Metagenomics: Retrospect and Prospects in High Throughput Age
Identifieur interne : 000695 ( Ncbi/Merge ); précédent : 000694; suivant : 000696Metagenomics: Retrospect and Prospects in High Throughput Age
Auteurs : Satish Kumar [Inde] ; Kishore Kumar Krishnani [Inde] ; Bharat Bhushan [Inde] ; Manoj Pandit Brahmane [Inde]Source :
- Biotechnology Research International [ 2090-3138 ] ; 2015.
Abstract
In recent years, metagenomics has emerged as a powerful tool for mining of hidden microbial treasure in a culture independent manner. In the last two decades, metagenomics has been applied extensively to exploit concealed potential of microbial communities from almost all sorts of habitats. A brief historic progress made over the period is discussed in terms of origin of metagenomics to its current state and also the discovery of novel biological functions of commercial importance from metagenomes of diverse habitats. The present review also highlights the paradigm shift of metagenomics from basic study of community composition to insight into the microbial community dynamics for harnessing the full potential of uncultured microbes with more emphasis on the implication of breakthrough developments, namely, Next Generation Sequencing, advanced bioinformatics tools, and systems biology.
Url:
DOI: 10.1155/2015/121735
PubMed: 26664751
PubMed Central: 4664791
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Age</title><author><name sortKey="Kumar, Satish" sort="Kumar, Satish" uniqKey="Kumar S" first="Satish" last="Kumar">Satish Kumar</name><affiliation wicri:level="1"><nlm:aff id="I1">ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115</wicri:regionArea><wicri:noRegion>Maharashtra 413115</wicri:noRegion></affiliation></author><author><name sortKey="Krishnani, Kishore Kumar" sort="Krishnani, Kishore Kumar" uniqKey="Krishnani K" first="Kishore Kumar" last="Krishnani">Kishore Kumar Krishnani</name><affiliation wicri:level="1"><nlm:aff id="I1">ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115</wicri:regionArea><wicri:noRegion>Maharashtra 413115</wicri:noRegion></affiliation></author><author><name sortKey="Bhushan, Bharat" sort="Bhushan, Bharat" uniqKey="Bhushan B" first="Bharat" last="Bhushan">Bharat Bhushan</name><affiliation wicri:level="1"><nlm:aff id="I2">ICAR-Central Institute of Post-Harvest Engineering and Technology, Abohar Station, Punjab 152116, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>ICAR-Central Institute of Post-Harvest Engineering and Technology, Abohar Station, Punjab 152116</wicri:regionArea><wicri:noRegion>Punjab 152116</wicri:noRegion></affiliation></author><author><name sortKey="Brahmane, Manoj Pandit" sort="Brahmane, Manoj Pandit" uniqKey="Brahmane M" first="Manoj Pandit" last="Brahmane">Manoj Pandit Brahmane</name><affiliation wicri:level="1"><nlm:aff id="I1">ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115</wicri:regionArea><wicri:noRegion>Maharashtra 413115</wicri:noRegion></affiliation></author></analytic><series><title level="j">Biotechnology Research International</title><idno type="ISSN">2090-3138</idno><idno type="eISSN">2090-3146</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>In recent years, metagenomics has emerged as a powerful tool for mining of hidden microbial treasure in a culture independent manner. In the last two decades, metagenomics has been applied extensively to exploit concealed potential of microbial communities from almost all sorts of habitats. A brief historic progress made over the period is discussed in terms of origin of metagenomics to its current state and also the discovery of novel biological functions of commercial importance from metagenomes of diverse habitats. The present review also highlights the paradigm shift of metagenomics from basic study of community composition to insight into the microbial community dynamics for harnessing the full potential of uncultured microbes with more emphasis on the implication of breakthrough developments, namely, Next Generation Sequencing, advanced bioinformatics tools, and systems biology.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Kunin, V" uniqKey="Kunin V">V. Kunin</name></author><author><name sortKey="Copeland, A" uniqKey="Copeland A">A. