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Advancements in Microbial Genome Sequencing and Microbial Community Characterization

  • Bhaskar ReddyEmail author
Chapter

Abstract

The microorganism play an essential role in various metabolic activity associated with health, obesity, immune system, complex carbohydrate, nitrogen, sulfur, and xenobiotic metabolism etc. The identification of microorganism involved in such process is becoming possible with the sequencing of 16S rRNA amplicon and responsible gene through molecular cloning and then sequencing. The first-generation sequencing extensively facilitated the molecular characterization of microorganism and functional gene with expense of high cost with low throughput. The advent of next-generation sequencing technology enables the high-scale full-length 16S rRNA molecular characterization and genome sequencing with reduced time and cost with high yield. The present article describes available genomes in public database and the role of next- and third-generation sequencing technology contribution to the growth of genome and metagenome sequencing and its associated projects, their taxonomy, and functional characterization through bioinformatic analysis. This chapter also provides an overview on the metagenomic sequencing and functional characterization of three important ecological niches, viz., rumen, soil, and human gut. The massive advancement in high-throughput sequencing technology and bioinformatic analysis enabled robust genome and metagenome characterization in short time with reduced budget.

Keywords

Whole genome annotation Microbiome Metagenome Next-generation sequencing Bioinformatic analysis 

References

  1. Aagaard K, Riehle K, Ma J, Segata N, Mistretta TA, Coarfa C, Raza S, Rosenbaum S et al (2012) A metagenomic approach to characterization of the vaginal microbiome signature in pregnancy. PLoS One 7:e36466CrossRefPubMedPubMedCentralGoogle Scholar
  2. Adessi C, Matton G, Ayala G, Turcatti G, Mermod JJ, Mayer P, Kawashima E (2000) Solid phase DNA amplification: characterisation of primer attachment and amplification mechanisms. Nucleic Acids Res 28(20):E87Google Scholar
  3. Arabidopsis Genome I (2000) Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408:796–815CrossRefGoogle Scholar
  4. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI et al (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bennett GM, Moran NA (2013) Small, smaller, smallest: the origins and evolution of ancient dual symbioses in a Phloem-feeding insect. Genome Biol Evol 5:1675–1688CrossRefPubMedPubMedCentralGoogle Scholar
  6. Berendsen RL, Pieterse CM, Bakker PA (2012) The rhizosphere microbiome and plant health. Trends Plant Sci 17:478–486CrossRefGoogle Scholar
  7. Besemer J, Lomsadze A, Borodovsky M (2001) GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 29:2607–2618CrossRefPubMedPubMedCentralGoogle Scholar
  8. Blattner FR, Plunkett G 3rd, Bloch CA, Perna NT, Burland V, Riley M, Collado-Vides J, Glasner JD et al (1997) The complete genome sequence of Escherichia coli K-12. Science 277:1453–1462CrossRefGoogle Scholar
  9. Buchfink B, Xie C, Huson DH (2015) Fast and sensitive protein alignment using DIAMOND. Nat Methods 12:59–60CrossRefGoogle Scholar
  10. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421CrossRefPubMedPubMedCentralGoogle Scholar
  11. Cao Y, Fanning S, Proos S, Jordan K, Srikumar S (2017) A review on the applications of next generation sequencing technologies as applied to food-related microbiome studies. Front Microbiol 8:1829CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cho I, Blaser MJ (2012) The human microbiome: at the interface of health and disease. Nat Rev Genet 13:260–270CrossRefPubMedPubMedCentralGoogle Scholar
