Metagenomics - Knowledge

1078:. Shotgun sequencing reveals genes present in environmental samples. Historically, clone libraries were used to facilitate this sequencing. However, with advances in high throughput sequencing technologies, the cloning step is no longer necessary and greater yields of sequencing data can be obtained without this labour-intensive bottleneck step. Shotgun metagenomics provides information both about which organisms are present and what metabolic processes are possible in the community. Because the collection of DNA from an environment is largely uncontrolled, the most abundant organisms in an environmental sample are most highly represented in the resulting sequence data. To achieve the high coverage needed to fully resolve the genomes of under-represented community members, large samples, often prohibitively so, are needed. On the other hand, the random nature of shotgun sequencing ensures that many of these organisms, which would otherwise go unnoticed using traditional culturing techniques, will be represented by at least some small sequence segments. 1493:-based comparative metagenomic analysis application called Community-Analyzer has been developed by Kuntal et al. which implements a correlation-based graph layout algorithm that not only facilitates a quick visualization of the differences in the analyzed microbial communities (in terms of their taxonomic composition), but also provides insights into the inherent inter-microbial interactions occurring therein. Notably, this layout algorithm also enables grouping of the metagenomes based on the probable inter-microbial interaction patterns rather than simply comparing abundance values of various taxonomic groups. In addition, the tool implements several interactive GUI-based functionalities that enable users to perform standard comparative analyses across microbiomes. 1980:

critically important for the health of the intestinal tract. There are two types of functions in these range clusters: housekeeping and those specific to the intestine. The housekeeping gene clusters are required in all bacteria and are often major players in the main metabolic pathways including central carbon metabolism and amino acid synthesis. The gut-specific functions include adhesion to host proteins and the harvesting of sugars from globoseries glycolipids. Patients with irritable bowel syndrome were shown to exhibit 25% fewer genes and lower bacterial diversity than individuals not suffering from irritable bowel syndrome indicating that changes in patients' gut biome diversity may be associated with this condition.

1111:; Ion Torrent PGM System and 454 pyrosequencing typically produces ~400 bp reads, Illumina MiSeq produces 400-700bp reads (depending on whether paired end options are used), and SOLiD produce 25–75 bp reads. Historically, these read lengths were significantly shorter than the typical Sanger sequencing read length of ~750 bp, however the Illumina technology is quickly coming close to this benchmark. However, this limitation is compensated for by the much larger number of sequence reads. In 2009, pyrosequenced metagenomes generate 200–500 megabases, and Illumina platforms generate around 20–50 gigabases, but these outputs have increased by orders of magnitude in recent years. 1009: 49: 1894: 377: 1175: 1438:

MEGAN run slowly to annotate large samples (e.g., several hours to process a small/medium size dataset/sample ). Thus, ultra-fast classifiers have recently emerged, thanks to more affordable powerful servers. These tools can perform the taxonomic annotation at extremely high speed, for example CLARK (according to CLARK's authors, it can classify accurately "32 million metagenomic short reads per minute"). At such a speed, a very large dataset/sample of a billion short reads can be processed in about 30 minutes.

218: 1881:

high-throughput bioinformatic analysis pipelines. The sequence-driven approach to screening is limited by the breadth and accuracy of gene functions present in public sequence databases. In practice, experiments make use of a combination of both functional and sequence-based approaches based upon the function of interest, the complexity of the sample to be screened, and other factors. An example of success using metagenomics as a biotechnology for drug discovery is illustrated with the

7818: 754: 332: 7846: 7806: 570: 1426:(MEta Genome ANalyzer). A first version of the program was used in 2005 to analyse the metagenomic context of DNA sequences obtained from a mammoth bone. Based on a BLAST comparison against a reference database, this tool performs both taxonomic and functional binning, by placing the reads onto the nodes of the NCBI taxonomy using a simple lowest common ancestor (LCA) algorithm or onto the nodes of the 1140: 7858: 1709:. Functional metagenomics strategies are being used to explore the interactions between plants and microbes through cultivation-independent study of these microbial communities. By allowing insights into the role of previously uncultivated or rare community members in nutrient cycling and the promotion of plant growth, metagenomic approaches can contribute to improved disease detection in 1262:. The use of reference genomes allows researchers to improve the assembly of the most abundant microbial species, but this approach is limited by the small subset of microbial phyla for which sequenced genomes are available. After an assembly is created, an additional challenge is "metagenomic deconvolution", or determining which sequences come from which species in the sample. 1991:(HMP), gut microbial communities were assayed using high-throughput DNA sequencing. HMP showed that, unlike individual microbial species, many metabolic processes were present among all body habitats with varying frequencies. Microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals were studied as part of the 869:, it did support early microbial morphology-based observations that diversity was far more complex than was known by culturing methods. Soon after that in 1995, Healy reported the metagenomic isolation of functional genes from "zoolibraries" constructed from a complex culture of environmental organisms grown in the laboratory on dried 1872:

approach is limited by availability of a suitable screen and the requirement that the desired trait be expressed in the host cell. Moreover, the low rate of discovery (less than one per 1,000 clones screened) and its labor-intensive nature further limit this approach. In contrast, sequence-driven analysis uses

1407:) a community resource for metagenome data set analysis. As of June 2012 over 14.8 terabases (14x10 bases) of DNA have been analyzed, with more than 10,000 public data sets freely available for comparison within MG-RAST. Over 8,000 users now have submitted a total of 50,000 metagenomes to MG-RAST. The 1901:

Metagenomics can provide valuable insights into the functional ecology of environmental communities. Metagenomic analysis of the bacterial consortia found in the defecations of Australian sea lions suggests that nutrient-rich sea lion faeces may be an important nutrient source for coastal ecosystems.

1632:

for eukarya), the only way to access the genetic diversity of the viral community from an environmental sample is through metagenomics. Viral metagenomes (also called viromes) should thus provide more and more information about viral diversity and evolution. For example, a metagenomic pipeline called

1542:

researchers can piece together a metabolic network that goes beyond species boundaries. Such studies require detailed knowledge about which versions of which proteins are coded by which species and even by which strains of which species. Therefore, community genomic information is another fundamental

1476:

Additionally, several studies have also utilized oligonucleotide usage patterns to identify the differences across diverse microbial communities. Examples of such methodologies include the dinucleotide relative abundance approach by Willner et al. and the HabiSign approach of Ghosh et al. This latter

1441:

With the increasing availability of samples containing ancient DNA and due to the uncertainty associated with the nature of those samples (ancient DNA damage), a fast tool capable of producing conservative similarity estimates has been made available. According to FALCON's authors, it can use relaxed

1437:

With the advent of fast and inexpensive sequencing instruments, the growth of databases of DNA sequences is now exponential (e.g., the NCBI GenBank database ). Faster and efficient tools are needed to keep pace with the high-throughput sequencing, because the BLAST-based approaches such as MG-RAST or

6992:

Abubucker, Sahar; Segata, Nicola; Goll, Johannes; Schubert, Alyxandria M.; Izard, Jacques; Cantarel, Brandi L.; Rodriguez-Mueller, Beltran; Zucker, Jeremy; Thiagarajan, Mathangi; Henrissat, Bernard; White, Owen; Kelley, Scott T.; Methé, Barbara; Schloss, Patrick D.; Gevers, Dirk; Mitreva, Makedonka;

2028:

shows promise as a sensitive and rapid method to diagnose infection by comparing genetic material found in a patient's sample to databases of all known microscopic human pathogens and thousands of other bacterial, viral, fungal, and parasitic organisms and databases on antimicrobial resistances gene

1983:

While these studies highlight some potentially valuable medical applications, only 31–48.8% of the reads could be aligned to 194 public human gut bacterial genomes and 7.6–21.2% to bacterial genomes available in GenBank which indicates that there is still far more research necessary to capture novel

1840:

Microbial communities produce a vast array of biologically active chemicals that are used in competition and communication. Many of the drugs in use today were originally uncovered in microbes; recent progress in mining the rich genetic resource of non-culturable microbes has led to the discovery of

1472:

as a whole rather than taxonomic groups, and shows that the functional complements are analogous under similar environmental conditions. Consequently, metadata on the environmental context of the metagenomic sample is especially important in comparative analyses, as it provides researchers with the

1871:

of metagenomic data: function-driven screening for an expressed trait, and sequence-driven screening for DNA sequences of interest. Function-driven analysis seeks to identify clones expressing a desired trait or useful activity, followed by biochemical characterization and sequence analysis. This

1385:

associated with metagenomic projects. Metadata includes detailed information about the three-dimensional (including depth, or height) geography and environmental features of the sample, physical data about the sample site, and the methodology of the sampling. This information is necessary both to

1225:

while metagenomic data is usually highly non-redundant. Furthermore, the increased use of second-generation sequencing technologies with short read lengths means that much of future metagenomic data will be error-prone. Taken in combination, these factors make the assembly of metagenomic sequence

1979:

The study demonstrated that two bacterial divisions, Bacteroidetes and Firmicutes, constitute over 90% of the known phylogenetic categories that dominate distal gut bacteria. Using the relative gene frequencies found within the gut these researchers identified 1,244 metagenomic clusters that are

1975:

Another medical study as part of the MetaHit (Metagenomics of the Human Intestinal Tract) project consisted of 124 individuals from Denmark and Spain consisting of healthy, overweight, and irritable bowel disease patients. The study attempted to categorize the depth and phylogenetic diversity of

1880:

to screen clones for the sequence of interest. In comparison to cloning-based approaches, using a sequence-only approach further reduces the amount of bench work required. The application of massively parallel sequencing also greatly increases the amount of sequence data generated, which require

1488:

A key goal in comparative metagenomics is to identify microbial group(s) which are responsible for conferring specific characteristics to a given environment. However, due to issues in the sequencing technologies artifacts need to be accounted for like in metagenomeSeq. Others have characterized

968:

Seas. Analysis of the metagenomic data collected during this journey revealed two groups of organisms, one composed of taxa adapted to environmental conditions of 'feast or famine', and a second composed of relatively fewer but more abundantly and widely distributed taxa primarily composed of

1681:

in which plants grow are inhabited by microbial communities, with one gram of soil containing around 10-10 microbial cells which comprise about one gigabase of sequence information. The microbial communities which inhabit soils are some of the most complex known to science, and remain poorly

1976:

gastrointestinal bacteria. Using Illumina GA sequence data and SOAPdenovo, a de Bruijn graph-based tool specifically designed for assembly short reads, they were able to generate 6.58 million contigs greater than 500 bp for a total contig length of 10.3 Gb and a N50 length of 2.2 kb.

500:

Because of its ability to reveal the previously hidden diversity of microscopic life, metagenomics offers a powerful way of understanding the microbial world that might revolutionize understanding of biology. As the price of DNA sequencing continues to fall, metagenomics now allows

940:(GOS), circumnavigating the globe and collecting metagenomic samples throughout the journey. All of these samples were sequenced using shotgun sequencing, in hopes that new genomes (and therefore new organisms) would be identified. The pilot project, conducted in the 1450:

Comparative analyses between metagenomes can provide additional insight into the function of complex microbial communities and their role in host health. Pairwise or multiple comparisons between metagenomes can be made at the level of sequence composition (comparing

6869:

Qin, Junjie; Li, Ruiqiang; Raes, Jeroen; Arumugam, Manimozhiyan; Burgdorf, Kristoffer Solvsten; Manichanh, Chaysavanh; Nielsen, Trine; Pons, Nicolas; Levenez, Florence; Yamada, Takuji; Mende, Daniel R.; Li, Junhua; Xu, Junming; Li, Shaochuan; Li, Dongfang (2010).

1477:

study also indicated that differences in tetranucleotide usage patterns can be used to identify genes (or metagenomic reads) originating from specific habitats. Additionally some methods as TriageTools or Compareads detect similar reads between two read sets. The

1459:

and other phylogenetic marker genes, or—in the case of low-diversity communities—by genome reconstruction from the metagenomic dataset. Functional comparisons between metagenomes may be made by comparing sequences against reference databases such as

1369:, use read coverage landscape of individual reference genomes to minimize false-positive hits and get reliable relative abundances. In composition based binning, methods use intrinsic features of the sequence, such as oligonucleotide frequencies or 1194:

gene catalog identified 3.3 million genes assembled from 567.7 gigabases of sequence data. Collecting, curating, and extracting useful biological information from datasets of this size represent significant computational challenges for researchers.

852:

to explore the diversity of ribosomal RNA sequences. The insights gained from these breakthrough studies led Pace to propose the idea of cloning DNA directly from environmental samples as early as 1985. This led to the first report of isolating and

1086:

An advantage to high throughput sequencing is that this technique does not require cloning the DNA before sequencing, removing one of the main biases and bottlenecks in environmental sampling. The first metagenomic studies conducted using

1936:

and for cleaning up contaminated environments. Increased understanding of how microbial communities cope with pollutants improves assessments of the potential of contaminated sites to recover from pollution and increases the chances of

1905:

DNA sequencing can also be used more broadly to identify species present in a body of water, debris filtered from the air, sample of dirt, or animal's faeces, and even detect diet items from blood meals. This can establish the range of

1960:, but their composition and the mechanism by which they do so remains mysterious. Metagenomic sequencing is being used to characterize the microbial communities from 15–18 body sites from at least 250 individuals. This is part of the 2011:

In animals, metagenomics can be used to profile their gut microbiomes and enable detection of antibiotic-resistant bacteria. This can have implications in monitoring the spread of diseases from wildlife to farmed animals and humans.

1394:

Several tools have been developed to integrate metadata and sequence data, allowing downstream comparative analyses of different datasets using a number of ecological indices. In 2007, Folker Meyer and Robert Edwards and a team at

2542:

Healy FG, Ray RM, Aldrich HC, Wilkie AC, Ingram LO, Shanmugam KT (1995). "Direct isolation of functional genes encoding cellulases from the microbial consortia in a thermophilic, anaerobic digester maintained on lignocellulose".

1230:

that make assembly especially difficult because of the difference in the relative abundance of species present in the sample. Misassemblies can also involve the combination of sequences from more than one species into chimeric

1390:

and to enable downstream analysis. Because of its importance, metadata and collaborative data review and curation require standardized data formats located in specialized databases, such as the Genomes OnLine Database (GOLD).