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Biotechnol Res Int</journal-id><journal-id journal-id-type="iso-abbrev">Biotechnol Res Int</journal-id><journal-id journal-id-type="publisher-id">BTRI</journal-id><journal-title-group><journal-title>Biotechnology Research International</journal-title></journal-title-group><issn pub-type="ppub">2090-3138</issn><issn pub-type="epub">2090-3146</issn><publisher><publisher-name>Hindawi Publishing Corporation</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26664751</article-id><article-id pub-id-type="pmc">4664791</article-id><article-id pub-id-type="doi">10.1155/2015/121735</article-id><article-categories><subj-group subj-group-type="heading"><subject>Review Article</subject></subj-group></article-categories><title-group><article-title>Metagenomics: Retrospect and Prospects in High Throughput Age</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kumar</surname><given-names>Satish</given-names></name><xref ref-type="aff" rid="I1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Krishnani</surname><given-names>Kishore Kumar</given-names></name><xref ref-type="aff" rid="I1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Bhushan</surname><given-names>Bharat</given-names></name><xref ref-type="aff" rid="I2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Brahmane</surname><given-names>Manoj Pandit</given-names></name><xref ref-type="aff" rid="I1"><sup>1</sup></xref></contrib></contrib-group><aff id="I1"><sup>1</sup>ICAR-National Institute of Abiotic Stress Management, Baramati, Pune, Maharashtra 413115, India</aff><aff id="I2"><sup>2</sup>ICAR-Central Institute of Post-Harvest Engineering and Technology, Abohar Station, Punjab 152116, India</aff><author-notes><corresp id="cor1">*Bharat Bhushan: <email>buddingbiochemist@gmail.com</email></corresp><fn fn-type="other"><p>Academic Editor: Manuel Canovas</p></fn></author-notes><pub-date pub-type="ppub"><year>2015</year></pub-date><pub-date pub-type="epub"><day>17</day><month>11</month><year>2015</year></pub-date><volume>2015</volume><elocation-id>121735</elocation-id><history><date date-type="received"><day>13</day><month>7</month><year>2015</year></date><date date-type="accepted"><day>26</day><month>10</month><year>2015</year></date></history><permissions><copyright-statement>Copyright © 2015 Satish Kumar et al.</copyright-statement><copyright-year>2015</copyright-year><license license-type="open-access"><license-p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><p>In recent years, metagenomics has emerged as a powerful tool for mining of hidden microbial treasure in a culture independent manner. In the last two decades, metagenomics has been applied extensively to exploit concealed potential of microbial communities from almost all sorts of habitats. A brief historic progress made over the period is discussed in terms of origin of metagenomics to its current state and also the discovery of novel biological functions of commercial importance from metagenomes of diverse habitats. The present review also highlights the paradigm shift of metagenomics from basic study of community composition to insight into the microbial community dynamics for harnessing the full potential of uncultured microbes with more emphasis on the implication of breakthrough developments, namely, Next Generation Sequencing, advanced bioinformatics tools, and systems biology.</p></abstract></article-meta></front><floats-group><table-wrap id="tab1" orientation="portrait" position="float"><label>Table 1</label><caption><p>Biological functions derived from the metagenomes from diverse habitats.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Type of activity exhibited by the metagenomic clone</th><th align="center" rowspan="1" colspan="1">Library type</th><th align="left" rowspan="1" colspan="1">Number of clones screened/size of DNA used for library construction</th><th align="left" rowspan="1" colspan="1">Sampling site</th><th align="left" rowspan="1" colspan="1">Screening method</th><th align="center" rowspan="1" colspan="1">Reference</th></tr></thead><tbody><tr><td align="left" rowspan="3" colspan="1">Lipase</td><td align="center" rowspan="1" colspan="1">Plasmid and fosmid</td><td align="left" rowspan="1" colspan="1">29.3 Gb of cloned soil DNA</td><td align="left" rowspan="1" colspan="1">German forest soil (horizon A)</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B50" ref-type="bibr">50</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">200,000 clones</td><td align="left" rowspan="1" colspan="1">Qiongdongnan basin, South China Sea (water depth 778.5 m)</td><td align="left" rowspan="1" colspan="1">Phenotypic screening<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B51" ref-type="bibr">51</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">15,000 clones</td><td align="left" rowspan="1" colspan="1">Peat-swamp forest soil from Narathiwat Province, Thailand</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B52" ref-type="bibr">52</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="3" colspan="1">Esterase</td><td align="center" rowspan="1" colspan="1">Plasmid</td><td align="left" rowspan="1" colspan="1">20,000 clones</td><td align="left" rowspan="1" colspan="1">High Andean forest soil</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B53" ref-type="bibr">53</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">20000</td><td align="left" rowspan="1" colspan="1">Deep-sea sediment</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B54" ref-type="bibr">54</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">142,900</td><td