Extracting data from the muck: Deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing

Current Opinion in Biotechnology

Volumn 28, Issue , 2014, Pages 103-110

  Solomon, Kevin V ^a   Haitjema, Charles H ^a   Thompson, Dawn A ^b   O'Malley, Michelle A ^a  

^a University of California   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMALS; BACTERIA; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; GENOME; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; PLANTS; PROTEOMICS; SEQUENCE ANALYSIS, DNA; SEQUENCE ANALYSIS, RNA;

EID: 84893437280     PISSN: 09581669     EISSN: 18790429     Source Type: Journal    
DOI: 10.1016/j.copbio.2014.01.007     Document Type: Review

References (83)

1. Vartoukian S.R., Palmer R.M., Wade W.G. Strategies for culture of "unculturable" bacteria. FEMS Microbiol Lett 2010, 309:1-7.
2. Hess M., Sczyrba A., Egan R., Kim T.-W., Chokhawala H., Schroth G., Luo S., Clark D.S., Chen F., Zhang T., et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science 2011, 331:463-467.
3. Xie W., Wang F., Guo L., Chen Z., Sievert S.M., Meng J., Huang G., Li Y., Yan Q., Wu S., et al. Comparative metagenomics of microbial communities inhabiting deep-sea hydrothermal vent chimneys with contrasting chemistries. ISME J 2011, 5:414-426.
4. Qin J., Li Y., Cai Z., Li S., Zhu J., Zhang F., Liang S., Zhang W., Guan Y., Shen D., et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 2012, 490:55-60.
5. Sommer F., Bäckhed F. The gut microbiota - masters of host development and physiology. Nat Rev Microbiol 2013, 11:227-238.
6. Kang H.-S., Brady S.F. Arimetamycin A: improving clinically relevant families of natural products through sequence-guided screening of soil metagenomes. Angew Chem Int Ed 2013, 10.1002/anie.201305109.
7. Metzker M.L. Sequencing technologies - the next generation. Nat Rev Genet 2010, 11:31-46.
8. Adessi C., Matton G., Ayala G., Turcatti G., Mermod J.-J., Mayer P., Kawashima E. Solid phase DNA amplification: characterisation of primer attachment and amplification mechanisms. Nucleic Acids Res 2000, 28. e87.
9. Dressman D., Yan H., Traverso G., Kinzler K.W., Vogelstein B. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc Natl Acad Sci 2003, 100:8817-8822.
10. Simon C., Daniel R. Metagenomic analyses: past and future trends. Appl Environ Microbiol 2011, 77:1153-1161.
11. Zeng J., Liu Y., Liu W., Liu X., Liu F., Huang P., Zhu P., Chen J., Shi M., Guo F., et al. Integration of transcriptome, proteome and metabolism data reveals the alkaloids biosynthesis in Macleaya cordata and Macleaya microcarpa. PLoS ONE 2013, 8:e53409.
12. Chaisson M.J., Brinza D., Pevzner P.A. De novo fragment assembly with short mate-paired reads: does the read length matter?. Genome Res 2008, 10.1101/gr.079053.108.
13. Youssef N.H., Couger M.B., Struchtemeyer C.G., Liggenstoffer A.S., Prade R.A., Najar F.Z., Atiyeh H.K., Wilkins M.R., Elshahed M.S. Genome of the anaerobic fungus Orpinomyces sp. C1A reveals the unique evolutionary history of a remarkable plant biomass degrader [Internet]. Appl Environ Microbiol 2013, 10.1128/AEM.00821-13.
14. Sanger F., Nicklen S., Coulson A.R. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci USA 1977, 74:5463-5467.
15. Albertsen M., Hugenholtz P., Skarshewski A., Nielsen K.L., Tyson G.W., Nielsen P.H. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nat Biotechnol 2013, 31:533-538.
16. Castelle C.J., Hug L.A., Wrighton K.C., Thomas B.C., Williams K.H., Wu D., Tringe S.G., Singer S.W., Eisen J.A., Banfield J.F. Extraordinary phylogenetic diversity and metabolic versatility in aquifer sediment [Internet]. Nat Commun 2013, 4.
17. Iverson V., Morris R.M., Frazar C.D., Berthiaume C.T., Morales R.L., Armbrust E.V. Untangling genomes from metagenomes: revealing an uncultured class of marine Euryarchaeota. Science 2012, 335:587-590.