533:, and Sean F. Brady, and first appeared in publication in 1998. The term metagenome referenced the idea that a collection of genes sequenced from the environment could be analyzed in a way analogous to the study of a single 1314:

prediction is that it enables the detection of coding regions that lack homologs in the sequence databases; however, it is most accurate when there are large regions of contiguous genomic DNA available for comparison.

1809:. Furthermore, knowledge of how these microbial communities function is required to control them, and metagenomics is a key tool in their understanding. Metagenomic approaches allow comparative analyses between 1999:

degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. The HMP has brought to light the utility of metagenomics in diagnostics and

1571:

Metagenomics allows researchers to access the functional and metabolic diversity of microbial communities, but it cannot show which of these processes are active. The extraction and analysis of metagenomic

1902:

This is because the bacteria that are expelled simultaneously with the defecations are adept at breaking down the nutrients in the faeces into a bioavailable form that can be taken up into the food chain.

877:

continued in the field and has published work that has largely laid the groundwork for environmental phylogenies based on signature 16S sequences, beginning with his group's construction of libraries from

7741: 5913: 1118:(Hi-C), which measures the proximity of any two DNA sequences within the same cell, to guide microbial genome assembly. Long read sequencing technologies, including PacBio RSII and PacBio Sequel by 3073:

Béjà O, Suzuki MT, Koonin EV, Aravind L, Hadd A, Nguyen LP, et al. (October 2000). "Construction and analysis of bacterial artificial chromosome libraries from a marine microbial assemblage".

2697:

Tyson GW, Chapman J, Hugenholtz P, Allen EE, Ram RJ, Richardson PM, et al. (March 2004). "Community structure and metabolism through reconstruction of microbial genomes from the environment".

1062:, refinements of DNA amplification, and the proliferation of computational power have greatly aided the analysis of DNA sequences recovered from environmental samples, allowing the adaptation of 1411:(IMG/M) system also provides a collection of tools for functional analysis of microbial communities based on their metagenome sequence, based upon reference isolate genomes included from the 6346: 1203:

The first step of metagenomic data analysis requires the execution of certain pre-filtering steps, including the removal of redundant, low-quality sequences and sequences of probable

4404:

Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger SA, Kultima JR, et al. (December 2013). "Metagenomic species profiling using universal phylogenetic marker genes".

1182:

The data generated by metagenomics experiments are both enormous and inherently noisy, containing fragmented data representing as many as 10,000 species. The sequencing of the cow

6743:"A two-step metagenomics approach for the identification and mitochondrial DNA contig assembly of vertebrate prey from the blood meals of common vampire bats (Desmodus rotundus)" 2020:

Differentiating between infectious and non-infectious illness, and identifying the underlying etiology of infection, can be challenging. For example, more than half of cases of

1178:

Schematic representation of the main steps necessary for the analysis of whole metagenome shotgun sequencing-derived data. The software related to each step is shown in italics.

1995:

project. The metagenomic analysis revealed variations in niche specific abundance among 168 functional modules and 196 metabolic pathways within the microbiome. These included

1468:, and tabulating the abundance by category and evaluating any differences for statistical significance. This gene-centric approach emphasizes the functional complement of the 778: 1207:

origin (especially in metagenomes of human origin). The methods available for the removal of contaminating eukaryotic genomic DNA sequences include Eu-Detect and DeConseq.

837:

species in a sample. Much of the interest in metagenomics comes from these discoveries that showed that the vast majority of microorganisms had previously gone unnoticed.

1302:, uses intrinsic features of the sequence to predict coding regions based upon gene training sets from related organisms. This is the approach taken by programs such as 3470:

Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, et al. (January 2011). "Metagenomic discovery of biomass-degrading genes and genomes from cow rumen".

4963:

Pratas D, Pinho AJ, Silva RM, Rodrigues JM, Hosseini M, Caetano T, Ferreira PJ (February 2018). "FALCON: a method to infer metagenomic composition of ancient DNA".

3846:

Mohammed MH, Chadaram S, Komanduri D, Ghosh TS, Mande SS (September 2011). "Eu-Detect: an algorithm for detecting eukaryotic sequences in metagenomic data sets".

2920:

Poinar HN, Schwarz C, Qi J, Shapiro B, Macphee RD, Buigues B, et al. (January 2006). "Metagenomics to paleogenomics: large-scale sequencing of mammoth DNA".

5921: 2802:

Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D, Eisen JA, et al. (April 2004). "Environmental genome shotgun sequencing of the Sargasso Sea".

865:

false positives and supported the existence of a complex community of unexplored species. Although this methodology was limited to exploring highly conserved,

6741:

Chua, Physilia Y. S.; Carøe, Christian; Crampton-Platt, Alex; Reyes-Avila, Claudia S.; Jones, Gareth; Streicker, Daniel G.; Bohmann, Kristine (4 July 2022).

1357:

are methods based on unique clade-specific markers for estimating organismal relative abundances with improved computational performances. Other tools, like

5481:

Leininger S, Urich T, Schloter M, Schwark L, Qi J, Nicol GW, et al. (August 2006). "Archaea predominate among ammonia-oxidizing prokaryotes in soils".

1455:

or genome size), taxonomic diversity, or functional complement. Comparisons of population structure and phylogenetic diversity can be made on the basis of

2041:(blood-feeding) insects such as mosquitoes and ticks. Metagenomics is routinely used by public health officials and organisations for the surveillance of 428:) to deduce the individual genomes or parts of genomes that constitute the original environmental sample. This information can then be used to study the 1066:

to metagenomic samples (known also as whole metagenome shotgun or WMGS sequencing). The approach, used to sequence many cultured microorganisms and the

6509:"Culture-independent discovery of the malacidins as calcium-dependent antibiotics with activity against multidrug-resistant Gram-positive pathogens" 897:(see below) to show that 200 liters of seawater contains over 5000 different viruses. Subsequent studies showed that there are more than a thousand 829:, indicating that there are numerous non-isolated organisms. These surveys of ribosomal RNA genes taken directly from the environment revealed that 545:) defined metagenomics as "the application of modern genomics technique without the need for isolation and lab cultivation of individual species". 6377: 1341:

are used to rapidly search for phylogenetic markers or otherwise similar sequences in existing public databases. This approach is implemented in

2457:

Pace NR, Stahl DA, Lane DJ, Olsen GJ (1986). "The Analysis of Natural Microbial Populations by Ribosomal RNA Sequences". In Marshall KC (ed.).

2588:"Characterization of uncultivated prokaryotes: isolation and analysis of a 40-kilobase-pair genome fragment from a planktonic marine archaeon" 1365:

is possible to profile species without a reference genome, improving the estimation of microbial community diversity. Recent methods, such as

5997: 1624:

Metagenomic sequencing is particularly useful in the study of viral communities. As viruses lack a shared universal phylogenetic marker (as

1897:

Metagenomics allows the study of microbial communities like those present in this stream receiving acid drainage from surface coal mining.

1610:

to measure whole-genome expression and quantification of a microbial community, first employed in analysis of ammonia oxidation in soils.

7736: 1649:

Metagenomics has the potential to advance knowledge in a wide variety of fields. It can also be applied to solve practical challenges in

806:. However, early metagenomic studies revealed that there are probably large groups of microorganisms in many environments that cannot be 363: 6607:"High nutrient transport and cycling potential revealed in the microbial metagenome of Australian sea lion (Neophoca cinerea) faeces" 5837:

Kerepesi C, Grolmusz V (June 2017). "The "Giant Virus Finder" discovers an abundance of giant viruses in the Antarctic dry valleys".

1797:

with higher productivity and lower cost. Metagenomic approaches to the analysis of complex microbial communities allow the targeted

1280:

use two approaches in the annotation of coding regions in the assembled contigs. The first approach is to identify genes based upon

1968:, to understand the changes in the human microbiome that can be correlated with human health, and to develop new technological and 6690:

Chua, Physilia Y. S.; Crampton-Platt, Alex; Lammers, Youri; Alsos, Inger G.; Boessenkool, Sanne; Bohmann, Kristine (25 May 2021).

785: 621: 1381:

The massive amount of exponentially growing sequence data is a daunting challenge that is complicated by the complexity of the

857:

bulk DNA from an environmental sample, published by Pace and colleagues in 1991 while Pace was in the Department of Biology at

909:. Essentially all of the viruses in these studies were new species. In 2004, Gene Tyson, Jill Banfield, and colleagues at the 7778: 6850: 6799: 6326: 6040: 3665: 2474: 2230: 652: 6058:"Pivotal roles of phyllosphere microorganisms at the interface between plant functioning and atmospheric trace gas dynamics" 5995: 3645: 2037:

Metagenomics has been an invaluable tool to help characterise the diversity and ecology of pathogens that are vectored by

1790: 1221:

DNA sequence data from genomic and metagenomic projects are essentially the same, but genomic sequence data offers higher

1151:

about quality assessment: on assembly (N50, MetaQUAST), on genome (universal single-copy marker genes – CheckM and BUSCO).

7893: 6664: 1877: 1408: 4660:"The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes" 1088: 7463: 6995:"PLOS Computational Biology: Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome" 910: 739: 542: 3176:

Rodrigue S, Materna AC, Timberlake SC, Blackburn MC, Malmstrom RR, Alm EJ, Chisholm SW (July 2010). Gilbert JA (ed.).

7274:"Uncovering the Worldwide Diversity and Evolution of the Virome of the Mosquitoes Aedes aegypti and Aedes albopictus" 6217:

Suen G, Scott JJ, Aylward FO, Adams SM, Tringe SG, Pinto-Tomás AA, et al. (September 2010). Sonnenburg J (ed.).

5891: 1333:

provide the "who". In order to connect community composition and function in metagenomes, sequences must be binned.

7898: 6160:"Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing" 1337:

is the process of associating a particular sequence with an organism. In similarity-based binning, methods such as

937: 734: 729: 6816: 4611:"The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata" 3691:"Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies" 513:

directed sequencing to get largely unbiased samples of all genes from all the members of the sampled communities.

7810: 7756: 5532:

Paez-Espino D, Eloe-Fadrosh EA, Pavlopoulos GA, Thomas AD, Huntemann M, Mikhailova N, et al. (August 2016).

5152:"HabiSign: a novel approach for comparison of metagenomes and rapid identification of habitat-specific sequences" 2025: 1115: 1039: 953: 5638:"IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes" 6558:"Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic data" 5299:"Community-analyzer: a platform for visualizing and comparing microbial community structure across microbiomes" 356: 6031:

Charles T (2010). "The Potential for Investigation of Plant-microbe Interactions Using Metagenomics Methods".

236: 7784: 5935:

Vogel TM, Simonet P, Jansson JK, Hirsch PR, Tiedje JM, Van Elsas JD, Bailey MJ, Nalin R, Philippot L (2009).

3418:"Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses" 2299:"Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products" 6790:

George I, Stenuit B, Agathos SN (2010). "Application of Metagenomics to Bioremediation". In Marco D (ed.).

6158:

Jaenicke S, Ander C, Bekel T, Bisdorf R, Dröge M, Gartemann KH, et al. (January 2011). Aziz RK (ed.).

1607: 1560: 1123: 1096: 6458:"Isolation of xylose isomerases by sequence- and function-based screening from a soil metagenomic library" 4914:"CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers" 2248:"Environmental shotgun sequencing: its potential and challenges for studying the hidden world of microbes" 1547:

and proteomics) in the quest to determine how metabolites are transferred and transformed by a community.

981: 493:

gene) to produce a profile of diversity in a natural sample. Such work revealed that the vast majority of

7700: 7428: 6841:

Nelson KE and White BA (2010). "Metagenomics and Its Applications to the Study of the Human Microbiome".

1841:

new genes, enzymes, and natural products. The application of metagenomics has allowed the development of

1514:), during which the waste products of some organisms are metabolites for others. In one such system, the 1396: 1373:. Once sequences are binned, it is possible to carry out comparative analysis of diversity and richness. 723: 1258:, have been optimized for the shorter reads produced by second-generation sequencing through the use of 921:

system. This effort resulted in the complete, or nearly complete, genomes for a handful of bacteria and

7836: 4008:"MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads" 2971:

Edwards RA, Rodriguez-Brito B, Wegley L, Haynes M, Breitbart M, Peterson DM, et al. (March 2006).

1043: 997: 709: 125: 17: 5686: 1126:, is another choice to get long shotgun sequencing reads that should make ease in assembling process. 7790: 5996:

Committee on Metagenomics: Challenges and Functional Applications, National Research Council (2007).

3646:

Committee on Metagenomics: Challenges and Functional Applications, National Research Council (2007).

1762:. This process is dependent upon microbial consortia (association) that transform the cellulose into 1254:

but nevertheless produce good results when assembling metagenomic data sets. Other programs, such as

862: 849: 693: 510: 349: 3689:

Oulas A, Pavloudi C, Polymenakou P, Pavlopoulos GA, Papanikolaou N, Kotoulas G, et al. (2015).

2824: 1598: 7746: 7591: 7523: 4812:

Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW (January 2013).

3738:

Mende DR, Waller AS, Sunagawa S, Järvelin AI, Chan MM, Arumugam M, et al. (23 February 2012).

1988: 1961: 143: 5199:"TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data" 2024:

remain undiagnosed, despite extensive testing using state-of-the-art clinical laboratory methods.

7883: 7731: 7603: 6006: 3891:"Fast identification and removal of sequence contamination from genomic and metagenomic datasets" 2001: 1227: 1008: 830: 807: 598: 486: 2170:"Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity" 1721:

practices which improve crop health by harnessing the relationship between microbes and plants.

7772: 7688: 7491: 7456: 5338:

Werner JJ, Knights D, Garcia ML, Scalfone NB, Smith S, Yarasheski K, et al. (March 2011).

4106:"Species-level deconvolution of metagenome assemblies with Hi-C-based contact probability maps" 2819: 2635:

Breitbart M, Salamon P, Andresen B, Mahaffy JM, Segall AM, Mead D, et al. (October 2002).