  13. Claesson MJ, Jeffery IB, Conde S, Power SE, O'Connor EM, Cusack S, Harris HM, Coakley M et al (2012) Gut microbiota composition correlates with diet and health in the elderly. Nature 488:178–184CrossRefGoogle Scholar
  14. Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676CrossRefGoogle Scholar
  15. Conlon MA, Bird AR (2014) The impact of diet and lifestyle on gut microbiota and human health. Nutrients 7:17–44CrossRefPubMedPubMedCentralGoogle Scholar
  16. Cook H, Ussery DW (2013) Sigma factors in a thousand E. coli genomes. Environ Microbiol 15:3121–3129CrossRefPubMedPubMedCentralGoogle Scholar
  17. Crielaard W, Zaura E, Schuller AA, Huse SM, Montijn RC, Keijser BJ (2011) Exploring the oral microbiota of children at various developmental stages of their dentition in the relation to their oral health. BMC Med Genet 4:22Google Scholar
  18. Delcher AL, Harmon D, Kasif S, White O, Salzberg SL (1999) Improved microbial gene identification with GLIMMER. Nucleic Acids Res 27:4636–4641CrossRefPubMedPubMedCentralGoogle Scholar
  19. Dethlefsen L, Huse S, Sogin ML, Relman DA (2008) The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing. PLoS Biol 6:e280CrossRefPubMedPubMedCentralGoogle Scholar
  20. Dicksved J, Halfvarson J, Rosenquist M, Jarnerot G, Tysk C, Apajalahti J, Engstrand L, Jansson JK (2008) Molecular analysis of the gut microbiota of identical twins with Crohn's disease. ISME J 2:716–727CrossRefGoogle Scholar
  21. Dinsdale EA, Edwards RA, Hall D, Angly F, Breitbart M, Brulc JM, Furlan M, Desnues C et al (2008) Functional metagenomic profiling of nine biomes. Nature 452:629–632CrossRefGoogle Scholar
  22. Dube AN, Moyo F, Dhlamini Z (2015) Metagenome sequencing of the greater kudu (Tragelaphus strepsiceros) rumen microbiome. Genome Announc 3Google Scholar
  23. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461CrossRefGoogle Scholar
  24. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, Peluso P, Rank D et al (2009) Real-time DNA sequencing from single polymerase molecules. Science 323:133–138CrossRefPubMedPubMedCentralGoogle Scholar
  25. Ekblom R, Wolf JB (2014) A field guide to whole-genome sequencing, assembly and annotation. Evol Appl 7:1026–1042CrossRefPubMedPubMedCentralGoogle Scholar
  26. Fedurco M, Romieu A, Williams S, Lawrence I, Turcatti G (2006) BTA, a novel reagent for DNA attachment on glass and efficient generation of solid-phase amplified DNA colonies. Nucleic Acids Res 34(3):e22Google Scholar
  27. Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlavage AR, Bult CJ, Tomb JF et al (1995) Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 269:496–512CrossRefPubMedPubMedCentralGoogle Scholar
  28. Forde BM, O’Toole PW (2013) Next-generation sequencing technologies and their impact on microbial genomics. Brief Funct Genomics 12:440–453CrossRefGoogle Scholar
  29. Francke C, Siezen RJ, Teusink B (2005) Reconstructing the metabolic network of a bacterium from its genome. Trends Microbiol 13:550–558CrossRefGoogle Scholar
  30. Gilbert JA, Jansson JK, Knight R (2014) The Earth Microbiome project: successes and aspirations. BMC Biol 12:69CrossRefPubMedPubMedCentralGoogle Scholar
  31. Goffeau A (1998) The yeast genome. Pathol Biol (Paris) 46:96–97Google Scholar
  32. Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17:333–351CrossRefGoogle Scholar
  33. Han K, Li ZF, Peng R, Zhu LP, Zhou T, Wang LG, Li SG, Zhang XB et al (2013) Extraordinary expansion of a Sorangium cellulosum genome from an alkaline milieu. Sci Rep 3:2101CrossRefPubMedPubMedCentralGoogle Scholar
  34. Handelsman J (2004) Metagenomics: application of genomics to uncultured microorganisms. Microbiol Mol Biol Rev 68:669–685CrossRefPubMedPubMedCentralGoogle Scholar