18. Di Rienzi S.C., Sharon I., Wrighton K.C., Koren O., Hug L.A., Thomas B.C., Goodrich J.K., Bell J.T., Spector T.D., Banfield J.F., et al. The human gut and groundwater harbor non-photosynthetic bacteria belonging to a new candidate phylum sibling to Cyanobacteria [Internet]. eLife 2013, 2.
19. Wrighton K.C., Thomas B.C., Sharon I., Miller C.S., Castelle C.J., VerBerkmoes N.C., Wilkins M.J., Hettich R.L., Lipton M.S., Williams K.H., et al. Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 2012, 337:1661-1665.
20. Trapnell C., Salzberg S.L. How to map billions of short reads onto genomes. Nat Biotechnol 2009, 27:455-457.
21. Paszkiewicz K., Studholme D.J. De novo assembly of short sequence reads. Brief Bioinform 2010, 11:457-472.
22. DiGuistini S., Liao N.Y., Platt D., Robertson G., Seidel M., Chan S.K., Docking T.R., Birol I., Holt R.A., Hirst M., et al. De novo genome sequence assembly of a filamentous fungus using Sanger, 454 and Illumina sequence data. Genome Biol 2009, 10:R94.
23. Grabherr M.G., Haas B.J., Yassour M., Levin J.Z., Thompson D.A., Amit I., Adiconis X., Fan L., Raychowdhury R., Zeng Q., et al. Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat Biotechnol 2011, 29:644-652.
24. Zerbino D.R., Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008, 18:821-829.
25. Simpson J.T., Wong K., Jackman S.D., Schein J.E., Jones S.J.M., Birol I. ABySS: a parallel assembler for short read sequence data. Genome Res 2009, 19:1117-1123.
26. Martin J.A., Wang Z. Next-generation transcriptome assembly. Nat Rev Genet 2011, 12:671-682.
27. Grigoriev I.V., Nordberg H., Shabalov I., Aerts A., Cantor M., Goodstein D., Kuo A., Minovitsky S., Nikitin R., Ohm R.A., et al. The genome portal of the Department of Energy Joint Genome Institute [Internet]. Nucleic Acids Res 2011, 10.1093/nar/gkr947.
28. Qi M., Wang P., O'Toole N., Barboza P.S., Ungerfeld E., Leigh M.B., Selinger L.B., Butler G., Tsang A., McAllister T.A., et al. Snapshot of the eukaryotic gene expression in muskoxen rumen-a metatranscriptomic approach. PLoS ONE 2011, 6:e20521.
29. Smale S.T., Kadonaga J.T. The RNA polymerase II core promoter. Annu Rev Biochem 2003, 72:449-479.
30. Gagniuc P., Ionescu-Tirgoviste C. Eukaryotic genomes may exhibit up to 10 generic classes of gene promoters. BMC Genomics 2012, 13:512.
31. Zhu W., Lomsadze A., Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 2010, 38. e132-e132.
32. Ter-Hovhannisyan V., Lomsadze A., Chernoff Y.O., Borodovsky M. Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res 2008, 18:1979-1990.
33. Stanke M., Schöffmann O., Morgenstern B., Waack S. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics 2006, 7:62.
34. Majoros W.H., Pertea M., Salzberg S.L. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 2004, 20:2878-2879.
35. Haas B.J., Delcher A.L., Mount S.M., Wortman J.R., Hannick L.I., Maiti R., Ronning C.M., Rusch D.B., Town C.D., et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res 2003, 31:5654-5666.
36. Armour C.D., Castle J.C., Chen R., Babak T., Loerch P., Jackson S., Shah J.K., Dey J., Rohl C.A., Johnson J.M., et al. Digital transcriptome profiling using selective hexamer priming for cDNA synthesis. Nat Methods 2009, 6:647-649.
37. Zhang Z., Theurkauf W.E., Weng Z., Zamore P.D. Strand-specific libraries for high throughput RNA sequencing (RNA-seq) prepared without poly(A) selection. Silence 2012, 3:9.
38. Levin J.Z., Yassour M., Adiconis X., Nusbaum C., Thompson D.A., Friedman N., Gnirke A., Regev A. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat Methods 2010, 7:709-715.