2222: 2054: 1334: 914: 771: 758: 7423: 4709:

Markowitz VM, Chen IM, Chu K, Szeto E, Palaniappan K, Grechkin Y, et al. (January 2012).

3310:

Stewart RD, Auffret MD, Warr A, Wiser AH, Press MO, Langford KW, et al. (February 2018).

2004:. Thus metagenomics is a powerful tool to address many of the pressing issues in the field of 505:

to be investigated at a much greater scale and detail than before. Recent studies use either "

7878: 7751: 7705: 5587:

Paez-Espino D, Chen IA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. (January 2017).

4450:

Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh HJ, Cuenca M, et al. (March 2019).

2005: 1953: 1400: 1338: 1289: 977: 316: 296: 261: 173: 168: 5636:

Paez-Espino D, Roux S, Chen IA, Palaniappan K, Ratner A, Chu K, et al. (January 2019).

1422:

One of the first standalone tools for analysing high-throughput metagenome shotgun data was

7511: 7496: 7336: 7179: 7006: 6948: 6883: 6618: 6171: 5545: 5490: 5351: 5114: 5057: 4964: 4609:

Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, et al. (January 2012).

4463: 4267: 3902: 3751: 3534: 3479: 3323: 3189: 3082: 2929: 2876: 2863:

Yooseph S, Nealson KH, Rusch DB, McCrow JP, Dupont CL, Kim M, et al. (November 2010).

2811: 2706: 2648: 2411: 2352: 2119: 1825: 1810: 1767: 1104: 1067: 933: 608: 603: 6507:

Hover BM, Kim SH, Katz M, Charlop-Powers Z, Owen JG, Ternei MA, et al. (April 2018).

4658:

Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, et al. (September 2008).

8: 7721: 7695: 7553: 7540: 7501: 5687:"Nontargeted virus sequence discovery pipeline and virus clustering for metagenomic data" 5340:"Bacterial community structures are unique and resilient in full-scale bioenergy systems" 4761:

Mitra S, Rupek P, Richter DC, Urich T, Gilbert JA, Meyer F, et al. (February 2011).

1854: 1842: 1806: 1683: 1602:

metatranscriptomic studies of microbial communities to date. While originally limited to

1566: 1523: 1277: 1226:

reads into genomes difficult and unreliable. Misassemblies are caused by the presence of

1119: 679: 613: 444: 291: 271: 206: 163: 157: 148: 120: 7340: 7183: 7010: 6952: 6887: 6622: 6175: 5549: 5494: 5355: 5118: 5061: 4986:"Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes" 4467: 4271: 3906: 3755: 3538: 3483: 3327: 3193: 3086: 2933: 2880: 2815: 2710: 2652: 2415: 2356: 2123: 1153:

Please expand the section to include this information. Further details may exist on the

48: 7675: 7486: 7357: 7324: 7300: 7273: 7249: 7224: 7200: 7167: 7143: 7108: 7089: 7029: 6994: 6969: 6936: 6912: 6871: 6772: 6718: 6691: 6641: 6606: 6582: 6557: 6533: 6508: 6484: 6457: 6433: 6408: 6294: 6269: 6245: 6218: 6194: 6159: 6135: 6108: 6084: 6057: 5872: 5846: 5819: 5793: 5761: 5736: 5717: 5662: 5637: 5613: 5588: 5569: 5514: 5423: 5398: 5374: 5339: 5274: 5247: 5223: 5198: 5174: 5151: 5078: 5045: 5010: 4985: 4940: 4913: 4889: 4862: 4838: 4813: 4789: 4762: 4735: 4710: 4686: 4659: 4635: 4610: 4586: 4559: 4535: 4509:"Accurate and fast estimation of taxonomic profiles from metagenomic shotgun sequences" 4508: 4484: 4451: 4429: 4381: 4356: 4332: 4307: 4231: 4206: 4182: 4157: 4130: 4105: 4081: 4056: 4032: 4007: 3983: 3958: 3925: 3890: 3871: 3823: 3798: 3774: 3739: 3715: 3690: 3610: 3585: 3555: 3522: 3503: 3444: 3417: 3393: 3368: 3344: 3311: 3260: 3212: 3177: 3153: 3128: 3106: 3050: 3023: 2999: 2972: 2953: 2845: 2730: 2568: 2375: 2340: 2274: 2247: 2142: 2107: 1911: 1893: 1873: 1759: 1634: 1619: 1478: 1281: 1100: 1075: 1063: 980:

and colleagues published the first sequences of an environmental sample generated with

918: 894: 858: 818: 704: 688: 668: 626: 506: 417: 286: 281: 256: 178: 7325:"Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool" 6365: 4984:

Kurokawa K, Itoh T, Kuwahara T, Oshima K, Toh H, Toyoda A, et al. (August 2007).

4355:

Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C (June 2012).

2779: 2752: 2671: 2636: 2612: 2587: 2519: 2494: 2434: 2399: 2315: 2298: 2194: 2169: 7888: 7726: 7535: 7449: 7403: 7362: 7305: 7254: 7205: 7148: 7130: 7093: 7081: 7073: 7053: 7034: 6974: 6935:

Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. (March 2010).

6917: 6899: 6846: 6795: 6776: 6764: 6723: 6646: 6587: 6538: 6489: 6438: 6369: 6322: 6299: 6250: 6199: 6140: 6089: 6036: 5864: 5811: 5766: 5709: 5667: 5618: 5561: 5506: 5463: 5428: 5379: 5320: 5279: 5228: 5179: 5132: 5127: 5102: 5083: 5015: 4945: 4894: 4843: 4794: 4740: 4691: 4640: 4591: 4540: 4489: 4421: 4386: 4337: 4285: 4236: 4187: 4135: 4086: 4037: 3988: 3930: 3863: 3828: 3779: 3720: 3671: 3661: 3615: 3560: 3521:

Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. (March 2010).

3495: 3449: 3398: 3349: 3252: 3235:

Schuster SC (January 2008). "Next-generation sequencing transforms today's biology".

3217: 3158: 3098: 3094: 3055: 3004: 2945: 2894: 2837: 2784: 2722: 2676: 2617: 2560: 2524: 2510: 2495:"Analysis of a marine picoplankton community by 16S rRNA gene cloning and sequencing" 2470: 2439: 2380: 2320: 2279: 2226: 2199: 2185: 2147: 2069: 1996: 1691: 1687: 1629: 1625: 1593: 1456: 1324: 1285: 1216: 1154: 1108: 1071: 1047: 1035: 1031: 1027: 989: 961: 841: 718: 646: 569: 526: 502: 490: 475: 429: 421: 409: 336: 221: 100: 7166:

Zakrzewski M, Rašić G, Darbro J, Krause L, Poo YS, Filipović I, et al. (2018).

5823: 4357:"Metagenomic microbial community profiling using unique clade-specific marker genes" 3875: 3814: 3740:"Assessment of metagenomic assembly using simulated next generation sequencing data" 3507: 2957: 2769: 2572: 1361:

and MetaPhyler, use universal marker genes to profile prokaryotic species. With the

7650: 7645: 7398: 7393: 7381: 7352: 7344: 7295: 7285: 7244: 7236: 7195: 7187: 7138: 7120: 7065: 7024: 7014: 6964: 6956: 6907: 6891: 6754: 6713: 6703: 6636: 6626: 6577: 6569: 6528: 6520: 6479: 6469: 6428: 6420: 6361: 6289: 6281: 6240: 6230: 6189: 6179: 6130: 6120: 6079: 6069: 5948: 5914:"Towards "Tera-Terra": Terabase Sequencing of Terrestrial Metagenomes Print E-mail" 5876: 5856: 5803: 5756: 5748: 5721: 5701: 5657: 5649: 5608: 5600: 5573: 5553: 5518: 5498: 5455: 5418: 5410: 5369: 5359: 5310: 5269: 5259: 5218: 5210: 5169: 5159: 5122: 5073: 5065: 5005: 4997: 4935: 4925: 4884: 4874: 4833: 4825: 4784: 4774: 4730: 4722: 4681: 4671: 4630: 4622: 4581: 4571: 4530: 4520: 4479: 4471: 4433: 4413: 4376: 4368: 4327: 4319: 4275: 4226: 4218: 4177: 4169: 4125: 4117: 4076: 4068: 4027: 4019: 3978: 3970: 3920: 3910: 3855: 3818: 3810: 3769: 3759: 3710: 3702: 3653: 3605: 3597: 3550: 3542: 3487: 3439: 3429: 3388: 3380: 3339: 3331: 3290: 3264: 3244: 3207: 3197: 3148: 3140: 3127:

Segata N, Boernigen D, Tickle TL, Morgan XC, Garrett WS, Huttenhower C (May 2013).

3110: 3090: 3045: 3035: 2994: 2984: 2937: 2884: 2849: 2829: 2774: 2764: 2734: 2714: 2666: 2656: 2607: 2599: 2552: 2514: 2506: 2462: 2429: 2419: 2370: 2360: 2310: 2269: 2259: 2189: 2181: 2137: 2127: 1992: 1965: 1907: 1861: 1858: 1695: 1370: 1255: 483: 392:

directly from samples taken from the environment (e.g. soil, sea water, human gut,

376: 228: 7290: 6605:

Lavery TJ, Roudnew B, Seymour J, Mitchell JG, Jeffries T (2012). Steinke D (ed.).

6424: 4711:"IMG/M: the integrated metagenome data management and comparative analysis system" 2603: 1442:

thresholds and edit distances without affecting the memory and speed performance.

1174: 7862: 7665: 7655: 7640: 7576: 7019: 6631: 6235: 6184: 5459: 5446:

Klitgord N, Segrè D (August 2011). "Ecosystems biology of microbial metabolism".

5414: 5264: 3915: 3764: 3369:"Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond" 3202: 2365: 2264: 2132: 1938: 1585: 1581: 1271: 1259: 902: 5315: 5298: 5164: 4779: 3312:"Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen" 2466: 1530:) working together in order to turn raw resources into fully metabolized waste ( 7850: 7822: 7660: 7563: 7506: 7348: 7191: 7069: 5533: 5344:

Proceedings of the National Academy of Sciences of the United States of America

4763:"Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG" 4525: 4475: 3335: 2641:

Proceedings of the National Academy of Sciences of the United States of America

2490: 2404:

Proceedings of the National Academy of Sciences of the United States of America

2064: 1969: 1942: 1923: 1868: 1846: 1829: 1798: 1662: 1603: 1350: 1239: 1092: 1059: 1017: 985: 906: 879: 845: 401: 389: 276: 201: 7125: 6524: 6285: 5860: 5807: 5752: 4930: 3859: 3649:

The New Science of Metagenomics: Revealing the Secrets of Our Microbial Planet

2400:"Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses" 1473:

ability to study the effect of habitat upon community structure and function.

1416: 1403:

released the Metagenomics Rapid Annotation using Subsystem Technology server (

1095:. Three other technologies commonly applied to environmental sampling are the 7872: 7635: 7581: 7545: 7134: 7077: 6903: 6768: 6074: 2341:"Bioinformatics for whole-genome shotgun sequencing of microbial communities" 2074: 2038: 1556: 1387: 1222: 1190:, or 279 billion base pairs of nucleotide sequence data, while the human gut 993: 898: 890: 886: 874: 866: 580: 576: 561: 522: 7742:

Matrix-assisted laser desorption ionization-time of flight mass spectrometer

6937:"A human gut microbial gene catalogue established by metagenomic sequencing" 6872:"A human gut microbial gene catalogue established by metagenomic sequencing" 6708: 5589:"IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses" 5364: 5001: 4879: 4676: 4452:"Microbial abundance, activity and population genomic profiling with mOTUs2" 3957:

Kunin V, Copeland A, Lapidus A, Mavromatis K, Hugenholtz P (December 2008).

3523:"A human gut microbial gene catalogue established by metagenomic sequencing" 3491: 2941: 2833: 2424: 2059: 1588:

profiles of complex communities. Because of the technical difficulties (the

1412: 1238:

There are several assembly programs, most of which can use information from

1107:

system. These techniques for sequencing DNA generate shorter fragments than

7625: 7586: 7407: 7366: 7309: 7258: 7225:"Targeted Metagenomics Offers Insights into Potential Tick-Borne Pathogens" 7209: 7152: 7085: 7038: 6978: 6921: 6727: 6650: 6591: 6542: 6493: 6442: 6373: 6303: 6254: 6219:"An insect herbivore microbiome with high plant biomass-degrading capacity" 6203: 6144: 6125: 6093: 5868: 5815: 5770: 5713: 5705: 5671: 5622: 5565: 5510: 5467: 5432: 5383: 5324: 5283: 5232: 5183: 5136: 5087: 5019: 4949: 4898: 4847: 4798: 4744: 4695: 4644: 4595: 4544: 4493: 4425: 4390: 4341: 4289: 4240: 4191: 4139: 4090: 4057:"Velvet: algorithms for de novo short read assembly using de Bruijn graphs" 4041: 3992: 3934: 3867: 3832: 3783: 3724: 3675: 3619: 3564: 3499: 3453: 3402: 3353: 3256: 3221: 3162: 3102: 3059: 3008: 2989: 2949: 2898: 2865:"Genomic and functional adaptation in surface ocean planktonic prokaryotes" 2841: 2788: 2726: 2680: 2661: 2384: 2283: 2151: 2021: 1850: 1461: 1346: 1330: 941: 929: 538: 494: 471: 266: 6742: 6474: 6317:

Wong D (2010). "Applications of Metagenomics for Industrial Bioproducts".

5784:

Kerepesi C, Grolmusz V (March 2016). "Giant viruses of the Kutch Desert".

5653: 5604: 4829: 4626: 4280: 4255: 4173: 4121: 4072: 3974: 3434: 3384: 3295: 3278: 3040: 2621: 2564: 2528: 2443: 2324: 2203: 7598: 7530: 7240: 7168:"Mapping the virome in wild-caught Aedes aegypti from Cairns and Bangkok" 6759: 5214: 5069: 4726: 4222: 4156:

Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC (September 2011).