  35. Hartman WH, Ye R, Horwath WR, Tringe SG (2017) A genomic perspective on stoichiometric regulation of soil carbon cycling. ISME J 11:2652–2665CrossRefPubMedPubMedCentralGoogle Scholar
  36. Howe A, Yang F, Williams RJ, Meyer F, Hofmockel KS (2016) Identification of the core set of carbon-associated genes in a bioenergy grassland soil. PLoS One 11:e0166578CrossRefPubMedPubMedCentralGoogle Scholar
  37. Huang X, Madan A (1999) CAP3: a DNA sequence assembly program. Genome Res 9:868–877CrossRefPubMedPubMedCentralGoogle Scholar
  38. Human Microbiome Project Consortium (2012a) A framework for human microbiome research. Nature 486:215–221CrossRefGoogle Scholar
  39. Human Microbiome Project Consortium (2012b) Structure, function and diversity of the healthy human microbiome. Nature 486:207–214CrossRefGoogle Scholar
  40. Huse SM, Ye Y, Zhou Y, Fodor AA (2012) A core human microbiome as viewed through 16S rRNA sequence clusters. PLoS One 7:e34242CrossRefPubMedPubMedCentralGoogle Scholar
  41. Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data. Genome Res 17:377–386CrossRefPubMedPubMedCentralGoogle Scholar
  42. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11:119CrossRefPubMedPubMedCentralGoogle Scholar
  43. Ju J, Kim DH, Bi L, Meng Q, Bai X, Li Z, Li X, Marma MS et al (2006) Four-color DNA sequencing by synthesis using cleavable fluorescent nucleotide reversible terminators. Proc Natl Acad Sci U S A 103:19635–19640CrossRefPubMedPubMedCentralGoogle Scholar
  44. Judge K, Harris SR, Reuter S, Parkhill J, Peacock SJ (2015) Early insights into the potential of the Oxford Nanopore MinION for the detection of antimicrobial resistance genes. J Antimicrob Chemother 70:2775–2778CrossRefPubMedPubMedCentralGoogle Scholar
  45. Keegan KP, Glass EM, Meyer F (2016) MG-RAST, a metagenomics service for analysis of microbial community structure and function. Methods Mol Biol 1399:207–233CrossRefGoogle Scholar
  46. Kelley DR, Liu B, Delcher AL, Pop M, Salzberg SL (2012) Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering. Nucleic Acids Res 40:e9CrossRefGoogle Scholar
  47. Kolbert CP, Persing DH (1999) Ribosomal DNA sequencing as a tool for identification of bacterial pathogens. Curr Opin Microbiol 2:299–305CrossRefGoogle Scholar
  48. Kuczynski J, Stombaugh J, Walters WA, Gonzalez A, Caporaso JG, Knight R (2011) Using QIIME to analyze 16S rRNA gene sequences from microbial communities. Curr Protoc Bioinformatics Chapter 10:Unit 10 17Google Scholar
  49. Kunst F, Ogasawara N, Moszer I, Albertini AM, Alloni G, Azevedo V, Bertero MG, Bessieres P et al (1997) The complete genome sequence of the gram-positive bacterium Bacillus subtilis. Nature 390:249–256CrossRefGoogle Scholar
  50. Lamelas A, Gosalbes MJ, Manzano-Marin A, Pereto J, Moya A, Latorre A (2011) Serratia symbiotica from the aphid Cinara cedri: a missing link from facultative to obligate insect endosymbiont. PLoS Genet 7:e1002357CrossRefPubMedPubMedCentralGoogle Scholar
  51. Land ML, Hyatt D, Jun S-R, Kora GH, Hauser LJ, Lukjancenko O, Ussery DW (2014) Quality scores for 32,000 genomes. Stand Genomic Sci 9:20CrossRefPubMedPubMedCentralGoogle Scholar
  52. Laszlo AH, Derrington IM, Ross BC, Brinkerhoff H, Adey A, Nova IC, Craig JM, Langford KW et al (2014) Decoding long nanopore sequencing reads of natural DNA. Nat Biotechnol 32:829–833CrossRefPubMedPubMedCentralGoogle Scholar
  53. Leinonen R, Sugawara H, Shumway M, International Nucleotide Sequence Database Collaboration (2011) The sequence read archive. Nucleic Acids Res 39:D19–D21CrossRefGoogle Scholar