align="left" rowspan="1" colspan="1">Red pepper plant rhizosphere and strawberry plant rhizosphere</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(tributyrin hydrolysis)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B55" ref-type="bibr">55</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="2" colspan="1">Protease</td><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">17000</td><td align="left" rowspan="1" colspan="1">Surface sand from the Gobi and Death Valley deserts</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(skimmed milk)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B56" ref-type="bibr">74</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Plasmid</td><td align="left" rowspan="1" colspan="1">70,000</td><td align="left" rowspan="1" colspan="1">Goat skin surface</td><td align="left" rowspan="1" colspan="1">Phenotypic detection (skimmed milk)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B57" ref-type="bibr">75</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="2" colspan="1">Laccase</td><td align="center" rowspan="1" colspan="1">Plasmid</td><td align="left" rowspan="1" colspan="1">8000</td><td align="left" rowspan="1" colspan="1">Mangrove soil </td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(hydrolysis of guaiacol)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B58" ref-type="bibr">76</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Phagemid</td><td align="left" rowspan="1" colspan="1">Not mentioned</td><td align="left" rowspan="1" colspan="1">Bovine rumen microflora</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(oxidation of syringaldazine)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B59" ref-type="bibr">77</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Agarase</td><td align="center" rowspan="1" colspan="1">Cosmids</td><td align="left" rowspan="1" colspan="1">1,532</td><td align="left" rowspan="1" colspan="1">Soil from uncultivated field (Germany)</td><td align="left" rowspan="1" colspan="1">Phenotypical detection<break></break>(hydrolysis of low melting point agarose)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B60" ref-type="bibr">78</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Amidase</td><td align="center" rowspan="1" colspan="1">Plasmids</td><td align="left" rowspan="1" colspan="1">193,000</td><td align="left" rowspan="1" colspan="1">Soil and enrichment cultures from marine sediment, goose pond, lakeshore, and an agricultural field (Netherlands)</td><td align="left" rowspan="1" colspan="1">Heterologous complementation</td><td align="center" rowspan="1" colspan="1">[<xref rid="B61" ref-type="bibr">79</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Alcohol oxidoreductase</td><td align="center" rowspan="1" colspan="1">Plasmids</td><td align="left" rowspan="1" colspan="1">900,000 and 400,000</td><td align="left" rowspan="1" colspan="1">Soil and enrichment cultures from a sugar beet field (Germany),<break></break>river sediment (Germany),<break></break>sediments from Solar Lake (Egypt), and sediment from the Gulf of Eilat (Israel)</td><td align="left" rowspan="1" colspan="1">Phenotypic detection<break></break>(NAD(P)H-dependent reduction of carbonyls or by measuring the NAD(P)-dependent oxidation of alcohols) </td><td align="center" rowspan="1" colspan="1">[<xref rid="B62" ref-type="bibr">80</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="3" colspan="1">Antibiotics and bioactive compounds with anti-infective properties</td><td align="center" rowspan="1" colspan="1">Fosmid</td><td align="left" rowspan="1" colspan="1">80,500 clones from Yuseong and 33,200 clones from Jindong Valley forest soil</td><td align="left" rowspan="1" colspan="1">Forest soil from Jindong Valley</td><td align="left" rowspan="1" colspan="1">Phenotypic detection</td><td align="center" rowspan="1" colspan="1">[<xref rid="B63" ref-type="bibr">81</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Cosmids</td><td align="left" rowspan="1" colspan="1">Not mentioned</td><td align="left" rowspan="1" colspan="1">Bromeliad tank water (Costa Rica)</td><td align="left" rowspan="1" colspan="1">Phenotypical detection</td><td align="center" rowspan="1" colspan="1">[<xref rid="B64" ref-type="bibr">82</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">BAC</td><td align="left" rowspan="1" colspan="1">24,546</td><td align="left" rowspan="1" colspan="1">Soil</td><td align="left" rowspan="1" colspan="1">Phenotypic detection</td><td align="center" rowspan="1" colspan="1">[<xref rid="B65" ref-type="bibr">83</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">DNA polymerase 1</td><td align="center" rowspan="1" colspan="1">Plasmid</td><td align="left" rowspan="1" colspan="1">21,198 Sanger<break></break>sequence reads were analyzed</td><td align="left" rowspan="1" colspan="1">Octopus hot spring (93°C) in Yellowstone National Park</td><td align="left" rowspan="1" colspan="1">Activity-based