39. Yassour M., Pfiffner J., Levin J.Z., Adiconis X., Gnirke A., Nusbaum C., Thompson D.-A., Friedman N., Regev A. Strand-specific RNA sequencing reveals extensive regulated long antisense transcripts that are conserved across yeast species. Genome Biol 2010, 11:R87.
40. Wang X., Naqa I.M.E. Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics 2008, 24:325-332.
41. van der Burgt A., Fiers M.W., Nap J.-P., van Ham R.C. In silico miRNA prediction in metazoan genomes: balancing between sensitivity and specificity. BMC Genomics 2009, 10:204.
42. Jia P., Shi T., Cai Y., Li Y. Demonstration of two novel methods for predicting functional siRNA efficiency. BMC Bioinformatics 2006, 7:271.
43. Washietl S., Hofacker I.L., Stadler P.F. Fast and reliable prediction of noncoding RNAs. Proc Natl Acad Sci USA 2005, 102:2454-2459.
44. McGinnis S., Madden T.L. BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res 2004, 32:W20-W25.
45. Karplus K., Barrett C., Hughey R. Hidden Markov models for detecting remote protein homologies. Bioinformatics 1998, 14:846-856.
46. Benson D.A., Cavanaugh M., Clark K., Karsch-Mizrachi I., Lipman D.J., Ostell J., Sayers E.W. GenBank. Nucleic Acids Res 2013, 41:D36-D42.
47. Finn R.D., Tate J., Mistry J., Coggill P.C., Sammut S.J., Hotz H.-R., Ceric G., Forslund K., Eddy S.R., Sonnhammer E.L.L., et al. The Pfam protein families database. Nucleic Acids Res 2007, 36:D281-D288.
48. The UniProt, Consortium Update on activities at the Universal Protein Resource (UniProt) in 2013. Nucleic Acids Res 2012, 41:D43-D47.
49. Hunter S., Jones P., Mitchell A., Apweiler R., Attwood T.K., Bateman A., Bernard T., Binns D., Bork P., Burge S., et al. InterPro in 2011: new developments in the family and domain prediction database. Nucleic Acids Res 2012, 40:D306-D312.
50. Cantarel B.L., Coutinho P.M., Rancurel C., Bernard T., Lombard V., Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res 2009, 37:D233-D238.
51. Conesa A., Götz S., García-Gómez J.M., Terol J., Talón M., Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21:3674-3676.
52. Götz S., García-Gómez J.M., Terol J., Williams T.D., Nagaraj S.H., Nueda M.J., Robles M., Talón M., Dopazo J., Conesa A. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res 2008, 36:3420-3435.
53. Haas B.J., Papanicolaou A., Yassour M., Grabherr M., Blood P.D., Bowden J., Couger M.B., Eccles D., Li B., Lieber M., et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 2013, 8:1494-1512.
54. Ashburner M., Ball C.A., Blake J.A., Botstein D., Butler H., Cherry J.M., Davis A.P., Dolinski K., Dwight S.S., Eppig J.T., et al. Gene ontology: tool for the unification of biology. Nat Genet 2000, 25:25-29.
55. Kanehisa M., Goto S., Sato Y., Furumichi M., Tanabe M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 2011, 40:D109-D114.
56. Ong W.D., Voo L.-Y.C., Kumar V.S. De novo assembly, characterization and functional annotation of pineapple fruit transcriptome through massively parallel sequencing. PLoS ONE 2012, 7:e46937.
57. Li C., Weng S., Chen Y., Yu X., Lü L., Zhang H., He J., Xu X. Analysis of Litopenaeus vannamei transcriptome using the next-generation DNA sequencing technique. PLoS ONE 2012, 7:e47442.
58. Li B., Dewey C.N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 2011, 12:323.
59. Wang L., Feng Z., Wang X., Wang X., Zhang X. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 2010, 26:136-138.
60. Leng N., Dawson J.A., Thomson J.A., Ruotti V., Rissman A.I., Smits B.M.G., Haag J.D., Gould M.N., Stewart R.M., Kendziorski C. EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics 2013, 10.1093/bioinformatics/btt087.
61. Clark N.R., Ma'ayan A. Introduction to statistical methods for analyzing large data sets: gene-set enrichment analysis. Sci Signal 2011, 4:tr4.
62. Luo W., Friedman M.S., Shedden K., Hankenson K.D., Woolf P.J. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics 2009, 10:161.
