. Even more, there are distinct patterns at single position 21 with glycine, leucine and isoleucine corresponding to subtype C, B and all possible recombination forms chimeric with CRF01_AE, which also indicate distinct geographic features. Our method widens the scope of inference of signature from geographic, genetic, and genomic viewpoints. These findings may provide a valuable reference for epidemiological research or vaccine design.
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      1. Avenue M, Hill M, Cohen W W, Of C, and Pruning R. 1994. Fast E ective Rule Induction 2 Previous work 1 in introduction.

      2. Bello G, Eyer-Silva W a, Couto-Fernandez J C, Guimarães M L, Chequer-Fernandez S L, Teixeira S L M, and Morgado M G. 2007. Demographic history of HIV-1 subtypes B and F in Brazil. Infection, genetics and evolution :journal of molecular epidemiology and evolutionary genetics in infectious diseases, 7:263-270.
          doi: 10.1016/j.meegid.2006.11.002

      3. Blair C, and Murphy R W. 2011. Recent trends in molecular phylogenetic analysis:where to next? The Journal of heredity, 102:130-138.
          doi: 10.1093/jhered/esq092

      4. Buonaguro L, Tagliamonte M, Tornesello M L, and Buonaguro F M. 2007. Genetic and phylogenetic evolution of HIV-1 in a low subtype heterogeneity epidemic:the Italian example. Retrovirology, 4:34-34.
          doi: 10.1186/1742-4690-4-34

      5. Butler I F, Pandrea I, Marx P a, and Apetrei C. 2007. HIV genetic diversity:biological and public health consequences. Current HIV research, 5:23-45.
          doi: 10.2174/157016207779316297

      6. Cai Y-D, Lu L, Chen L, and He J-F. 2010. Predicting subcellular location of proteins using integrated-algorithm method. Molecular diversity, 14:551-558.
          doi: 10.1007/s11030-009-9182-4

      7. Crooks G E, Hon G, Chandonia J-m, and Brenner S E. 2004. WebLogo : A Sequence Logo Generator. 1188-1190.

      8. Delano W L, and Ph D. 2004. PyMOL User' s Guide written by.

      9. Delatorre E O, and Bello G. 2012. Phylodynamics of HIV-1 subtype C epidemic in east Africa. PloS one, 7:e41904-e41904.
          doi: 10.1371/journal.pone.0041904

      10. Dybowski J N, Riemenschneider M, Hauke S, Pyka M, Verheyen J, Hoffmann D, and Heider D. 2011. Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers. BioData mining, 4:26-26.
          doi: 10.1186/1756-0381-4-26

      11. Edgar R C. 2004. MUSCLE:multiple sequence alignment with high accuracy and high throughput. Nucleic acids research, 32:1792-1797.
          doi: 10.1093/nar/gkh340

      12. Fauci A S, Johnston M I, Dieffenbach C W, Burton D R, Hammer S M, Hoxie J a, Martin M, Overbaugh J, Watkins D I, Mahmoud A, and Greene W C. 2008. HIV vaccine research:the way forward. Science (New York, N.Y.), 321:530-532.
          doi: 10.1126/science.1161000

      13. Fryer H R, and McLean A R. 2011. Modelling the spread of HIV immune escape mutants in a vaccinated population. PLoS computational biology, 7:e1002289-e1002289.
          doi: 10.1371/journal.pcbi.1002289

      14. Gentleman R C, Carey V J, Bates D M, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, and Gentry J. 2004. Bioconductor:open software development for computational biology and bioinformatics. Genome biology, 5:R80
          doi: 10.1186/gb-2004-5-10-r80

      15. Gilbert M T P, Rambaut A, Wlasiuk G, Spira T J, Pitchenik A E, and Worobey M. 2007. The emergence of HIV/AIDS in the Americas and beyond. Proceedings of the National Academy of Sciences of the United States of America, 104:18566-18570.
          doi: 10.1073/pnas.0705329104

      16. Grant B J, Rodrigues A P C, ElSawy K M, McCammon J A, and Caves L S D. 2006. Bio3d:an R package for the comparative analysis of protein structures. Bioinformatics, 22:2695-2696.
          doi: 10.1093/bioinformatics/btl461

      17. Hemelaar J. 2012. The origin and diversity of the HIV-1 pandemic. Trends in Molecular Medicine, 18:182-192.
          doi: 10.1016/j.molmed.2011.12.001

      18. Hornik K, Buchta C, and Zeileis A. 2009. Open-source machine learning:R meets Weka. Computational Statistics, 24:225–232.
          doi: 10.1007/s00180-008-0119-7