4023: 1783: 1755: 1718: 1699: 1658: 1654: 1544: 1527: 854: 7436:

The “Critical Assessment of Metagenome Interpretation” (CAMI) initiative

6960: 6895: 6109:"Bioprospecting metagenomes: glycosyl hydrolases for converting biomass" 5953: 5936: 5557: 5531: 5502: 4560:"SLIMM: species level identification of microorganisms from metagenomes" 3647: 3546: 3144: 2889: 2864: 2718: 2297:

Handelsman J, Rondon MR, Brady SF, Clardy J, Goodman RM (October 1998).

901:

in human stool and possibly a million different viruses per kilogram of

7683: 7630: 7620: 7615: 6573: 6409:"Size Does Matter: Application-driven Approaches for Soil Metagenomics" 4576: 4417: 4372: 4323: 3706: 3601: 2556: 2398:

Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR (October 1985).

1779: 1589: 1539: 1535: 1515: 1507: 1452: 1242:

in order to improve the accuracy of assemblies. Some programs, such as

1204: 1191: 992:. Another early paper in this area appeared in 2006 by Robert Edwards, 957: 799: 530: 489:, early environmental gene sequencing cloned specific genes (often the 448: 432:

and functional potential of the microbial community of the environment.

196: 110: 90: 65: 5685:

Paez-Espino D, Pavlopoulos GA, Ivanova NN, Kyrpides NC (August 2017).

3248: 1489:

inter-microbial interactions between the resident microbial groups. A

1481:

they apply on reads is based on a number of identical words of length

7610: 6107:

Li LL, McCorkle SR, Monchy S, Taghavi S, van der Lelie D (May 2009).

5684: 4403: 2042: 1933: 1929: 1882: 1821: 1775: 1747: 1714: 1519: 1511: 1298: 1023: 965: 811: 153: 6270:"Achievements and new knowledge unraveled by metagenomic approaches" 825:

sequences have been found which do not belong to any known cultured

821:

within a species, and generally different between species. Many 16S

7845: 7472: 5999:

Understanding Our Microbial Planet: The New Science of Metagenomics

5937:"TerraGenome: A consortium for the sequencing of a soil metagenome" 5851: 5737:"New dimensions of the virus world discovered through metagenomics" 4969: 4811: 3688: 3657: 3586:"Differential abundance analysis for microbial marker-gene surveys" 2973:"Using pyrosequencing to shed light on deep mine microbial ecology" 2106:

Wooley JC, Godzik A, Friedberg I (February 2010). Bourne PE (ed.).

1650: 1427: 1382: 1303: 1187: 970: 949: 479: 440: 212: 95: 85: 40: 7382:"Metagenomic arbovirus detection using MinION nanopore sequencing" 6740: 5798: 5246:

Maillet N, Lemaitre C, Chikhi R, Lavenier D, Peterlongo P (2012).

3175: 2970: 1534:). Using comparative gene studies and expression experiments with 1518:

bioreactor, functional stability requires the presence of several

7571: 5735:

Kristensen DM, Mushegian AR, Dolja VV, Koonin EV (January 2010).

5150:

Ghosh TS, Mohammed MH, Rajasingh H, Chadaram S, Mande SS (2011).

3415: 2586:

Stein JL, Marsh TL, Wu KY, Shizuya H, DeLong EF (February 1996).

1928:

Metagenomics can improve strategies for monitoring the impact of

1802: 1794: 1771: 1743: 1735: 1730: 1666: 1531: 1404: 1366: 1354: 1307: 945: 922: 834: 826: 810:

and thus cannot be sequenced. These early studies focused on 16S

7380:

Batovska J, Lynch SE, Rodoni BC, Sawbridge TI, Cogan NO (2017).

7052:

Chua, Physilia Ying Shi; Rasmussen, Jacob Agerbo (11 May 2022).

5586: 4354: 2801: 1139: 6692:"Metagenomics: A viable tool for reconstructing herbivore diet" 2634: 1957: 1818: 1814: 1251: 1247: 1232: 534: 105: 80: 7323:

Batovska J, Mee PT, Lynch SE, Sawbridge TI, Rodoni BC (2019).

6689: 5968: 5734: 5635: 5149: 5103:"Metagenomic signatures of 86 microbial and viral metagenomes" 4863:"A comparative evaluation of sequence classification programs" 4158:"Integrative analysis of environmental sequences using MEGAN4" 3956: 3845: 1506:

In many bacterial communities, natural or engineered (such as

1292:

searches. This type of approach is implemented in the program

6556:

Raes J, Letunic I, Yamada T, Jensen LJ, Bork P (March 2011).

5480: 5245: 4657: 4006:

Namiki T, Hachiya T, Tanaka H, Sakakibara Y (November 2012).

4005: 1763: 1751: 1706: 1638: 1423: 1342: 1293: 1243: 1183: 956:, and completed a two-year expedition in 2006 to explore the 870: 420:. These short sequences can then be put together again using 7435: 7379: 6604: 4558:

Dadi TH, Renard BY, Wieler LH, Semmler T, Reinert K (2017).

1805:

with industrial applications in biofuel production, such as

7441: 7165: 6991: 5337: 4103: 3737: 3126: 2696: 2296: 1739: 1710: 1702: 1678: 1573: 1465: 1431: 1329:

Gene annotations provide the "what", while measurements of

1070:, randomly shears DNA, sequences many short sequences, and 822: 6506: 4983: 4911: 3129:"Computational meta'omics for microbial community studies" 7322: 6157: 5934: 4962: 4449: 4155: 3796: 2862: 2637:"Genomic analysis of uncultured marine viral communities" 1606:

technology, metatranscriptomics studies have made use of

1510:), there is significant division of labor in metabolism ( 1490: 1362: 1358: 814: 803: 381: 75: 70: 4912:

Ounit R, Wanamaker S, Close TJ, Lonardi S (March 2015).

4608: 4506: 4207:"Ab initio gene identification in metagenomic sequences" 4104:

Burton JN, Liachko I, Dunham MJ, Shendure J (May 2014).

3799:"Filtering duplicate reads from 454 pyrosequencing data" 802:

begins with a culture of identical cells as a source of

6555: 6455: 6106: 5396: 4557: 3797:

Balzer S, Malde K, Grohme MA, Jonassen I (April 2013).

3584:

Paulson JN, Stine OC, Bravo HC, Pop M (December 2013).

3309: 3072: 3024:"Metagenomics - a guide from sampling to data analysis" 1250:

Assembler, were designed to be used to assemble single

925:

that had previously resisted attempts to culture them.

6840: 5920:. Vol. 6, no. 7. p. 309. Archived from 5397:

McInerney MJ, Sieber JR, Gunsalus RP (December 2009).

5196: 4760: 4507:

Liu B, Gibbons T, Ghodsi M, Treangen T, Pop M (2011).

2919: 7834: 6216: 4708: 4204: 3416:

Pérez-Cobas AE, Gomez-Valero L, Buchrieser C (2020).

2541: 2105: 1114:

An emerging approach combines shotgun sequencing and

1022:

Recovery of DNA sequences longer than a few thousand

833:

based methods find less than 1% of the bacterial and

6789: 5248:"Compareads: comparing huge metagenomic experiments" 5100: 3583: 2753:"Exploring prokaryotic diversity in the genomic era" 2167: 6406: 4306:Huson DH, Auch AF, Qi J, Schuster SC (March 2007). 4305: 2585: 2219:

Metagenomics: Current Innovations and Future Trends

2168:Hugenholtz P, Goebel BM, Pace NR (September 1998). 1964:with primary goals to determine if there is a core 1417:

Genomic Encyclopedia of Bacteria and Archaea (GEBA)