63. Subramanian A., Tamayo P., Mootha V.K., Mukherjee S., Ebert B.L., Gillette M.A., Paulovich A., Pomeroy S.L., Golub T.R., Lander E.S., et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005, 102:15545-15550.
64. Ullah U., Tripathi P., Lahesmaa R., Rao K.V.S. Gene set enrichment analysis identifies LIF as a negative regulator of human Th2 cell differentiation [Internet]. Sci Rep 2012, 2.
65. He K., Chen Z., Ma Y., Pan Y. Identification of high-copper-responsive target pathways in Atp7b knockout mouse liver by GSEA on microarray data sets. Mamm Genome 2011, 22:703-713.
66. Mann M., Pandey A. Use of mass spectrometry-derived data to annotate nucleotide and protein sequence databases. Trends Biochem Sci 2001, 26:54-61.
67. Koenig T., Menze B.H., Kirchner M., Monigatti F., Parker K.C., Patterson T., Steen J.J., Hamprecht F.A., Steen H. Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics. J Proteome Res 2008, 7:3708-3717.
68. Gonzalez-Vogel A., Eyzaguirre J., Oleas G., Callegari E., Navarrete M. Proteomic analysis in non-denaturing condition of the secretome reveals the presence of multienzyme complexes in Penicillium purpurogenum. Appl Microbiol Biotechnol 2011, 89:145-155.
69. Toyoda A., Iio W., Mitsumori M., Minato H. Isolation and identification of cellulose-binding proteins from sheep rumen contents. Appl Environ Microbiol 2009, 75:1667-1673.
70. Zaia J. Mass spectrometry and the emerging field of glycomics. Chem Biol 2008, 15:881-892.
71. Sylvestersen K.B., Young C., Nielsen M.L. Advances in characterizing ubiquitylation sites by mass spectrometry. Curr Opin Chem Biol 2013, 17:49-58.
72. Roux P.P., Thibault P. The coming of age of phosphoproteomics; from large data sets to inference of protein functions [Internet]. Mol Cell Proteomics 2013, 10.1074/mcp.R113.032862.
73. Dykstra A.B., Rodriguez M., Raman B., Cook K.D., Hettich R.L. Characterizing the range of extracellular protein post-translational modifications in a cellulose-degrading bacteria using a multiple proteolyic digestion/peptide fragmentation approach. Anal Chem 2013, 85:3144-3151.
74. Grigoriev I.V., Cullen D., Goodwin S.B., Hibbett D., Jeffries T.W., Kubicek C.P., Kuske C., Magnuson J.K., Martin F., Spatafora J.W., et al. Fueling the future with fungal genomics. Mycol Int J Fungal Biol 2011, 2:192-209.
75. Bowen B.P., Northen T.R. Dealing with the unknown: metabolomics and metabolite atlases. J Am Soc Mass Spectrom 2010, 21:1471-1476.
76. Palsson B. Two-dimensional annotation of genomes. Nat Biotechnol 2004, 22:1218-1219.
77. Segata N., Boernigen D., Tickle T.L., Morgan X.C., Garrett W.S., Huttenhower C. Computational meta'omics for microbial community studies [Internet]. Mol Syst Biol 2013, 9.
78. May P., Wienkoop S., Kempa S., Usadel B., Christian N., Rupprecht J., Weiss J., Recuenco-Munoz L., Ebenhoh O., Weckwerth W., et al. Metabolomics- and proteomics-assisted genome annotation and analysis of the draft metabolic network of Chlamydomonas reinhardtii. Genetics 2008, 179:157-166.
79. Turnbaugh P.J., Gordon J.I. An invitation to the marriage of metagenomics and metabolomics. Cell 2008, 134:708-713.
80. Muller E.E.L., Glaab E., May P., Vlassis N., Wilmes P. Condensing the omics fog of microbial communities. Trends Microbiol 2013, 21:325-333.
81. Amthauer H.A., Tsatsoulis C. Classifying genes to the correct gene ontology slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning. BMC Genomics 2010, 11:340.
82. Lee J.M., Sonnhammer E.L.L. Genomic gene clustering analysis of pathways in eukaryotes. Genome Res 2003, 13:875-882.
83. Dávila López M., Martínez Guerra J.J., Samuelsson T. Analysis of gene order conservation in eukaryotes identifies transcriptionally and functionally linked genes [Internet]. PLoS ONE 2010, 5.