  54. Li E, Hamm CM, Gulati AS, Sartor RB, Chen H, Wu X, Zhang T, Rohlf FJ et al (2012a) Inflammatory bowel diseases phenotype, C. difficile and NOD2 genotype are associated with shifts in human ileum associated microbial composition. PLoS One 7:e26284CrossRefPubMedPubMedCentralGoogle Scholar
  55. Li RW, Connor EE, Li C, Baldwin Vi RL, Sparks ME (2012b) Characterization of the rumen microbiota of pre-ruminant calves using metagenomic tools. Environ Microbiol 14:129–139CrossRefGoogle Scholar
  56. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y et al (2012) SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience 1:18CrossRefPubMedPubMedCentralGoogle Scholar
  57. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS et al (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437:376–380CrossRefPubMedPubMedCentralGoogle Scholar
  58. McCutcheon JP, Moran NA (2011) Extreme genome reduction in symbiotic bacteria. Nat Rev Microbiol 10:13–26CrossRefGoogle Scholar
  59. Mitchell AL, Scheremetjew M, Denise H, Potter S, Tarkowska A, Qureshi M, Salazar GA, Pesseat S et al (2018) EBI metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies. Nucleic Acids Res 46:D726–D735CrossRefGoogle Scholar
  60. Morgan XC, Segata N, Huttenhower C (2013) Biodiversity and functional genomics in the human microbiome. Trends Genet 29:51–58CrossRefGoogle Scholar
  61. Mukherjee S, Stamatis D, Bertsch J, Ovchinnikova G, Katta HY, Mojica A, Chen IA, Kyrpides NC et al (2018) Genomes OnLine database (GOLD) v.7: updates and new features. Nucleic Acids Res 47:D649–D659CrossRefPubMedPubMedCentralGoogle Scholar
  62. Namiki T, Hachiya T, Tanaka H, Sakakibara Y (2012) MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 40:e155CrossRefPubMedPubMedCentralGoogle Scholar
  63. Nannipieri P (2014) Soil as a biological system and omics approaches. EQA – Int J Environ Qual 13:61Google Scholar
  64. Nathani NM, Patel AK, Mootapally CS, Reddy B, Shah SV, Lunagaria PM, Kothari RK, Joshi CG (2015) Effect of roughage on rumen microbiota composition in the efficient feed converter and sturdy Indian Jaffrabadi buffalo (Bubalus bubalis). BMC Genomics 16:1116CrossRefPubMedPubMedCentralGoogle Scholar
  65. Nesme J, Achouak W, Agathos SN, Bailey M, Baldrian P, Brunel D, Frostegard A, Heulin T et al (2016) Back to the future of soil metagenomics. Front Microbiol 7:73CrossRefPubMedPubMedCentralGoogle Scholar
  66. Patel V, Patel AK, Parmar NR, Patel AB, Reddy B, Joshi CG (2014) Characterization of the rumen microbiome of Indian Kankrej cattle (Bos indicus) adapted to different forage diet. Appl Microbiol Biotechnol 98:9749–9761CrossRefGoogle Scholar
  67. Peng Y, Leung HC, Yiu SM, Chin FY (2011) Meta-IDBA: a de Novo assembler for metagenomic data. Bioinformatics 27:i94–i101CrossRefPubMedPubMedCentralGoogle Scholar
  68. Peng Y, Leung HC, Yiu SM, Chin FY (2012) IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28:1420–1428CrossRefGoogle Scholar
  69. Pennisi E (2010) Genomics. Semiconductors inspire new sequencing technologies. Science 327:1190CrossRefPubMedPubMedCentralGoogle Scholar
  70. Pfreundt U, Kopf M, Belkin N, Berman-Frank I, Hess WR (2014) The primary transcriptome of the marine diazotroph Trichodesmium erythraeum IMS101. Sci Rep 4:6187CrossRefPubMedPubMedCentralGoogle Scholar
  71. Pitta DW, Kumar S, Veiccharelli B, Parmar N, Reddy B, Joshi CG (2014a) Bacterial diversity associated with feeding dry forage at different dietary concentrations in the rumen contents of Mehshana buffalo (Bubalus bubalis) using 16S pyrotags. Anaerobe 25:31–41CrossRefGoogle Scholar
  72. Pitta DW, Parmar N, Patel AK, Indugu N, Kumar S, Prajapathi KB, Patel AB, Reddy B et al (2014b) Bacterial diversity dynamics associated with different diets and different primer pairs in the rumen of Kankrej cattle. PLoS One 9:e111710CrossRefPubMedPubMedCentralGoogle Scholar