861:. Considerable efforts ensured that these were not 817:(rRNA) sequences which are relatively short, often 6407:Kakirde KS, Parsley LC, Liles MR (November 2010). 3652:. Washington, D.C.: The National Academies Press. 3469: 3366: 3178:"Unlocking short read sequencing for metagenomics" 3021: 2456: 2397: 1284:with genes that are already publicly available in 952:never before seen. Venter thoroughly explored the 6934: 6868: 6665:"What's Swimming in the River? Just Look For DNA" 6344: 3520: 2489: 1641:in a saline desert and in Antarctic dry valleys. 932:, leader of the privately funded parallel of the 7870: 7271: 5836: 5783: 5296: 3888: 3641: 3639: 3637: 3635: 3633: 3631: 3629: 3367:Hiraoka S, Yang CC, Iwasaki W (September 2016). 1774:. Microbes also produce a variety of sources of 5973:TerraGenome international sequencing consortium 5197:Fimereli D, Detours V, Konopka T (April 2013). 4860: 4445: 4443: 2163: 2161: 2029:sequences with associated clinical phenotypes. 2015: 1948: 6843:Metagenomics: Theory, Methods and Applications 6792:Metagenomics: Theory, Methods and Applications 6402: 6400: 6398: 6347:"Biotechnological prospects from metagenomics" 6340: 6338: 6319:Metagenomics: Theory, Methods and Applications 6033:Metagenomics: Theory, Methods and Applications 6005:. The National Academies Press. Archived from 5991: 5989: 5297:Kuntal BK, Ghosh TS, Mande SS (October 2013). 5046:"Metagenomic analyses: past and future trends" 4551: 3579: 3577: 3022:Thomas T, Gilbert J, Meyer F (February 2012). 1682:understood despite their economic importance. 1122:, and Nanopore MinION, GridION, PromethION by 497:had been missed by cultivation-based methods. 7457: 7373: 7316: 7265: 7216: 7159: 7051: 5474: 5445: 5399:"Syntrophy in anaerobic global carbon cycles" 5390: 5101:Willner D, Thurber RV, Rohwer F (July 2009). 4702: 4205:Zhu W, Lomsadze A, Borodovsky M (July 2010). 4054: 3952: 3950: 3948: 3946: 3944: 3626: 3122: 3120: 2915: 2913: 2911: 2744: 2628: 2290: 1081: 779: 451:. The broad field may also be referred to as 357: 7107:Chiu, Charles Y.; Miller, Steven A. (2019). 6456:Parachin NS, Gorwa-Grauslund MF (May 2011). 6449: 6151: 6055: 5439: 5190: 5039: 5037: 5035: 5033: 5031: 5029: 4977: 4756: 4754: 4440: 4397: 4301: 4299: 4151: 4149: 3959:"A bioinformatician's guide to metagenomics" 3228: 3169: 2692: 2690: 2158: 2101: 2099: 2097: 2095: 2093: 2091: 2089: 1917: 1030:was very difficult until recent advances in 1012:Flow diagram of a typical metagenome project 7737:Matrix-assisted laser desorption ionization 6834: 6395: 6335: 6267: 6024: 5986: 5905: 5239: 5094: 5043: 4854: 4247: 3574: 3465: 3463: 2964: 2856: 2461:. Vol. 9. Springer US. pp. 1–55. 2338: 1592:of mRNA, for example) in the collection of 1445: 7805: 7464: 7450: 7106: 6808: 6783: 6598: 6500: 6261: 5777: 5728: 5331: 5290: 4805: 4602: 4348: 4097: 3963:Microbiology and Molecular Biology Reviews 3941: 3117: 2908: 2795: 2750: 1637:showed the first evidence of existence of 786: 772: 521:The term "metagenomics" was first used by 364: 350: 7397: 7356: 7299: 7289: 7248: 7199: 7142: 7124: 7028: 7018: 6968: 6911: 6758: 6717: 6707: 6640: 6630: 6581: 6532: 6483: 6473: 6432: 6293: 6244: 6234: 6193: 6183: 6134: 6124: 6083: 6073: 5952: 5928: 5850: 5797: 5760: 5661: 5612: 5422: 5373: 5363: 5314: 5273: 5263: 5222: 5173: 5163: 5143: 5126: 5077: 5026: 5009: 4968: 4939: 4929: 4905: 4888: 4878: 4837: 4788: 4778: 4751: 4734: 4685: 4675: 4651: 4634: 4585: 4575: 4534: 4524: 4483: 4380: 4331: 4296: 4279: 4230: 4181: 4146: 4129: 4080: 4031: 3982: 3924: 3914: 3822: 3773: 3763: 3714: 3609: 3554: 3443: 3433: 3392: 3343: 3294: 3271: 3211: 3201: 3152: 3049: 3039: 3028:Microbial Informatics and Experimentation 2998: 2988: 2888: 2823: 2778: 2768: 2687: 2670: 2660: 2611: 2579: 2535: 2518: 2433: 2423: 2374: 2364: 2314: 2273: 2263: 2210: 2193: 2141: 2131: 2086: 2032: 1791:efficient industrial-scale deconstruction 1198: 7222: 6549: 6310: 6210: 5889: 3460: 3234: 3066: 2239: 2216: 1892: 1409:Integrated Microbial Genomes/Metagenomes 1173: 1007: 380:In metagenomics, the genetic materials ( 375: 6030: 5911: 4500: 4253: 4198: 3514: 2483: 2391: 2332: 1501: 1053: 1034:techniques allowed the construction of 944:, found DNA from nearly 2000 different 447:or clinical samples by a method called 27:Study of genes found in the environment 14: 7871: 6864: 6862: 6814: 6345:Schloss PD, Handelsman J (June 2003). 6316: 6274:Applied Microbiology and Biotechnology 6100: 5890:Copeland CS (September–October 2017). 5830: 5050:Applied and Environmental Microbiology 4956: 4256:"What is microbial community ecology?" 2545:Applied Microbiology and Biotechnology 1867:Two types of analysis are used in the 1690:necessary for plant growth, including 1550: 7779:European Molecular Biology Laboratory 7445: 7054:"Taking metagenomics under the wings" 5961: 3889:Schmieder R, Edwards R (March 2011). 3731: 2245: 873:. After leaving the Pace laboratory, 7272:Parry R, James ME, Asgari S (2021). 4861:Bazinet AL, Cummings MP (May 2012). 4308:"MEGAN analysis of metagenomic data" 1956:play a key role in preserving human 1746:conversion, as in the conversion of 1318: 1133: 893:, and colleagues used environmental 7438:to evaluate methods in metagenomics 6859: 6817:"How Microbes Defend and Define Us" 6268:Simon C, Daniel R (November 2009). 5158:. 12 Suppl 13 (Supplement 13): S9. 5044:Simon C, Daniel R (February 2011). 3695:Bioinformatics and Biology Insights 1376: 1097:Ion Torrent Personal Genome Machine 24: 6985: 6056:Bringel F, Couée I (22 May 2015). 2493:, DeLong EF, Pace NR (July 1991). 1914:, and track seasonal populations. 1265: 984:, in this case massively parallel 911:University of California, Berkeley 740:Consortium for the Barcode of Life 543:University of California, Berkeley 25: 7910: 7417: 5899:Healthcare Journal of New Orleans 4055:Zerbino DR, Birney E (May 2008). 3279:"Metagenomics versus Moore's law" 1129: 443:material recovered directly from 7856: 7844: 7817: 7816: 7804: 7100: 7045: 6928: 6354:Current Opinion in Biotechnology 5448:Current Opinion in Biotechnology 5403:Current Opinion in Biotechnology 5128:10.1111/j.1462-2920.2009.01901.x 3969:(4): 557–78, Table of Contents. 3095:10.1046/j.1462-2920.2000.00133.x 2511:10.1128/jb.173.14.4371-4378.1991 2186:10.1128/JB.180.18.4765-4774.1998 1835: 1496: 1138: 1040:bacterial artificial chromosomes 938:Global Ocean Sampling Expedition 917:sequenced DNA extracted from an 753: 752: 568: 331: 330: 217: 216: 47: 7757:Chromosome conformation capture 6734: 6683: 6657: 6413:Soil Biology & Biochemistry 6049: 5883: 5678: 5629: 5580: 5525: 4048: 3999: 3882: 3839: 3790: 3682: 3409: 3360: 3303: 3015: 2770:10.1186/gb-2002-3-2-reviews0003 2339:Chen K, Pachter L (July 2005). 2026:Clinical metagenomic sequencing 1717:and the adaptation of enhanced 1644: 1596:there have been relatively few 1434:classifications, respectively. 1116:chromosome conformation capture 976:In 2005 Stephan C. Schuster at 954:West Coast of the United States 7399:10.1016/j.jviromet.2017.08.019 6747:Metabarcoding and Metagenomics 2450: 1972:tools to support these goals. 1672: 1628:for bacteria and archaea, and 1580:) provides information on the 1345:. Another tool, PhymmBL, uses 1042:(BACs), which provided better 844:in the field was conducted by 13: 1: 7785:National Institutes of Health 7291:10.3390/microorganisms9081653 6425:10.1016/j.soilbio.2010.07.021 6366:10.1016/S0958-1669(03)00067-3 3815:10.1093/bioinformatics/btt047 2604:10.1128/jb.178.3.591-599.1996 2459:Advances in Microbial Ecology 2316:10.1016/S1074-5521(98)90108-9 2080: 1003: 7471: 7020:10.1371/journal.pcbi.1002358 6993:Huttenhower, Curtis (2012). 6632:10.1371/journal.pone.0036478 6236:10.1371/journal.pgen.1001129 6185:10.1371/journal.pone.0014519 5460:10.1016/j.copbio.2011.04.018 5415:10.1016/j.copbio.2009.10.001 5265:10.1186/1471-2105-13-S19-S10 3916:10.1371/journal.pone.0017288 3765:10.1371/journal.pone.0031386 3203:10.1371/journal.pone.0011840 2366:10.1371/journal.pcbi.0010024 2265:10.1371/journal.pbio.0050082 2133:10.1371/journal.pcbi.1000667 2016:Infectious disease diagnosis 1949:Gut microbe characterization 1864:is increasingly recognized. 1608:transcriptomics technologies 1561:Transcriptomics technologies 1413:Integrated Microbial Genomes 1124:Oxford Nanopore Technologies 516: 7: 7701:Structure-based drug design 7429:Nature Reviews Microbiology 7058:Nature Reviews Microbiology 6696:Molecular Ecology Resources 5941:Nature Reviews Microbiology 5534:"Uncovering Earth's virome" 5316:10.1016/j.ygeno.2013.08.004 5165:10.1186/1471-2105-12-s13-s9 4780:10.1186/1471-2105-12-S1-S21 4254:Konopka A (November 2009). 2467:10.1007/978-1-4757-0611-6_1 2048: 1962:Human Microbiome initiative 1698:, disease suppression, and 1692:fixing atmospheric nitrogen 1397:Argonne National Laboratory 1210: 10: 7915: 7894:Environmental microbiology 7349:10.1038/s41598-019-55741-3 7192:10.1038/s41598-018-22945-y 7070:10.1038/s41579-022-00746-5 6999:PLOS Computational Biology 6845:. Caister Academic Press. 6794:. Caister Academic Press. 6462:Biotechnology for Biofuels 6321:. Caister Academic Press. 6113:Biotechnology for Biofuels 6035:. Caister Academic Press. 5107:Environmental Microbiology 4824:(Database issue): D36-42. 4721:(Database issue): D123-9. 4621:(Database issue): D571-9. 4526:10.1186/1471-2164-12-S2-S4 4476:10.1038/s41467-019-08844-4 3336:10.1038/s41467-018-03317-6 3075:Environmental Microbiology 2345:PLOS Computational Biology 2112:PLOS Computational Biology 2108:"A primer on metagenomics" 1921: 1888: 1793:of biomass requires novel 1728: 1724: 1686:perform a wide variety of 1617: 1613: 1564: 1554: 1485:shared by pairs of reads. 1347:interpolated Markov models 1322: 1269: 1214: 1089:high-throughput sequencing 1082:High-throughput sequencing 1015: 998:San Diego State University 982:high-throughput sequencing 710:High throughput sequencing 548: 537:. In 2005, Kevin Chen and 408:) after multiplication by 7800: 7791:Wellcome Sanger Institute 7765: 7714: 7674: 7562: 7479: 7126:10.1038/s41576-019-0113-7 6815:Zimmer C (13 July 2010). 6562:Molecular Systems Biology 6525:10.1038/s41564-018-0110-1 6286:10.1007/s00253-009-2233-z 6062:Frontiers in Microbiology 5861:10.1007/s00705-017-3286-4 5808:10.1007/s00705-015-2720-8 5753:10.1016/j.tim.2009.11.003 4931:10.1186/s12864-015-1419-2 3860:10.1007/s12038-011-9105-2 3373:Microbes and Environments 3133:Molecular Systems Biology 1918:Environmental remediation 1758:, and other biomass into 1186:metagenome generated 279 948:, including 148 types of 848:and colleagues, who used 7747:Microfluidic-based tools 7592:Human Connectome Project 7524:Human Microbiome Project 6075:10.3389/fmicb.2015.00486 1989:Human Microbiome Project 1446:Comparative metagenomics 1310:. The main advantage of 1228:repetitive DNA sequences 1105:Applied Biosystems SOLiD 1091:used massively parallel 867:non-protein coding genes 647:Environmental DNA (eDNA) 416:) in an approach called 7899:Microbiology techniques 7732:Electrospray ionization 7604:Human Epigenome Project 7113:Nature Reviews Genetics 7109:"Clinical metagenomics" 6709:10.1111/1755-0998.13425 5365:10.1073/pnas.1015676108 4880:10.1186/1471-2105-13-92 4677:10.1186/1471-2105-9-386 3570:(subscription required) 3492:10.1126/science.1200387 2942:10.1126/science.1123360 2904:(subscription required) 2834:10.1126/science.1093857 2740:(subscription required) 2592:Journal of Bacteriology 2499:Journal of Bacteriology 2425:10.1073/pnas.82.20.6955 2303:Chemistry & Biology 2246:Eisen JA (March 2007). 