screening<break></break>(primer extension assay)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B66" ref-type="bibr">84</xref>] </td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Na<sup>+</sup>/H<sup>+</sup> antiporters</td><td align="center" rowspan="1" colspan="1">Plasmid</td><td align="left" rowspan="1" colspan="1">8,000</td><td align="left" rowspan="1" colspan="1">Chaerhan Salt Lake, China</td><td align="left" rowspan="1" colspan="1">Heterologous complementation</td><td align="center" rowspan="1" colspan="1">[<xref rid="B67" ref-type="bibr">85</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Cellulases and xylanases</td><td align="center" rowspan="1" colspan="1">Fosmid library</td><td align="left" rowspan="1" colspan="1">Not mentioned</td><td align="left" rowspan="1" colspan="1">Hindgut of wood-feeding termite</td><td align="left" rowspan="1" colspan="1">AZCL-HE cellulose and AZCL-Xylan based assay</td><td align="center" rowspan="1" colspan="1">[<xref rid="B68" ref-type="bibr">86</xref>]</td></tr><tr><td align="center" colspan="6" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Phytases</td><td align="center" rowspan="1" colspan="1">Fosmid library</td><td align="left" rowspan="1" colspan="1">14,440</td><td align="left" rowspan="1" colspan="1">Soil</td><td align="left" rowspan="1" colspan="1">Functional screening<break></break>(by supplying only the phytate as the sole P source in the growth medium and selecting only clones with strong growth rate)</td><td align="center" rowspan="1" colspan="1">[<xref rid="B69" ref-type="bibr">87</xref>]</td></tr></tbody></table></table-wrap><table-wrap id="tab2" orientation="portrait" position="float"><label>Table 2</label><caption><p>Comparison of the unique features of NGS platforms widely applied in metagenomic research.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Sequencer</th><th align="left" rowspan="1" colspan="1">Roche/454 GS FLX Titanium</th><th align="left" rowspan="1" colspan="1">HiSeq 2000</th><th align="left" rowspan="1" colspan="1">SOLiDv4</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">NGS chemistry</td><td align="left" rowspan="1" colspan="1">Pyrosequencing</td><td align="left" rowspan="1" colspan="1">Sequencing by synthesis</td><td align="left" rowspan="1" colspan="1">Sequencing by ligation and exact call chemistry</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Library/template preparation</td><td align="left" rowspan="1" colspan="1">Emulsion PCR (emPCR)</td><td align="left" rowspan="1" colspan="1">Solid phase amplification</td><td align="left" rowspan="1" colspan="1">Emulsion PCR for fragment/mate-pair end sequencing</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Average read length</td><td align="left" rowspan="1" colspan="1">250–310 bp (highest among the NGS platforms) <break></break>Now approaching 400–500 (titanium) pyroreads</td><td align="left" rowspan="1" colspan="1">Initially it was 36, now approaching 150</td><td align="left" rowspan="1" colspan="1">35</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Run time (days)</td><td align="left" rowspan="1" colspan="1">24 hours (fastest of all)</td><td align="left" rowspan="1" colspan="1">4 days (fragment run)<break></break>9 days (mate-pair run)</td><td align="left" rowspan="1" colspan="1">7 days (fragment run)<break></break>14 days (mate-pair run)</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Output data/run</td><td align="left" rowspan="1" colspan="1">0.7 Gb</td><td align="left" rowspan="1" colspan="1">600 Gb<break></break>(over 1 Tb with Illumina's HiSeq X Ten)</td><td align="left" rowspan="1" colspan="1">120 Gb</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Advantage</td><td align="left" rowspan="1" colspan="1">Longer reads<break></break>Least time for one run<break></break>Amenable to multiplexing allowing many samples in single run</td><td align="left" rowspan="1" colspan="1">High throughput<break></break>Most widely used platform</td><td align="left" rowspan="1" colspan="1">Highest accuracy due to ECC (exact call chemistry) </td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Limitations</td><td align="left" rowspan="1" colspan="1">High error rate in homopolymer region<break></break>High cost of reagents<break></break>Low in throughput<break></break>Artificial replicate sequences during ePCR [<xref rid="B76" ref-type="bibr">88</xref>]</td><td align="left" rowspan="1" colspan="1">Short read length<break></break>Low multiplexing capability of samples<break></break>Single base error with GGC motifs<break></break>High error rate at tail end reads [<xref rid="B77" ref-type="bibr">89</xref>]</td><td align="left" rowspan="1" colspan="1">Long run time<break></break>Short read length</td></tr></tbody></table></table-wrap><table-wrap id="tab3" orientation="portrait" position="float"><label>Table 3</label><caption><p>A brief description of bioinformatic tools commonly employed for postsequencing analysis of metagenomic sequence data.