      19. Junqueira D M, de Medeiros R M, Matte M C C, Araújo L A L, Chies J A B, Ashton-Prolla P, and Almeida S E D M. 2011. Reviewing the history of HIV-1:spread of subtype B in the Americas. PloS one, 6:e27489-e27489.
          doi: 10.1371/journal.pone.0027489

      20. Kallings L O. 2008. The first postmodern pandemic:25 years of HIV/ AIDS. Journal of internal medicine, 263:218-243.
          doi: 10.1111/jim.2008.263.issue-3

      21. Karlsson Hedestam G B, Fouchier R a M, Phogat S, Burton D R, Sodroski J, and Wyatt R T. 2008. The challenges of eliciting neutralizing antibodies to HIV-1 and to influenza virus. Nature reviews. Microbiology, 6:143-155.
          doi: 10.1038/nrmicro1819

      22. Li Y, Uenishi R, Hase S, Liao H, Li X-J, Tsuchiura T, Tee K K, Pybus O G, and Takebe Y. 2010. Explosive HIV-1 subtype B' epidemics in Asia driven by geographic and risk group founder events. Virology, 402:223-227.
          doi: 10.1016/j.virol.2010.03.048

      23. Liao H, Tee K K, Hase S, Uenishi R, Li X-J, Kusagawa S, Thang P H, Hien N T, Pybus O G, and Takebe Y. 2009. Phylodynamic analysis of the dissemination of HIV-1 CRF01_AE in Vietnam. Virology, 391:51-56.
          doi: 10.1016/j.virol.2009.05.023

      24. Lihana R W. 2012. Update on HIV-1 Diversity in Africa : A Decade in Review. 83-100.

      25. Liu J, and Zhang C. 2011. Phylogeographic analyses reveal a crucial role of Xinjiang in HIV-1 CRF07_BC and HCV 3a transmissions in Asia. PloS one, 6:e23347-e23347.
          doi: 10.1371/journal.pone.0023347

      26. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, and Nielsen M. 2008. NetMHC-3.0:accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Research, 36:W509-W512.

      27. Lynch R M, Shen T, Gnanakaran S, and Derdeyn C a. 2009. Appreciating HIV type 1 diversity:subtype differences in Env. AIDS research and human retroviruses, 25:237-248.
          doi: 10.1089/aid.2008.0219

      28. Masciotra S, Livellara B, Belloso W, Clara L, Tanuri a, Ramos a C, Baggs J, Lal R, and Pieniazek D. 2000. Evidence of a high frequency of HIV-1 subtype F infections in a heterosexual population in Buenos Aires, Argentina. AIDS research and human retroviruses, 16:1007-1014.
          doi: 10.1089/08892220050058425

      29. Meng Z, Xin R, Zhong P, Zhang C, Abubakar Y F, Li J, Liu W, Zhang X, and Xu J. 2012. A new migration map of HIV-1 CRF07_BC in China:analysis of sequences from 12 provinces over a decade. PloS one, 7:e52373-e52373.
          doi: 10.1371/journal.pone.0052373

      30. Moran D, and Jordaan J a. 2007. HIV/AIDS in Russia:determinants of regional prevalence. International journal of health geographics, 6:22-22.
          doi: 10.1186/1476-072X-6-22

      31. Morcos F, Pagnani A, Lunt B, Bertolino A, Marks D S, Sander C, Zecchina R, Onuchic J N, Hwa T, and Weigt M. Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proceedings of the National Academy of Sciences of the United States of America, 108: E1293-E1301.

      32. Morris C N, and Ferguson a G. 2006. Estimation of the sexual transmission of HIV in Kenya and Uganda on the trans-Africa highway:the continuing role for prevention in high risk groups. Sexually transmitted infections, 82:368-371
          doi: 10.1136/sti.2006.020933

      33. Njai H F, Gali Y, Vanham G, Clybergh C, Jennes W, Vidal N, Butel C, Mpoudi-Ngolle E, Peeters M, and Ariën K K. 2006. The predominance of Human Immunodeficiency Virus type 1 (HIV-1) circulating recombinant form 02 (CRF02_AG) in West Central Africa may be related to its replicative fitness. Retrovirology, 3:40-40.
          doi: 10.1186/1742-4690-3-40

      34. Paradis E, Claude J, and Strimmer K. 2004. APE:Analyses of Phylogenetics and Evolution in R language. Bioinformatics, 20:289-290.
          doi: 10.1093/bioinformatics/btg412