2174:Journal of Bacteriology 2060:Epidemiology and sewage 2002:evidence-based medicine 1874:conserved DNA sequences 1813:microbial systems like 1103:MiSeq or HiSeq and the 7773:DNA Data Bank of Japan 7689:Human proteome project 7492:Computational genomics 6702:(7): 1755–0998.13425. 6126:10.1186/1754-6834-2-10 5969:"TerraGenome Homepage" 5741:Trends in Microbiology 5706:10.1038/nprot.2017.063 5642:Nucleic Acids Research 5593:Nucleic Acids Research 5203:Nucleic Acids Research 4818:Nucleic Acids Research 4715:Nucleic Acids Research 4615:Nucleic Acids Research 4211:Nucleic Acids Research 4012:Nucleic Acids Research 3848:Journal of Biosciences 2990:10.1186/1471-2164-7-57 2662:10.1073/pnas.202488399 2223:Caister Academic Press 2217:Marco, D, ed. (2011). 2033:Arbovirus surveillance 1898: 1199:Sequence pre-filtering 1179: 1149:is missing information 1013: 915:Joint Genome Institute 529:, Michelle R. Rondon, 495:microbial biodiversity 453:environmental genomics 433: 7752:Isotope affinity tags 7706:Expression proteomics 7424:Focus on Metagenomics 6475:10.1186/1754-6834-4-9 5892:"The World Within Us" 5002:10.1093/dnares/dsm018 4456:Nature Communications 4281:10.1038/ismej.2009.88 4174:10.1101/gr.120618.111 4122:10.1534/g3.114.011825 4073:10.1101/gr.074492.107 3975:10.1128/MMBR.00009-08 3435:10.1099/mgen.0.000409 3385:10.1264/jsme2.ME16024 3316:Nature Communications 3296:10.1038/nmeth0909-623 3041:10.1186/2042-5783-2-3 2751:Hugenholtz P (2002). 2006:personalized medicine 1954:Microbial communities 1896: 1857:where the benefit of 1555:Further information: 1415:(IMG) system and the 1401:University of Chicago 1276:Metagenomic analysis 1177: 1011: 978:Penn State University 482:rely upon cultivated 379: 317:Personalized medicine 311:Personalized medicine 174:Quantitative genetics 169:Mendelian inheritance 7512:Human Genome Project 7497:Comparative genomics 7241:10.1128/JCM.01893-20 6760:10.3897/mbmg.6.78756 5839:Archives of Virology 5786:Archives of Virology 5070:10.1128/AEM.02345-10 1807:glycoside hydrolases 1502:Community metabolism 1054:Shotgun metagenomics 1032:molecular biological 996:, and colleagues at 934:Human Genome Project 541:(researchers at the 237:Branches of genetics 7722:2-D electrophoresis 7696:Call-map proteomics 7554:Structural genomics 7541:Population genomics 7502:Functional genomics 7341:2019NatSR...919398B 7223:Thoendel M (2020). 7184:2018NatSR...8.4690Z 7011:2012PLSCB...8E2358A 6961:10.1038/nature08821 6953:2010Natur.464...59. 6896:10.1038/nature08821 6888:2010Natur.464...59. 6623:2012PLoSO...736478L 6513:Nature Microbiology 6176:2011PLoSO...614519J 5954:10.1038/nrmicro2119 5654:10.1093/nar/gky1127 5605:10.1093/nar/gkw1030 5558:10.1038/nature19094 5550:2016Natur.536..425P 5503:10.1038/nature04983 5495:2006Natur.442..806L 5356:2011PNAS..108.4158W 5119:2009EnvMi..11.1752W 5062:2011ApEnM..77.1153S 4830:10.1093/nar/gks1195 4627:10.1093/nar/gkr1100 4468:2019NatCo..10.1014M 4272:2009ISMEJ...3.1223K 3907:2011PLoSO...617288S 3756:2012PLoSO...731386M 3547:10.1038/nature08821 3539:2010Natur.464...59. 3484:2011Sci...331..463H 3328:2018NatCo...9..870S 3194:2010PLoSO...511840R 3145:10.1038/msb.2013.22 3087:2000EnvMi...2..516B 2934:2006Sci...311..392P 2890:10.1038/nature09530 2881:2010Natur.468...60Y 2816:2004Sci...304...66V 2719:10.1038/nature02340 2711:2004Natur.428...37T 2653:2002PNAS...9914250B 2416:1985PNAS...82.6955L 2357:2005PLSCB...1...24C 2124:2010PLSCB...6E0667W 1984:bacterial genomes. 1945:trials to succeed. 1770:of the sugars into 1684:Microbial consortia 1567:Metatranscriptomics 1551:Metatranscriptomics 1524:Syntrophobacterales 1120:Pacific Biosciences 1026:from environmental 928:Beginning in 2003, 840:In the 1980s early 680:Metatranscriptomics 556:Part of a series on 396:) after filtering ( 207:Genetic engineering 164:Population genetics 35:Part of a series on 7676:Structural biology 7487:Cognitive genomics 6574:10.1038/msb.2011.6 6012:on 30 October 2012 5912:Jansson J (2011). 5252:BMC Bioinformatics 5215:10.1093/nar/gkt094 5156:BMC Bioinformatics 4867:BMC Bioinformatics 4767:BMC Bioinformatics 4727:10.1093/nar/gkr975 4664:BMC Bioinformatics 4577:10.7717/peerj.3138 4418:10.1038/nmeth.2693 4373:10.1038/nmeth.2066 4324:10.1101/gr.5969107 4223:10.1093/nar/gkq275 4024:10.1093/nar/gks678 3707:10.4137/BBI.S12462 3602:10.1038/nmeth.2658 3422:Microbial Genomics 2763:(2): REVIEWS0003. 2557:10.1007/BF00164771 1912:endangered species 1899: 1878:design PCR primers 1766:, followed by the 1760:cellulosic ethanol 1688:ecosystem services 1635:Giant Virus Finder 1620:Viral metagenomics 1479:similarity measure 1286:sequence databases 1180: 1093:454 pyrosequencing 1076:consensus sequence 1064:shotgun sequencing 1014: 919:acid mine drainage 895:shotgun sequencing 859:Indiana University 705:Shotgun sequencing 622:macroinvertebrates 470:While traditional 461:community genomics 434: 418:shotgun sequencing 179:Molecular genetics 138:History and topics 7832: 7831: 7727:Mass spectrometer 7536:Personal genomics 6852:978-1-904455-54-7 6801:978-1-904455-54-7 6419:(11): 1911–1923. 6328:978-1-904455-54-7 6042:978-1-904455-54-7 5924:on 31 March 2012. 5648:(D1): D678–D686. 5599:(D1): D457–D465. 5258:(Suppl 19): S10. 3667:978-0-309-10676-4 3249:10.1038/nmeth1156 2476:978-1-4757-0611-6 2232:978-1-904455-87-5 2070:Microbial ecology 1997:glycosaminoglycan 1594:environmental RNA 1578:metatranscriptome 1349:to assign reads. 1331:species diversity 1325:Species diversity 1319:Species diversity 1217:Sequence assembly 1172: 1171: 1109:Sanger sequencing 1048:molecular cloning 990:454 Life Sciences 905:, including many 796: 795: 719:Extracellular RNA 653:environmental RNA 527:Robert M. Goodman 503:microbial ecology 476:genome sequencing 430:species diversity 374: 373: 101:Genetic variation 16:(Redirected from 7906: 7861: 7860: 7859: 7849: 7848: 7840: 7820: 7819: 7808: 7807: 7651:Pharmacogenomics 7646:Pharmacogenetics 7466: 7459: 7452: 7443: 7442: 7412: 7411: 7401: 7377: 7371: 7370: 7360: 7320: 7314: 7313: 7303: 7293: 7269: 7263: 7262: 7252: 7229:J Clin Microbiol 7220: 7214: 7213: 7203: 7163: 7157: 7156: 7146: 7128: 7104: 7098: 7097: 7049: 7043: 7042: 7032: 7022: 6989: 6983: 6982: 6972: 6932: 6926: 6925: 6915: 6866: 6857: 6856: 6838: 6832: 6831: 6829: 6827: 6812: 6806: 6805: 6787: 6781: 6780: 6762: 6738: 6732: 6731: 6721: 6711: 6687: 6681: 6680: 6678: 6676: 6661: 6655: 6654: 6644: 6634: 6602: 6596: 6595: 6585: 6553: 6547: 6546: 6536: 6504: 6498: 6497: 6487: 6477: 6453: 6447: 6446: 6436: 6404: 6393: 6392: 6390: 6388: 6382: 6376:. Archived from 6351: 6342: 6333: 6332: 6314: 6308: 6307: 6297: 6265: 6259: 6258: 6248: 6238: 6214: 6208: 6207: 6197: 6187: 6155: 6149: 6148: 6138: 6128: 6104: 6098: 6097: 6087: 6077: 6053: 6047: 6046: 6028: 6022: 6021: 6019: 6017: 6011: 6004: 5993: 5984: 5983: 5981: 5979: 5965: 5959: 5958: 5956: 5932: 5926: 5925: 5909: 5903: 5902: 5896: 5887: 5881: 5880: 5854: 5845:(6): 1671–1676. 5834: 5828: 5827: 5801: 5781: 5775: 5774: 5764: 5732: 5726: 5725: 5700:(8): 1673–1682. 5694:Nature Protocols 5691: 5682: 5676: 5675: 5665: 5633: 5627: 5626: 5616: 5584: 5578: 5577: 5544:(7617): 425–30. 5529: 5523: 5522: 5478: 5472: 5471: 5443: 5437: 5436: 5426: 5394: 5388: 5387: 5377: 5367: 5335: 5329: 5328: 5318: 5294: 5288: 5287: 5277: 5267: 5243: 5237: 5236: 5226: 5194: 5188: 5187: 5177: 5167: 5147: 5141: 5140: 5130: 5098: 5092: 5091: 5081: 5041: 5024: 5023: 5013: 4981: 4975: 4974: 4972: 4960: 4954: 4953: 4943: 4933: 4909: 4903: 4902: 4892: 4882: 4858: 4852: 4851: 4841: 4809: 4803: 4802: 4792: 4782: 4773:(Suppl 1): S21. 4758: 4749: 4748: 4738: 4706: 4700: 4699: 4689: 4679: 4655: 4649: 4648: 4638: 4606: 4600: 4599: 4589: 4579: 4555: 4549: 4548: 4538: 4528: 4504: 4498: 4497: 4487: 4447: 4438: 4437: 4401: 4395: 4394: 4384: 4352: 4346: 4345: 4335: 4303: 4294: 4293: 4283: 4260:The ISME Journal 4251: 4245: 4244: 4234: 4202: 4196: 4195: 4185: 4153: 4144: 4143: 4133: 4101: 4095: 4094: 4084: 4052: 4046: 4045: 4035: 4003: 3997: 3996: 3986: 3954: 3939: 3938: 3928: 3918: 3886: 3880: 3879: 3843: 3837: 3836: 3826: 3794: 3788: 3787: 3777: 3767: 3735: 3729: 3728: 3718: 3686: 3680: 3679: 3643: 3624: 3623: 3613: 3581: 3572: 3571: 3568: 3558: 3518: 3512: 3511: 3467: 3458: 3457: 3447: 3437: 3413: 3407: 3406: 3396: 3364: 3358: 3357: 3347: 3307: 3301: 3300: 3298: 3289:(9): 623. 2009. 3275: 3269: 3268: 3232: 3226: 3225: 3215: 3205: 3173: 3167: 3166: 3156: 3124: 3115: 3114: 3070: 3064: 3063: 3053: 3043: 3019: 3013: 3012: 3002: 2992: 2968: 2962: 2961: 2917: 2906: 2905: 2902: 2892: 2860: 2854: 2853: 2827: 2799: 2793: 2792: 2782: 2772: 2748: 2742: 2741: 2738: 2694: 2685: 2684: 2674: 2664: 2632: 2626: 2625: 2615: 2583: 2577: 2576: 2539: 2533: 2532: 2522: 2487: 2481: 2480: 2454: 2448: 2447: 2437: 2427: 2395: 2389: 2388: 2378: 2368: 2336: 2330: 2328: 2318: 2294: 2288: 2287: 2277: 2267: 2243: 2237: 2236: 2214: 2208: 2207: 2197: 2165: 2156: 2155: 2145: 2135: 2103: 1993:human microbiome 1966:human microbiome 1908:invasive species 1862:chiral synthesis 1859:enzyme-catalyzed 1696:nutrient cycling 1377:Data integration 1371:codon usage bias 1260:de Bruijn graphs 1256:Velvet assembler 1167: 1164: 1158: 1142: 1134: 788: 781: 774: 761: 756: 755: 572: 553: 552: 439:is the study of 422:assembly methods 366: 359: 352: 339: 334: 333: 229:Medical genetics 225: 220: 219: 51: 32: 31: 21: 7914: 7913: 7909: 7908: 7907: 7905: 7904: 7903: 7869: 7868: 7867: 7857: 7855: 7843: 7835: 7833: 7828: 7796: 7761: 7710: 7670: 7666:Transcriptomics 7656:Systems biology 7641:Paleopolyploidy 7577:Cheminformatics 7558: 7475: 7470: 7432:journal website 7420: 7415: 7386:J Virol Methods 7378: 7374: 7321: 7317: 7270: 7266: 7221: 7217: 7164: 7160: 7105: 7101: 7050: 7046: 7005:(6): e1002358. 6990: 6986: 6947:(7285): 59–65. 6933: 6929: 6882:(7285): 59–65. 6867: 6860: 6853: 6839: 6835: 6825: 6823: 6813: 6809: 6802: 6788: 6784: 6739: 6735: 6688: 6684: 6674: 6672: 6663: 6662: 6658: 6603: 6599: 6554: 6550: 6505: 6501: 6454: 6450: 6405: 6396: 6386: 6384: 6383:on 4 March 2016 6380: 6349: 6343: 6336: 6329: 6315: 6311: 6266: 6262: 6229:(9): e1001129. 6215: 6211: 6156: 6152: 6105: 6101: 6054: 6050: 6043: 6029: 6025: 6015: 6013: 6009: 6002: 5994: 5987: 5977: 5975: 5967: 5966: 5962: 5933: 5929: 5910: 5906: 5894: 5888: 5884: 5835: 5831: 5782: 5778: 5733: 5729: 5689: 5683: 5679: 5634: 5630: 5585: 5581: 5530: 5526: 5489:(7104): 806–9. 5479: 5475: 5444: 5440: 5395: 5391: 5350:(10): 4158–63. 5336: 5332: 5295: 5291: 5244: 5240: 5195: 5191: 5148: 5144: 5099: 5095: 5042: 5027: 4982: 4978: 4961: 4957: 4910: 4906: 4859: 4855: 4810: 4806: 4759: 4752: 4707: 4703: 4656: 4652: 4607: 4603: 4556: 4552: 4519:(Suppl 2): S4. 4505: 4501: 4448: 4441: 4402: 4398: 4353: 4349: 4312:Genome Research 4304: 4297: 4266:(11): 1223–30. 