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Postsequencing task</th><th align="center" rowspan="1" colspan="1">Bioinformatic tool</th><th align="left" rowspan="1" colspan="1">Brief description</th><th align="center" rowspan="1" colspan="1">URL</th><th align="center" rowspan="1" colspan="1">Reference</th></tr></thead><tbody><tr><td align="left" rowspan="4" colspan="1">Metagenomic assembly tool</td><td align="center" rowspan="1" colspan="1">MetaVelvet</td><td align="left" rowspan="1" colspan="1">Decomposes a de Bruijn graph into individual subgraphs on the basis of coverage (abundance) difference and graph connectivity.<break></break>Overcomes the limitation of a single-genome assembler to misidentify sequences from highly abundant species as repeats.<break></break>Results in higher N50 scores than any single-genome assembler.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://metavelvet.dna.bio.keio.ac.jp/">http://metavelvet.dna.bio.keio.ac.jp/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B79" ref-type="bibr">63</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Meta-IDBA</td><td align="left" rowspan="1" colspan="1">Implies partitioning the de Bruijn graph into isolated components of different species by grouping similar regions of similar subspecies and partitioning the graph into components based on the topological structure of the graph.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://i.cs.hku.hk/~alse/hkubrg/projects/metaidba/">http://i.cs.hku.hk/~alse/hkubrg/projects/metaidba/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B80" ref-type="bibr">64</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Genovo</td><td align="left" rowspan="1" colspan="1">Uses Bayesian approach and generative probabilistic model of read generation which works by discovering likely sequence reconstructions under the model.<break></break>Algorithm used is iterated conditional modes (ICM) algorithm, which maximizes local conditional probabilities sequentially.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://cs.stanford.edu/group/genovo/">http://cs.stanford.edu/group/genovo/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B87" ref-type="bibr">90</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Bambus 2</td><td align="left" rowspan="1" colspan="1">Uses mate-pair information during the assembly process which is not used by Meta-IDBA, MetaVelvet, and Genovo.<break></break>Algorithms operate on a contig graph generation followed by orientation, positioning, and simplification for proper scaffolding.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://amos.sf.net">http://amos.sf.net</ext-link>. </td><td align="center" rowspan="1" colspan="1">[<xref rid="B88" ref-type="bibr">91</xref>]</td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="4" colspan="1">Short read alignment and mapping to reference genome</td><td align="center" rowspan="1" colspan="1">Bowtie</td><td align="left" rowspan="1" colspan="1">An ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences which employs Burrows-Wheeler index based on the full-text minute-space (FM) index having low memory footprint (1.3 GB only)<break></break>also supports gapped, local, and paired-end alignment modes.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://bowtie-bio.sourceforge.net/index.shtml">http://bowtie-bio.sourceforge.net/index.shtml</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B89" ref-type="bibr">92</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">BWA</td><td align="left" rowspan="1" colspan="1">Employed for mapping low-divergent sequences against a large reference genome.<break></break>Has three-algorithm mode for different read length.<break></break>For Illumina sequence reads up to 100 bp size algorithm BWA-backtrack is used, while algorithms, BWA-SW and BWA-MEM, meant for longer sequences ranged from 70 bp to 1 Mbp.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://bio-bwa.sourceforge.net/">http://bio-bwa.sourceforge.net/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B90" ref-type="bibr">93</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">SOAP 3</td><td align="left" rowspan="1" colspan="1">Fast, accurate, and sensitive GPU-based short read aligner which delivers high speed and sensitivity simultaneously.<break></break>Found to take less than 30 seconds to align one million read pairs onto the human reference genome, much faster than BWA and Bowtie.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://www.cs.hku.hk/2bwt-tools/soap3-dp/">http://www.cs.hku.hk/2bwt-tools/soap3-dp/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B91" ref-type="bibr">94</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">mrsFAST</td><td align="left" rowspan="1" colspan="1">A cache oblivious mapper that is designed to map short reads to reference genome.