      35. Paraschiv S, Otelea D, Batan I, Baicus C, Magiorkinis G, and Paraskevis D. 2012. Molecular typing of the recently expanding subtype B HIV-1 epidemic in Romania:evidence for local spread among MSMs in Bucharest area. Infection, genetics and evolution :journal of molecular epidemiology and evolutionary genetics in infectious diseases, 12:1052-1057.
          doi: 10.1016/j.meegid.2012.03.003

      36. Paraskevis D, Pybus O, Magiorkinis G, Hatzakis A, Wensing A M, van de Vijver D a, Albert J, Angarano G, Asjö B, Balotta C, Boeri E, Camacho R, Chaix M-L, Coughlan S, Costagliola D, De Luca A, de Mendoza C, Derdelinckx I, Grossman Z, Hamouda O, Hoepelman I, Horban A, Korn K, Kücherer C, Leitner T, Loveday C, Macrae E, Maljkovic-Berry I, Meyer L, Nielsen C, Op de Coul E L, Ormaasen V, Perrin L, Puchhammer-Stöckl E, Ruiz L, Salminen M O, Schmit J-C, Schuurman R, Soriano V, Stanczak J, Stanojevic M, Struck D, Van Laethem K, Violin M, Yerly S, Zazzi M, Boucher C a, and Vandamme A-M. 2009. Tracing the HIV-1 subtype B mobility in Europe:a phylogeographic approach. Retrovirology, 6:49-49.
          doi: 10.1186/1742-4690-6-49

      37. Pérez L, Thomson M M, Bleda M J, Aragonés C, González Z, Pérez J, Sierra M, Casado G, Delgado E, and Nájera R. 2006. HIV Type 1 molecular epidemiology in cuba:high genetic diversity, frequent mosaicism, and recent expansion of BG intersubtype recombinant forms. AIDS research and human retroviruses, 22:724-733.
          doi: 10.1089/aid.2006.22.724

      38. Pollakis G, Abebe A, Kliphuis A, De Wit T F R, Fisseha B, Tegbaru B, Tesfaye G, Negassa H, Mengistu Y, Fontanet A L, Cornelissen M, and Goudsmit J. 2003. Recombination of HIV type 1C (C'/C") in Ethiopia:possible link of EthHIV-1C' to subtype C sequences from the high-prevalence epidemics in India and Southern Africa. AIDS research and human retroviruses, 19:999-1008.
          doi: 10.1089/088922203322588350

      39. Poonpiriya V, Sungkanuparph S, Leechanachai P, Pasomsub E, Watitpun C, Chunhakan S, and Chantratita W. 2008. A study of seven rule-based algorithms for the interpretation of HIV-1 genotypic resistance data in Thailand. Journal of virological methods, 151:79-86.
          doi: 10.1016/j.jviromet.2008.03.017

      40. Restif O. 2009. Evolutionary epidemiology 20 years on:challenges and prospects. Infection, genetics and evolution :journal of molecular epidemiology and evolutionary genetics in infectious diseases, 9:108-123.
          doi: 10.1016/j.meegid.2008.09.007

      41. Sharp P M, and Hahn B H. 2011. Origins of HIV and the AIDS Pandemic. 1-22.

      42. Sharp P M, and Hahn B H. 2011. Origins of HIV and the AIDS pandemic. Cold Spring Harbor perspectives in medicine, 1:a006841-a006841.

      43. Shen C, Craigo J, Ding M, Chen Y, and Gupta P. 2011. Origin and dynamics of HIV-1 subtype C infection in India. PloS one, 6:e25956-e25956.
          doi: 10.1371/journal.pone.0025956

      44. Sierra M, Thomson M M, Posada D, Pérez L, Aragonés C, González Z, Pérez J, Casado G, and Nájera R. 2007. Identification of 3 phylogenetically related HIV-1 BG intersubtype circulating recombinant forms in Cuba. Journal of acquired immune deficiency syndromes (1999), 45:151-160.
          doi: 10.1097/QAI.0b013e318046ea47

      45. Silveira J, Santos A F, Martínez A M B, Góes L R, Mendoza-Sassi R, Muniz C P, Tupinambás U, Soares M a, and Greco D B. 2012. Heterosexual transmission of human immunodeficiency virus type 1 subtype C in southern Brazil. Journal of clinical virology :the official publication of the Pan American Society for Clinical Virology, 54:36-41.
          doi: 10.1016/j.jcv.2012.01.017

      46. Spira S. 2003. Impact of clade diversity on HIV-1 virulence, antiretroviral drug sensitivity and drug resistance. Journal of Antimicrobial Chemotherapy, 51:229-240.
          doi: 10.1093/jac/dkg079

      47. Taylor B S, and Hammer S M. 2008. The challenge of HIV-1 subtype diversity. The New England journal of medicine, 359:1965-1966.
          doi: 10.1056/NEJMc086373