  73. Pop M (2009) Genome assembly reborn: recent computational challenges. Brief Bioinform 10:354–366CrossRefPubMedPubMedCentralGoogle Scholar
  74. Popa O, Hazkani-Covo E, Landan G, Martin W, Dagan T (2011) Directed networks reveal genomic barriers and DNA repair bypasses to lateral gene transfer among prokaryotes. Genome Res 21:599–609CrossRefPubMedPubMedCentralGoogle Scholar
  75. Pylro VS, Roesch LF, Ortega JM, do Amaral AM, Totola MR, Hirsch PR, Rosado AS, Goes-Neto A et al (2014) Brazilian microbiome project: revealing the unexplored microbial diversity--challenges and prospects. Microb Ecol 67:237–241CrossRefGoogle Scholar
  76. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, Nielsen T, Pons N et al (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464:59–65CrossRefPubMedPubMedCentralGoogle Scholar
  77. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R (2005) InterProScan: protein domains identifier. Nucleic Acids Res 33:W116–W120CrossRefPubMedPubMedCentralGoogle Scholar
  78. Ran L, Larsson J, Vigil-Stenman T, Nylander JA, Ininbergs K, Zheng WW, Lapidus A, Lowry S et al (2010) Genome erosion in a nitrogen-fixing vertically transmitted endosymbiotic multicellular cyanobacterium. PLoS One 5:e11486CrossRefPubMedPubMedCentralGoogle Scholar
  79. Reddy B, Dubey SK (2018) River Ganges water as reservoir of microbes with antibiotic and metal ion resistance genes: high throughput metagenomic approach. Environ Pollut 246:443–451CrossRefGoogle Scholar
  80. Reddy B, Singh KM, Patel AK, Antony A, Panchasara HJ, Joshi CG (2014) Insights into resistome and stress responses genes in Bubalus bubalis rumen through metagenomic analysis. Mol Biol Rep 41:6405–6417CrossRefGoogle Scholar
  81. Rho M, Tang H, Ye Y (2010) FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res 38:e191CrossRefPubMedPubMedCentralGoogle Scholar
  82. Sayers EW, Agarwala R, Bolton EE, Brister JR, Canese K, Clark K, Connor R, Fiorini N et al (2018) Database resources of the National Center for Biotechnology Information. Nucleic Acids ResGoogle Scholar
  83. Schloss PD, Handelsman J (2005) Metagenomics for studying unculturable microorganisms: cutting the Gordian knot. Genome Biol 6:229CrossRefPubMedPubMedCentralGoogle Scholar
  84. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541CrossRefPubMedPubMedCentralGoogle Scholar
  85. Singh KM, Reddy B, Patel AK, Panchasara H, Parmar N, Patel AB, Shah TM, Bhatt VD et al (2014a) Metagenomic analysis of buffalo rumen microbiome: effect of roughage diet on dormancy and sporulation genes. Meta Gene 2:252–268CrossRefPubMedPubMedCentralGoogle Scholar
  86. Singh KM, Reddy B, Patel D, Patel AK, Parmar N, Patel A, Patel JB, Joshi CG (2014b) High potential source for biomass degradation enzyme discovery and environmental aspects revealed through metagenomics of Indian buffalo rumen. Biomed Res Int 2014:267189PubMedPubMedCentralGoogle Scholar
  87. Singh KM, Jisha TK, Reddy B, Parmar N, Patel A, Patel AK, Joshi CG (2015a) Microbial profiles of liquid and solid fraction associated biomaterial in buffalo rumen fed green and dry roughage diets by tagged 16S rRNA gene pyrosequencing. Mol Biol Rep 42:95–103CrossRefGoogle Scholar
  88. Singh KM, Patel AK, Shah RK, Reddy B, Joshi CG (2015b) Potential functional gene diversity involved in methanogenesis and methanogenic community structure in Indian buffalo (Bubalus bubalis) rumen. J Appl Genet 56:411–426CrossRefGoogle Scholar
  89. Stanke M, Morgenstern B (2005) AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res 33:W465–W467CrossRefPubMedPubMedCentralGoogle Scholar
  90. Stothard P (2000) The sequence manipulation suite: JavaScript programs for analyzing and formatting protein and DNA sequences. BioTechniques 28(1102):1104Google Scholar