<break></break>mrsFAST maps short reads with respect to user defined error threshold.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://sfu-compbio.github.io/mrsfast/">http://sfu-compbio.github.io/mrsfast/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B92" ref-type="bibr">95</xref>]</td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="3" colspan="1">Microbial diversity analysis</td><td align="center" rowspan="1" colspan="1">MLST</td><td align="left" rowspan="1" colspan="1">Exploits unambiguous nature and electronic portability of nucleotide sequence data for the characterization of microorganisms.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://www.mlst.net/">http://www.mlst.net/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B93" ref-type="bibr">96</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Axiome</td><td align="left" rowspan="1" colspan="1">Streamlines and manages analysis of small subunit (SSU) rRNA marker data in QIIME and mothur.<break></break>Has a companion graphical user interface (GUI) and is designed to be easily extended to facilitate customized research workflows.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://neufeld.github.com/axiometic">http://neufeld.github.com/axiometic</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B94" ref-type="bibr">97</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">PHACCS</td><td align="left" rowspan="1" colspan="1">Uses the contig spectrum from shotgun DNA based on modified Lander-Waterman algorithm sequence assemblies to predict structure of viral communities and make predictions about diversity.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://phaccs.sourceforge.net/">http://phaccs.sourceforge.net/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B95" ref-type="bibr">98</xref>]</td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Functional annotation</td><td align="center" rowspan="1" colspan="1">RAMMCAP</td><td align="left" rowspan="1" colspan="1">An ultrafast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://weizhong-lab.ucsd.edu/rammcap/cgi-bin/rammcap.cgi">http://weizhong-lab.ucsd.edu/rammcap/cgi-bin/rammcap.cgi</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B96" ref-type="bibr">99</xref>]</td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="3" colspan="1">Gene annotation/gene calling</td><td align="center" rowspan="1" colspan="1">FragGeneScan</td><td align="left" rowspan="1" colspan="1">Combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://omics.informatics.indiana.edu/FragGeneScan/">http://omics.informatics.indiana.edu/FragGeneScan/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B97" ref-type="bibr">100</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">MetaGeneMark</td><td align="left" rowspan="1" colspan="1">An ab initio gene prediction tool with updated heuristic models designed for metagenomic sequences.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://exon.gatech.edu/meta_gmhmmp.cgi">http://exon.gatech.edu/meta_gmhmmp.cgi</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B98" ref-type="bibr">101</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">MetaGeneAnnotator</td><td align="left" rowspan="1" colspan="1">Precisely predicts all kinds of prokaryotic genes from a single or a set of anonymous genomic sequences having a variety of lengths.<break></break>Integrates statistical models of prophage genes in addition to those of bacterial and archaeal genes and also uses a self-training model from input sequences for predictions.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://metagene.cb.k.u-tokyo.ac.jp/">http://metagene.cb.k.u-tokyo.ac.jp/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B99" ref-type="bibr">102</xref>]</td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="3" colspan="1">Binning</td><td align="center" rowspan="1" colspan="1">TETRA</td><td align="left" rowspan="1" colspan="1">Based on statistical analysis of tetranucleotide usage patterns in genomic fragments which automate the task of comparative tetranucleotide frequency analysis and outperform (G+C) content based analysis.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://www.megx.net/tetra/index.html">http://www.megx.net/tetra/index.html</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B100" ref-type="bibr">103</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">MetaCluster 5.0</td><td align="left" rowspan="1" colspan="1">A two-round binning method that separates reads of high-abundance species from those of low-abundance species in two different rounds and aims at identifying both low-abundance and high-abundance species in the presence of a large amount of noise due to many extremely low-abundance species.<break></break>Uses a filtering strategy to remove noise from the extremely low-abundance species.