      48. Tebit D M, and Arts E J. 2011. Tracking a century of global expansion and evolution of HIV to drive understanding and to combat disease. The Lancet Infectious Diseases, 11:45-56.
          doi: 10.1016/S1473-3099(10)70186-9

      49. Villanova F E. 2010. Diversity of HIV-1 Subtype B : Implications to the Origin of BF Recombinants. 5: 1-9.

      50. Walker B D, and Burton D R. 2008. Toward an AIDS vaccine. Science (New York, N.Y.), 320:760-764.
          doi: 10.1126/science.1152622

      51. Walker P R, Pybus O G, Rambaut A, and Holmes E C. 2005. Comparative population dynamics of HIV-1 subtypes B and C:subtype-specific differences in patterns of epidemic growth. Infection, genetics and evolution :journal of molecular epidemiology and evolutionary genetics in infectious diseases, 5:199-208.
          doi: 10.1016/j.meegid.2004.06.011

      52. Wang Y, Rawi R, Wilms C, Heider D, Yang R, and Hoffmann D. 2013. A small set of succinct signature patterns distinguishes Chinese and non-Chinese HIV-1 genomes. PloS one, 8:e58804-e58804.
          doi: 10.1371/journal.pone.0058804

      53. Witten I H, Frank E, and Hall M A. 2011. Data Mining: Practical Machine Learning Tools and Techniques: Practical Machine Learning Tools and Techniques. Elsevier

      54. Worobey M, Gemmel M, Teuwen D E, Haselkorn T, Kunstman K, Bunce M, Muyembe J-j, Kabongo J-m M, Kalengayi R M, Van Marck E, Gilbert M T P, Wolinsky S M, Kalengayi M, and Marck E V. 2008. Direct evidence of extensive diversity of HIV-1 in Kinshasa by 1960. Nature, 455:661-664.
          doi: 10.1038/nature07390

      55. Yang O O. 2009. Candidate vaccine sequences to represent intra-and inter-clade HIV-1 variation. PloS one, 4:e7388-e7388.
          doi: 10.1371/journal.pone.0007388

      56. Zhao Y. 2011. R and Data Mining: Examples and Case Studies 1.

      57. Zhu T, Korber B T, Nahmias a J, Hooper E, Sharp P M, and Ho D D. 1998. An African HIV-1 sequence from 1959 and implications for the origin of the epidemic. Nature, 391:594-597.
          doi: 10.1038/35400

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      Inference of Global HIV-1 Sequence Patterns and Preliminary Feature Analysis

        Corresponding author: Binlian Sun, sunbl@wh.iov.cn
        Corresponding author: Rongge Yang, ryang@wh.iov.cn
      • 1. AIDS and HIV Research Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China
      • 2. Research Group for Bioinformatics, Center for Medical Biology, University of Duisburg-Essen, Essen 45141, Germany
      • Received Date: 04 June 2013
      • Accepted Date: 26 July 2013
      • Published Date: 27 July 2013

      Abstract: The epidemiology of HIV-1 varies in different areas of the world, and it is possible that this complexity may leave unique footprints in the viral genome. Thus, we attempted to find significant patterns in global HIV-1 genome sequences. By applying the rule inference algorithm RIPPER (Repeated Incremental Pruning to Produce Error Reduction) to multiple sequence alignments of Env sequences from four classes of compiled datasets, we generated four sets of signature patterns. We found that these patterns were able to distinguish southeastern Asian from non- southeastern Asian sequences with 97.5% accuracy, Chinese from non-Chinese sequences with 98.3% accuracy, African from non-African sequences with 88.4% accuracy, and southern African from non-southern African sequences with 91.2% accuracy. These patterns showed different associations with subtypes and with amino acid positions. In addition, some signature patterns were characteristic of the geographic area from which the sample was taken. Amino acid features corresponding to the phylogenetic clustering of HIV-1 sequences were consistent with some of the deduced patterns. Using a combination of patterns inferred from subtypes B, C, and all subtypes chimeric with CRF01_AE worldwide, we found that signature patterns of subtype C were extremely common in some sampled countries (for example, Zambia in southern Africa), which may hint at the origin of this HIV-1 subtype and the need to pay special attention to this area of Africa. Signature patterns of subtype B sequences were associated with different countries. Even more, there are distinct patterns at single position 21 with glycine, leucine and isoleucine corresponding to subtype C, B and all possible recombination forms chimeric with CRF01_AE, which also indicate distinct geographic features. Our method widens the scope of inference of signature from geographic, genetic, and genomic viewpoints. These findings may provide a valuable reference for epidemiological research or vaccine design.

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