  91. Swerdlow H, Gesteland R (1990) Capillary gel electrophoresis for rapid, high resolution DNA sequencing. Nucleic Acids Res 18:1415–1419CrossRefPubMedPubMedCentralGoogle Scholar
  92. Thiele I, Palsson BO (2010) A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 5:93–121CrossRefPubMedPubMedCentralGoogle Scholar
  93. Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A et al (2017) A communal catalogue reveals Earth's multiscale microbial diversity. Nature 551:457–463CrossRefPubMedPubMedCentralGoogle Scholar
  94. Torsvik V, Sørheim R, Goksøyr J (1996) Total bacterial diversity in soil and sediment communities—a review. J Ind Microbiol 17:170–178Google Scholar
  95. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, Smith HO, Yandell M et al (2001) The sequence of the human genome. Science 291:1304–1351CrossRefGoogle Scholar
  96. Vogel TM, Simonet P, Jansson JK, Hirsch PR, Tiedje JM, van Elsas JD, Bailey MJ, Nalin R et al (2009) TerraGenome: a consortium for the sequencing of a soil metagenome. Nat Rev Microbiol 7:252CrossRefGoogle Scholar
  97. Vos M, Velicer GJ (2006) Genetic population structure of the soil bacterium Myxococcus xanthus at the centimeter scale. Appl Environ Microbiol 72:3615–3625CrossRefPubMedPubMedCentralGoogle Scholar
  98. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267CrossRefPubMedPubMedCentralGoogle Scholar
  99. Westbrook A, Ramsdell J, Schuelke T, Normington L, Bergeron RD, Thomas WK, MacManes MD (2017) PALADIN: protein alignment for functional profiling whole metagenome shotgun data. Bioinformatics 33:1473–1478CrossRefPubMedPubMedCentralGoogle Scholar
  100. Widmer F, Shaffer BT, Porteous LA, Seidler RJ (1999) Analysis of nifH gene pool complexity in soil and litter at a Douglas fir forest site in the Oregon cascade mountain range. Appl Environ Microbiol 65:374–380PubMedPubMedCentralGoogle Scholar
  101. Wu H, Fang Y, Yu J, Zhang Z (2014) The quest for a unified view of bacterial land colonization. ISME J 8:1358–1369CrossRefPubMedPubMedCentralGoogle Scholar
  102. Xu J (2006) Microbial ecology in the age of genomics and metagenomics: concepts, tools, and recent advances. Mol Ecol 15:1713–1731CrossRefGoogle Scholar
  103. Xue PP, Carrillo Y, Pino V, Minasny B, McBratney AB (2018) Soil properties drive microbial community structure in a large scale transect in south eastern Australia. Sci Rep 8:11725CrossRefPubMedPubMedCentralGoogle Scholar
  104. Yassour M, Vatanen T, Siljander H, Hamalainen AM, Harkonen T, Ryhanen SJ, Franzosa EA, Vlamakis H et al (2016) Natural history of the infant gut microbiome and impact of antibiotic treatment on bacterial strain diversity and stability. Sci Transl Med, 8:343ra381Google Scholar
  105. Ye Y, Choi JH, Tang H (2011) RAPSearch: a fast protein similarity search tool for short reads. BMC Bioinformatics 12:159CrossRefPubMedPubMedCentralGoogle Scholar
  106. Zani S, Mellon MT, Collier JL, Zehr JP (2000) Expression of nifH genes in natural microbial assemblages in Lake George, New York, detected by reverse transcriptase PCR. Appl Environ Microbiol 66:3119–3124CrossRefPubMedPubMedCentralGoogle Scholar
  107. Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821–829CrossRefPubMedPubMedCentralGoogle Scholar
  108. Zhu W, Lomsadze A, Borodovsky M (2010) Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 38:e132CrossRefPubMedPubMedCentralGoogle Scholar
  109. Zimin AV, Marcais G, Puiu D, Roberts M, Salzberg SL, Yorke JA (2013) The MaSuRCA genome assembler. Bioinformatics 29:2669–2677CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Centre of Advanced Study in Botany, Institute of ScienceBanaras Hindu UniversityVaranasiIndia

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