4252: 4248: 4203: 4199: 4162:Genome Research 4154: 4147: 4102: 4098: 4061:Genome Research 4053: 4049: 4004: 4000: 3955: 3942: 3887: 3883: 3844: 3840: 3795: 3791: 3736: 3732: 3687: 3683: 3668: 3644: 3627: 3582: 3575: 3569: 3533:(7285): 59–65. 3519: 3515: 3478:(6016): 463–7. 3468: 3461: 3414: 3410: 3365: 3361: 3308: 3304: 3277: 3276: 3272: 3233: 3229: 3174: 3170: 3125: 3118: 3071: 3067: 3020: 3016: 2969: 2965: 2928:(5759): 392–4. 2918: 2909: 2903: 2861: 2857: 2825:10.1.1.124.1840 2810:(5667): 66–74. 2800: 2796: 2749: 2745: 2739: 2705:(6978): 37–43. 2695: 2688: 2647:(22): 14250–5. 2633: 2629: 2584: 2580: 2540: 2536: 2488: 2484: 2477: 2455: 2451: 2396: 2392: 2337: 2333: 2295: 2291: 2244: 2240: 2233: 2215: 2211: 2180:(18): 4765–74. 2166: 2159: 2118:(2): e1000667. 2104: 2087: 2083: 2051: 2035: 2018: 1951: 1939:bioaugmentation 1926: 1920: 1891: 1855:pharmaceuticals 1838: 1830:leafcutter ants 1733: 1727: 1675: 1647: 1622: 1616: 1590:short half-life 1569: 1563: 1553: 1504: 1499: 1448: 1379: 1327: 1321: 1296:4. The second, 1274: 1272:Gene prediction 1268: 1266:Gene prediction 1240:paired-end tags 1219: 1213: 1201: 1168: 1162: 1159: 1152: 1143: 1132: 1084: 1056: 1020: 1006: 903:marine sediment 792: 751: 744: 735:Diet assessment 726: 714: 700: 684: 675: 659: 649: 633: 585: 583: 575: 551: 519: 370: 329: 322: 321: 312: 304: 303: 302: 301: 250: 242: 241: 233: 211: 192: 184: 183: 139: 131: 130: 117: 116: 115: 59: 28: 23: 22: 15: 12: 11: 5: 7912: 7902: 7901: 7896: 7891: 7886: 7884:Bioinformatics 7881: 7866: 7865: 7853: 7830: 7829: 7827: 7826: 7814: 7801: 7798: 7797: 7795: 7794: 7788: 7782: 7776: 7769: 7767: 7763: 7762: 7760: 7759: 7754: 7749: 7744: 7739: 7734: 7729: 7724: 7718: 7716: 7715:Research tools 7712: 7711: 7709: 7708: 7703: 7698: 7693: 7692: 7691: 7680: 7678: 7672: 7671: 7669: 7668: 7663: 7661:Toxicogenomics 7658: 7653: 7648: 7643: 7638: 7633: 7628: 7623: 7618: 7613: 7608: 7607: 7606: 7596: 7595: 7594: 7584: 7579: 7574: 7568: 7566: 7564:Bioinformatics 7560: 7559: 7557: 7556: 7551: 7543: 7538: 7533: 7528: 7527: 7526: 7516: 7515: 7514: 7507:Genome project 7504: 7499: 7494: 7489: 7483: 7481: 7477: 7476: 7469: 7468: 7461: 7454: 7446: 7440: 7439: 7433: 7419: 7418:External links 7416: 7414: 7413: 7372: 7315: 7278:Microorganisms 7264: 7215: 7158: 7119:(6): 341–355. 7099: 7044: 6984: 6927: 6858: 6851: 6833: 6821:New York Times 6807: 6800: 6782: 6733: 6682: 6671:. 24 July 2013 6656: 6597: 6548: 6519:(4): 415–422. 6499: 6448: 6394: 6334: 6327: 6309: 6260: 6209: 6150: 6099: 6048: 6041: 6023: 5985: 5960: 5927: 5904: 5882: 5829: 5776: 5727: 5677: 5628: 5579: 5524: 5473: 5438: 5389: 5330: 5289: 5238: 5189: 5142: 5113:(7): 1752–66. 5093: 5056:(4): 1153–61. 5025: 4976: 4970:10.1101/267179 4955: 4904: 4853: 4804: 4750: 4701: 4650: 4601: 4550: 4499: 4439: 4412:(12): 1196–9. 4406:Nature Methods 4396: 4361:Nature Methods 4347: 4295: 4246: 4197: 4168:(9): 1552–60. 4145: 4116:(7): 1339–46. 4096: 4047: 3998: 3940: 3881: 3838: 3803:Bioinformatics 3789: 3730: 3681: 3666: 3658:10.17226/11902 3625: 3596:(12): 1200–2. 3590:Nature Methods 3573: 3513: 3459: 3408: 3359: 3302: 3283:Nature Methods 3270: 3237:Nature Methods 3227: 3168: 3116: 3065: 3014: 2963: 2907: 2875:(7320): 60–6. 2855: 2794: 2757:Genome Biology 2743: 2686: 2627: 2578: 2534: 2505:(14): 4371–8. 2482: 2475: 2449: 2410:(20): 6955–9. 2390: 2331: 2309:(10): R245-9. 2289: 2238: 2231: 2209: 2157: 2084: 2082: 2079: 2078: 2077: 2072: 2067: 2065:Metaproteomics 2062: 2057: 2050: 2047: 2034: 2031: 2017: 2014: 1970:bioinformatics 1950: 1947: 1943:biostimulation 1924:Bioremediation 1922:Main article: 1919: 1916: 1890: 1887: 1869:bioprospecting 1847:fine chemicals 1837: 1834: 1817:fermenters or 1729:Main article: 1726: 1723: 1674: 1671: 1663:sustainability 1646: 1643: 1618:Main article: 1615: 1612: 1565:Main article: 1552: 1549: 1503: 1500: 1498: 1495: 1447: 1444: 1378: 1375: 1363:mOTUs profiler 1323:Main article: 1320: 1317: 1270:Main article: 1267: 1264: 1215:Main article: 1212: 1209: 1200: 1197: 1170: 1169: 1146: 1144: 1137: 1131: 1130:Bioinformatics 1128: 1083: 1080: 1060:bioinformatics 1055: 1052: 1018:DNA sequencing 1016:Main article: 1005: 1002: 986:pyrosequencing 936:, has led the 907:bacteriophages 846:Norman R. Pace 842:molecular work 794: 793: 791: 790: 783: 776: 768: 765: 764: 763: 762: 746: 745: 743: 742: 737: 732: 727: 721: 715: 713: 712: 707: 701: 699: 698: 697: 696: 685: 683: 682: 676: 674: 673: 672: 671: 660: 658: 657: 656: 655: 643: 640: 639: 635: 634: 632: 631: 630: 629: 624: 616: 611: 606: 601: 595: 592: 591: 587: 586: 573: 565: 564: 558: 557: 550: 547: 518: 515: 474:and microbial 372: 371: 369: 368: 361: 354: 346: 343: 342: 341: 340: 324: 323: 320: 319: 313: 310: 309: 306: 305: 300: 299: 294: 289: 284: 279: 277:Immunogenetics 274: 269: 264: 259: 253: 252: 251: 248: 247: 244: 243: 240: 239: 232: 231: 226: 209: 204: 202:DNA sequencing 199: 193: 190: 189: 186: 185: 182: 181: 176: 171: 166: 161: 151: 146: 140: 137: 136: 133: 132: 129: 128: 123: 114: 113: 108: 103: 98: 93: 88: 83: 78: 73: 68: 62: 61: 60: 58:Key components 57: 56: 53: 52: 44: 43: 37: 36: 26: 9: 6: 4: 3: 2: 7911: 7900: 7897: 7895: 7892: 7890: 7887: 7885: 7882: 7880: 7877: 7876: 7874: 7864: 7854: 7852: 7847: 7842: 7841: 7838: 7825: 7824: 7815: 7813: 7812: 7803: 7802: 7799: 7792: 7789: 7786: 7783: 7780: 7777: 7774: 7771: 7770: 7768: 7766:Organizations 7764: 7758: 7755: 7753: 7750: 7748: 7745: 7743: 7740: 7738: 7735: 7733: 7730: 7728: 7725: 7723: 7720: 7719: 7717: 7713: 7707: 7704: 7702: 7699: 7697: 7694: 7690: 7687: 7686: 7685: 7682: 7681: 7679: 7677: 7673: 7667: 7664: 7662: 7659: 7657: 7654: 7652: 7649: 7647: 7644: 7642: 7639: 7637: 7636:Nutrigenomics 7634: 7632: 7629: 7627: 7624: 7622: 7619: 7617: 7614: 7612: 7609: 7605: 7602: 7601: 7600: 7597: 7593: 7590: 7589: 7588: 7585: 7583: 7582:Chemogenomics 7580: 7578: 7575: 7573: 7570: 7569: 7567: 7565: 7561: 7555: 7552: 7550: 7548: 7544: 7542: 7539: 7537: 7534: 7532: 7529: 7525: 7522: 7521: 7520: 7517: 7513: 7510: 7509: 7508: 7505: 7503: 7500: 7498: 7495: 7493: 7490: 7488: 7485: 7484: 7482: 7478: 7474: 7467: 7462: 7460: 7455: 7453: 7448: 7447: 7444: 7437: 7434: 7431: 7430: 7425: 7422: 7421: 7409: 7405: 7400: 7395: 7391: 7387: 7383: 7376: 7368: 7364: 7359: 7354: 7350: 7346: 7342: 7338: 7334: 7330: 7326: 7319: 7311: 7307: 7302: 7297: 7292: 7287: 7283: 7279: 7275: 7268: 7260: 7256: 7251: 7246: 7242: 7238: 7234: 7230: 7226: 7219: 7211: 7207: 7202: 7197: 7193: 7189: 7185: 7181: 7177: 7173: 7169: 7162: 7154: 7150: 7145: 7140: 7136: 7132: 7127: 7122: 7118: 7114: 7110: 7103: 7095: 7091: 7087: 7083: 7079: 7075: 7071: 7067: 7063: 7059: 7055: 7048: 7040: 7036: 7031: 7026: 7021: 7016: 7012: 7008: 7004: 7000: 6996: 6988: 6980: 6976: 6971: 6966: 6962: 6958: 6954: 6950: 6946: 6942: 6938: 6931: 6923: 6919: 6914: 6909: 6905: 6901: 6897: 6893: 6889: 6885: 6881: 6877: 6873: 6865: 6863: 6854: 6848: 6844: 6837: 6822: 6818: 6811: 6803: 6797: 6793: 6786: 6778: 6774: 6770: 6766: 6761: 6756: 6752: 6748: 6744: 6737: 6729: 6725: 6720: 6715: 6710: 6705: 6701: 6697: 6693: 6686: 6670: 6666: 6660: 6652: 6648: 6643: 6638: 6633: 6628: 6624: 6620: 6617:(5): e36478. 6616: 6612: 6608: 6601: 6593: 6589: 6584: 6579: 6575: 6571: 6567: 6563: 6559: 6552: 6544: 6540: 6535: 6530: 6526: 6522: 6518: 6514: 6510: 6503: 6495: 6491: 6486: 6481: 6476: 6471: 6467: 6463: 6459: 6452: 6444: 6440: 6435: 6430: 6426: 6422: 6418: 6414: 6410: 6403: 6401: 6399: 6379: 6375: 6371: 6367: 6363: 6360:(3): 303–10. 6359: 6355: 6348: 6341: 6339: 6330: 6324: 6320: 6313: 6305: 6301: 6296: 6291: 6287: 6283: 6280:(2): 265–76. 6279: 6275: 6271: 6264: 6256: 6252: 6247: 6242: 6237: 6232: 6228: 6224: 6223:PLOS Genetics 6220: 6213: 6205: 6201: 6196: 6191: 6186: 6181: 6177: 6173: 6170:(1): e14519. 6169: 6165: 6161: 6154: 6146: 6142: 6137: 6132: 6127: 6122: 6118: 6114: 6110: 6103: 6095: 6091: 6086: 6081: 6076: 6071: 6067: 6063: 6059: 6052: 6044: 6038: 6034: 6027: 6008: 6001: 6000: 5992: 5990: 5974: 5970: 5964: 5955: 5950: 5946: 5942: 5938: 5931: 5923: 5919: 5915: 5908: 5900: 5893: 5886: 5878: 5874: 5870: 5866: 5862: 5858: 5853: 5848: 5844: 5840: 5833: 5825: 5821: 5817: 5813: 5809: 5805: 5800: 5795: 5791: 5787: 5780: 5772: 5768: 5763: 5758: 5754: 5750: 5746: 5742: 5738: 5731: 5723: 5719: 5715: 5711: 5707: 5703: 5699: 5695: 5688: 5681: 5673: 5669: 5664: 5659: 5655: 5651: 5647: 5643: 5639: 5632: 5624: 5620: 5615: 5610: 5606: 5602: 5598: 5594: 5590: 5583: 5575: 5571: 5567: 5563: 5559: 5555: 5551: 5547: 5543: 5539: 5535: 5528: 5520: 5516: 5512: 5508: 5504: 5500: 5496: 5492: 5488: 5484: 5477: 5469: 5465: 5461: 5457: 5453: 5449: 5442: 5434: 5430: 5425: 5420: 5416: 5412: 5409:(6): 623–32. 5408: 5404: 5400: 5393: 5385: 5381: 5376: 5371: 5366: 5361: 5357: 5353: 5349: 5345: 5341: 5334: 5326: 5322: 5317: 5312: 5309:(4): 409–18. 5308: 5304: 5300: 5293: 5285: 5281: 5276: 5271: 5266: 5261: 5257: 5253: 5249: 5242: 5234: 5230: 5225: 5220: 5216: 5212: 5208: 5204: 5200: 5193: 5185: 5181: 5176: 5171: 5166: 5161: 5157: 5153: 5146: 5138: 5134: 5129: 5124: 5120: 5116: 5112: 5108: 5104: 5097: 5089: 5085: 5080: 5075: 5071: 5067: 5063: 5059: 5055: 5051: 5047: 5040: 5038: 5036: 5034: 5032: 5030: 5021: 5017: 5012: 5007: 5003: 4999: 4996:(4): 169–81. 4995: 4991: 4987: 4980: 4971: 4966: 4959: 4951: 4947: 4942: 4937: 4932: 4927: 4923: 4919: 4915: 4908: 4900: 4896: 4891: 4886: 4881: 4876: 4872: 4868: 4864: 4857: 4849: 4845: 4840: 4835: 4831: 4827: 4823: 4819: 4815: 4808: 4800: 4796: 4791: 4786: 4781: 4776: 4772: 4768: 4764: 4757: 4755: 4746: 4742: 4737: 4732: 4728: 4724: 4720: 4716: 4712: 4705: 4697: 4693: 4688: 4683: 4678: 4673: 4669: 4665: 4661: 4654: 4646: 4642: 4637: 4632: 4628: 4624: 4620: 4616: 4612: 4605: 4597: 4593: 4588: 4583: 4578: 4573: 4569: 4565: 4561: 4554: 4546: 4542: 4537: 4532: 4527: 4522: 4518: 4514: 4510: 4503: 4495: 4491: 4486: 4481: 4477: 4473: 4469: 4465: 4461: 4457: 4453: 4446: 4444: 4435: 4431: 4427: 4423: 4419: 4415: 4411: 4407: 4400: 4392: 4388: 4383: 4378: 4374: 4370: 4366: 4362: 4358: 4351: 4343: 4339: 4334: 4329: 4325: 4321: 4318:(3): 377–86. 4317: 4313: 4309: 4302: 4300: 4291: 4287: 4282: 4277: 4273: 4269: 4265: 4261: 4257: 4250: 4242: 4238: 4233: 4228: 4224: 4220: 4216: 4212: 4208: 4201: 4193: 4189: 4184: 4179: 4175: 4171: 4167: 4163: 4159: 4152: 4150: 4141: 4137: 4132: 4127: 4123: 4119: 4115: 4111: 4107: 4100: 4092: 4088: 4083: 4078: 4074: 4070: 4066: 4062: 4058: 4051: 4043: 4039: 4034: 4029: 4025: 4021: 4017: 4013: 4009: 4002: 3994: 3990: 3985: 3980: 3976: 3972: 3968: 3964: 3960: 3953: 3951: 3949: 3947: 3945: 3936: 3932: 3927: 3922: 3917: 3912: 3908: 3904: 3901:(3): e17288. 3900: 3896: 3892: 3885: 3877: 3873: 3869: 3865: 3861: 3857: 3854:(4): 709–17. 3853: 3849: 3842: 3834: 3830: 3825: 3820: 3816: 3812: 3808: 3804: 3800: 3793: 3785: 3781: 3776: 3771: 3766: 3761: 3757: 3753: 3750:(2): e31386. 3749: 3745: 3741: 3734: 3726: 3722: 3717: 3712: 3708: 3704: 3700: 3696: 3692: 3685: 3677: 3673: 3669: 3663: 3659: 3655: 3651: 3650: 3642: 3640: 3638: 3636: 3634: 3632: 3630: 3621: 3617: 3612: 3607: 3603: 3599: 3595: 3591: 3587: 3580: 3578: 3566: 3562: 3557: 3552: 3548: 3544: 3540: 3536: 3532: 3528: 3524: 3517: 3509: 3505: 3501: 3497: 3493: 3489: 3485: 3481: 3477: 3473: 3466: 3464: 3455: 3451: 3446: 3441: 3436: 3431: 3427: 3423: 3419: 3412: 3404: 3400: 3395: 3390: 3386: 3382: 3379:(3): 204–12. 