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://i.cs.hku.hk/~alse/MetaCluster/">http://i.cs.hku.hk/~alse/MetaCluster/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B101" ref-type="bibr">104</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">Phymm</td><td align="left" rowspan="1" colspan="1">Uses interpolated Markov models (IMMs) to characterize variable-length oligonucleotides typical of a phylogenetic grouping.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://www.cbcb.umd.edu/software/phymm/">http://www.cbcb.umd.edu/software/phymm/</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B102" ref-type="bibr">105</xref>] </td></tr><tr><td align="center" colspan="5" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="6" colspan="1">Automated platforms/servers for comparative and functional analysis of metagenomic sequence data </td><td align="center" rowspan="1" colspan="1">MG-RAST</td><td align="left" rowspan="1" colspan="1">MG-RAST (the Metagenomics RAST) server is an automated analysis platform which provides upload, quality control, automated annotation, and analysis for prokaryotic metagenomic shotgun samples.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://metagenomics.anl.gov">http://metagenomics.anl.gov</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B81" ref-type="bibr">65</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">MetAMOS</td><td align="left" rowspan="1" colspan="1">An open source and modular metagenomic assembly and analysis pipeline leveraging over 20 existing tools with some new tools integrated as well.<break></break>Entire pipeline is built around the unique features provided by the metagenomic scaffolder Bambus 2.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="https://github.com/treangen/MetAMOS">https://github.com/treangen/MetAMOS</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B82" ref-type="bibr">66</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">MEGAN 4</td><td align="left" rowspan="1" colspan="1">Released in 2011 for taxonomic analysis, comparative analysis, and functional analysis methods based on the SEED and KEGG (Kyoto Encyclopedia for Genes and Genomes)</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://www-ab.informatik.uni-tuebingen.de/software/megan">http://www-ab.informatik.uni-tuebingen.de/software/megan</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B83" ref-type="bibr">106</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">IMG/M</td><td align="left" rowspan="1" colspan="1">A data management and analysis system for microbial community genomes (metagenomes) hosted at the Department of Energy's (DOE) Joint Genome Institute (JGI).<break></break>IMG/M consists of metagenome data integrated with isolate microbial genomes from the Integrated Microbial Genomes (IMG) system.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://img.jgi.doe.gov/cgi-bin/m/main.cgi">http://img.jgi.doe.gov/cgi-bin/m/main.cgi</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B84" ref-type="bibr">67</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">CAMERA</td><td align="left" rowspan="1" colspan="1">Provides access to raw environmental sequence data, with associated metadata, precomputed annotation, and analyses.<break></break>Integrates tools for gene prediction and annotation, clustering, assembly sequence quality control, functional and comparative genomics applications, and many other downstream analysis tools.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://camera.calit2.net">http://camera.calit2.net</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B85" ref-type="bibr">68</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">GALAXY</td><td align="left" rowspan="1" colspan="1">A publicly available web service, with software system that provides support for analysis of genomic, comparative genomic, and functional genomic data through a framework that gives experimentalists simple interfaces to powerful tools while automatically managing the computational details.</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://galaxyproject.org">http://galaxyproject.org</ext-link></td><td align="center" rowspan="1" colspan="1">[<xref rid="B86" ref-type="bibr">69</xref>]</td></tr></tbody></table></table-wrap></floats-group></pmc><affiliations><list><country><li>Inde</li></country></list><tree><country name="Inde"><noRegion><name sortKey="Kumar, Satish" sort="Kumar, Satish" uniqKey="Kumar S" first="Satish" last="Kumar">Satish Kumar</name></noRegion><name sortKey="Bhushan, Bharat" sort="Bhushan, Bharat" uniqKey="Bhushan B" first="Bharat" last="Bhushan">Bharat Bhushan</name><name sortKey="Brahmane, Manoj Pandit" sort="Brahmane, Manoj Pandit" uniqKey="Brahmane M" first="Manoj Pandit" last="Brahmane">Manoj Pandit Brahmane</name><name sortKey="Krishnani, Kishore Kumar" sort="Krishnani, Kishore Kumar" uniqKey="Krishnani K" first="Kishore Kumar" last="Krishnani">Kishore Kumar Krishnani</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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