3378: 3374: 3370: 3363: 3355: 3351: 3346: 3341: 3337: 3333: 3329: 3325: 3321: 3317: 3313: 3306: 3297: 3292: 3288: 3284: 3280: 3274: 3266: 3262: 3258: 3254: 3250: 3246: 3242: 3238: 3231: 3223: 3219: 3214: 3209: 3204: 3199: 3195: 3191: 3188:(7): e11840. 3187: 3183: 3179: 3172: 3164: 3160: 3155: 3150: 3146: 3142: 3138: 3134: 3130: 3123: 3121: 3112: 3108: 3104: 3100: 3096: 3092: 3088: 3084: 3081:(5): 516–29. 3080: 3076: 3069: 3061: 3057: 3052: 3047: 3042: 3037: 3033: 3029: 3025: 3018: 3010: 3006: 3001: 2996: 2991: 2986: 2982: 2978: 2974: 2967: 2959: 2955: 2951: 2947: 2943: 2939: 2935: 2931: 2927: 2923: 2916: 2914: 2912: 2900: 2896: 2891: 2886: 2882: 2878: 2874: 2870: 2866: 2859: 2851: 2847: 2843: 2839: 2835: 2831: 2826: 2821: 2817: 2813: 2809: 2805: 2798: 2790: 2786: 2781: 2776: 2771: 2766: 2762: 2758: 2754: 2747: 2736: 2732: 2728: 2724: 2720: 2716: 2712: 2708: 2704: 2700: 2693: 2691: 2682: 2678: 2673: 2668: 2663: 2658: 2654: 2650: 2646: 2642: 2638: 2631: 2623: 2619: 2614: 2609: 2605: 2601: 2597: 2593: 2589: 2582: 2574: 2570: 2566: 2562: 2558: 2554: 2551:(4): 667–74. 2550: 2546: 2538: 2530: 2526: 2521: 2516: 2512: 2508: 2504: 2500: 2496: 2492: 2486: 2478: 2472: 2468: 2464: 2460: 2453: 2445: 2441: 2436: 2431: 2426: 2421: 2417: 2413: 2409: 2405: 2401: 2394: 2386: 2382: 2377: 2372: 2367: 2362: 2358: 2354: 2351:(2): 106–12. 2350: 2346: 2342: 2335: 2326: 2322: 2317: 2312: 2308: 2304: 2300: 2293: 2285: 2281: 2276: 2271: 2266: 2261: 2257: 2253: 2249: 2242: 2234: 2228: 2224: 2220: 2213: 2205: 2201: 2196: 2191: 2187: 2183: 2179: 2175: 2171: 2164: 2162: 2153: 2149: 2144: 2139: 2134: 2129: 2125: 2121: 2117: 2113: 2109: 2102: 2100: 2098: 2096: 2094: 2092: 2090: 2085: 2076: 2075:Pathogenomics 2073: 2071: 2068: 2066: 2063: 2061: 2058: 2056: 2053: 2052: 2046: 2044: 2040: 2039:hematophagous 2030: 2027: 2023: 2013: 2009: 2007: 2003: 1998: 1994: 1990: 1985: 1981: 1977: 1973: 1971: 1967: 1963: 1959: 1955: 1946: 1944: 1940: 1935: 1931: 1925: 1915: 1913: 1909: 1903: 1895: 1886: 1885:antibiotics. 1884: 1879: 1875: 1870: 1865: 1863: 1860: 1856: 1852: 1851:agrochemicals 1848: 1844: 1836:Biotechnology 1833: 1831: 1827: 1826:fungus garden 1823: 1820: 1816: 1812: 1808: 1804: 1800: 1796: 1792: 1787: 1785: 1781: 1777: 1773: 1769: 1765: 1761: 1757: 1753: 1750:contained in 1749: 1745: 1742:derived from 1741: 1737: 1732: 1722: 1720: 1716: 1712: 1708: 1704: 1701: 1697: 1693: 1689: 1685: 1680: 1670: 1668: 1664: 1660: 1656: 1652: 1642: 1640: 1639:giant viruses 1636: 1631: 1627: 1621: 1611: 1609: 1605: 1601: 1600: 1595: 1591: 1587: 1583: 1579: 1575: 1568: 1562: 1558: 1557:Transcriptome 1548: 1546: 1541: 1537: 1533: 1529: 1525: 1521: 1517: 1513: 1509: 1497:Data analysis 1494: 1492: 1486: 1484: 1480: 1474: 1471: 1467: 1463: 1458: 1454: 1443: 1439: 1435: 1433: 1429: 1425: 1420: 1418: 1414: 1410: 1406: 1402: 1398: 1392: 1389: 1388:replicability 1384: 1374: 1372: 1368: 1364: 1360: 1356: 1352: 1348: 1344: 1340: 1336: 1332: 1326: 1316: 1313: 1309: 1305: 1301: 1300: 1295: 1291: 1288:, usually by 1287: 1283: 1279: 1273: 1263: 1261: 1257: 1253: 1249: 1245: 1241: 1236: 1234: 1229: 1224: 1218: 1208: 1206: 1196: 1193: 1189: 1185: 1176: 1166: 1163:February 2022 1156: 1150: 1147:This section 1145: 1141: 1136: 1135: 1127: 1125: 1121: 1117: 1112: 1110: 1106: 1102: 1098: 1094: 1090: 1079: 1077: 1073: 1069: 1065: 1061: 1051: 1049: 1045: 1041: 1037: 1033: 1029: 1025: 1019: 1010: 1001: 999: 995: 994:Forest Rohwer 991: 988:developed by 987: 983: 979: 974: 972: 967: 963: 962:Mediterranean 959: 955: 951: 947: 943: 939: 935: 931: 926: 924: 920: 916: 912: 908: 904: 900: 899:viral species 896: 892: 891:Forest Rohwer 888: 887:Mya Breitbart 883: 881: 876: 875:Edward DeLong 872: 868: 864: 860: 856: 851: 847: 843: 838: 836: 832: 828: 824: 820: 816: 813: 809: 805: 801: 798:Conventional 789: 784: 782: 777: 775: 770: 769: 767: 766: 760: 750: 749: 748: 747: 741: 738: 736: 733: 731: 728: 725: 722: 720: 717: 716: 711: 708: 706: 703: 702: 695: 692: 691: 690: 689:Amplification 687: 686: 681: 678: 677: 670: 667: 666: 665: 662: 661: 654: 651: 650: 648: 645: 644: 642: 641: 637: 636: 628: 625: 623: 620: 619: 617: 615: 612: 610: 607: 605: 602: 600: 597: 596: 594: 593: 589: 588: 582: 581:Metabarcoding 578: 577:DNA barcoding 571: 567: 566: 563: 562:DNA barcoding 560: 559: 555: 554: 546: 544: 540: 536: 532: 528: 524: 523:Jo Handelsman 514: 512: 508: 504: 498: 496: 492: 488: 485: 481: 477: 473: 468: 466: 462: 458: 454: 450: 446: 445:environmental 442: 438: 431: 427: 423: 419: 415: 411: 407: 403: 399: 395: 391: 387: 383: 378: 367: 362: 360: 355: 353: 348: 347: 345: 344: 338: 328: 327: 326: 325: 318: 315: 314: 308: 307: 298: 295: 293: 290: 288: 285: 283: 280: 278: 275: 273: 270: 268: 265: 263: 260: 258: 255: 254: 246: 245: 238: 235: 234: 230: 227: 223: 214: 210: 208: 205: 203: 200: 198: 195: 194: 188: 187: 180: 177: 175: 172: 170: 167: 165: 162: 159: 155: 152: 150: 147: 145: 142: 141: 135: 134: 127: 124: 122: 119: 118: 112: 109: 107: 104: 102: 99: 97: 94: 92: 89: 87: 84: 82: 79: 77: 74: 72: 69: 67: 64: 63: 55: 54: 50: 46: 45: 42: 39: 38: 34: 33: 30: 19: 7879:Metagenomics 7821: 7809: 7631:Microbiomics 7626:Metabolomics 7587:Connectomics 7546: 7519:Metagenomics 7518: 7427: 7389: 7385: 7375: 7335:(1): 19398. 7332: 7328: 7318: 7281: 7277: 7267: 7232: 7228: 7218: 7175: 7171: 7161: 7116: 7112: 7102: 7061: 7057: 7047: 7002: 6998: 6987: 6944: 6940: 6930: 6879: 6875: 6842: 6836: 6824:. Retrieved 6820: 6810: 6791: 6785: 6750: 6746: 6736: 6699: 6695: 6685: 6673:. Retrieved 6668: 6659: 6614: 6610: 6600: 6565: 6561: 6551: 6516: 6512: 6502: 6465: 6461: 6451: 6416: 6412: 6385:. Retrieved 6378:the original 6357: 6353: 6318: 6312: 6277: 6273: 6263: 6226: 6222: 6212: 6167: 6163: 6153: 6116: 6112: 6102: 6065: 6061: 6051: 6032: 6026: 6014:. Retrieved 6007:the original 5998: 5976:. Retrieved 5972: 5963: 5944: 5940: 5930: 5922:the original 5917: 5907: 5898: 5885: 5842: 5838: 5832: 5792:(3): 721–4. 5789: 5785: 5779: 5744: 5740: 5730: 5697: 5693: 5680: 5645: 5641: 5631: 5596: 5592: 5582: 5541: 5537: 5527: 5486: 5482: 5476: 5454:(4): 541–6. 5451: 5447: 5441: 5406: 5402: 5392: 5347: 5343: 5333: 5306: 5302: 5292: 5255: 5251: 5241: 5206: 5202: 5192: 5155: 5145: 5110: 5106: 5096: 5053: 5049: 4993: 4990:DNA Research 4989: 4979: 4958: 4921: 4918:BMC Genomics 4917: 4907: 4870: 4866: 4856: 4821: 4817: 4807: 4770: 4766: 4718: 4714: 4704: 4667: 4663: 4653: 4618: 4614: 4604: 4567: 4563: 4553: 4516: 4513:BMC Genomics 4512: 4502: 4459: 4455: 4409: 4405: 4399: 4367:(8): 811–4. 4364: 4360: 4350: 4315: 4311: 4263: 4259: 4249: 4217:(12): e132. 4214: 4210: 4200: 4165: 4161: 4113: 4109: 4099: 4067:(5): 821–9. 4064: 4060: 4050: 4018:(20): e155. 4015: 4011: 4001: 3966: 3962: 3898: 3894: 3884: 3851: 3847: 3841: 3809:(7): 830–6. 3806: 3802: 3792: 3747: 3743: 3733: 3698: 3694: 3684: 3648: 3593: 3589: 3530: 3526: 3516: 3475: 3471: 3425: 3421: 3411: 3376: 3372: 3362: 3319: 3315: 3305: 3286: 3282: 3273: 3240: 3236: 3230: 3185: 3181: 3171: 3139:(666): 666. 3136: 3132: 3078: 3074: 3068: 3031: 3027: 3017: 2980: 2977:BMC Genomics 2976: 2966: 2925: 2921: 2872: 2868: 2858: 2807: 2803: 2797: 2760: 2756: 2746: 2702: 2698: 2644: 2640: 2630: 2598:(3): 591–9. 2595: 2591: 2581: 2548: 2544: 2537: 2502: 2498: 2485: 2458: 2452: 2407: 2403: 2393: 2348: 2344: 2334: 2306: 2302: 2292: 2255: 2252:PLOS Biology 2251: 2241: 2218: 2212: 2177: 2173: 2115: 2111: 2036: 2022:encephalitis 2019: 2010: 1986: 1982: 1978: 1974: 1952: 1927: 1904: 1900: 1866: 1839: 1824:such as the 1788: 1768:fermentation 1734: 1676: 1648: 1645:Applications 1623: 1597: 1577: 1570: 1545:metabolomics 1516:methanogenic 1505: 1487: 1482: 1475: 1469: 1449: 1440: 1436: 1421: 1393: 1380: 1328: 1311: 1297: 1275: 1237: 1220: 1202: 1181: 1160: 1148: 1113: 1085: 1074:them into a 1072:reconstructs 1068:human genome 1058:Advances in 1057: 1021: 975: 942:Sargasso Sea 930:Craig Venter 927: 884: 839: 797: 664:Metagenomics 663: 539:Lior Pachter 520: 499: 472:microbiology 469: 465:microbiomics 464: 460: 456: 452: 437:Metagenomics 436: 435: 425: 413: 405: 397: 393: 385: 297:Quantitative 267:Cytogenetics 262:Conservation 144:Introduction 29: 7599:Epigenomics 7531:Pangenomics 7284:(8): 1653. 7178:(1): 4690. 6826:29 December 6016:30 December 5978:30 December 5747:(1): 11–9. 4462:(1): 1014. 3243:(1): 16–8. 2043:arboviruses 1756:switchgrass 1673:Agriculture 1659:agriculture 1655:engineering 1543:tool (with 1536:microarrays 1528:Synergistia 1508:bioreactors 831:cultivation 457:ecogenomics 400:), and are 7873:Categories 7684:Proteomics 7621:Lipidomics 7616:Immunomics 7064:(8): 447. 6753:: e78756. 6675:10 October 6387:20 January 5947:(4): 252. 5852:1503.05575 5209:(7): e86. 4924:(1): 236. 3322:(1): 870. 2491:Schmidt TM 2258:(3): e82. 2081:References 1934:ecosystems 1930:pollutants 1822:herbivores 1811:convergent 1778:including 1705:and other 1604:microarray 1586:expression 1582:regulation 1540:proteomics 1520:syntrophic 1453:GC-content 1205:eukaryotic 1192:microbiome 1024:base pairs 1004:Sequencing 800:sequencing 730:Healthcare 531:Jon Clardy 449:sequencing 292:Population 272:Ecological 197:Geneticist 111:Amino acid 91:Nucleotide 66:Chromosome 18:Metagenome 7611:Glycomics 7392:: 79–84. 7135:1471-0064 7094:248739527 7078:1740-1534 6904:1476-4687 6777:248041252 6769:2534-9708 5799:1410.1278 4814:"GenBank" 4570:: e3138. 3701:: 75–88. 2820:CiteSeerX 1883:malacidin 1843:commodity 1799:screening 1776:bioenergy 1748:cellulose 1715:livestock 1700:sequester 1522:species ( 1512:syntrophy 1470:community 1419:project. 1351:MetaPhlAn 1312:ab initio 1299:ab initio 1278:pipelines 1188:gigabases 1155:talk page 1036:libraries 885:In 2002, 882:samples. 819:conserved 812:ribosomal 599:Microbial 517:Etymology 402:sequenced 390:extracted 287:Molecular 282:Microbial 257:Classical 158:molecular 154:Evolution 7889:Genomics 7863:Medicine 7823:Category 7549:genomics 7473:Genomics 7408:28855093 7367:31852942 7310:34442732 7259:32878948 7210:29549363 7153:30918369 7086:35546350 7039:22719234 6979:20203603 6922:20203603 6728:33971086 6651:22606263 6611:PLOS ONE 6592:21407210 6543:29434326 6494:21545702 6468:(1): 9. 6443:21076656 6374:12849784 6304:19760178 6255:20885794 6204:21297863 6164:PLOS ONE 6145:19450243 6094:26052316 5901:: 21–26. 5869:28247094 5824:13145926 5816:26666442 5771:19942437 5714:28749930 5672:30407573 5623:27799466 5566:27533034 5511:16915287 5468:21592777 5433:19897353 5384:21368115 5325:23978768 5303:Genomics 5284:23282463 5233:23408855 5184:22373355 5137:19302541 5088:21169428 5020:17916580 4950:25879410 4899:22574964 4848:23193287 4799:21342551 4745:22086953 4696:18803844 4645:22135293 4596:28367376 4545:21989143 4494:30833550 4426:24141494 4391:22688413 4342:17255551 4290:19657372 4241:20403810 4192:21690186 4140:24855317 4091:18349386 4042:22821567 3993:19052320 3935:21408061 3895:PLOS ONE 3876:25857874 3868:21857117 3833:23376350 3784:22384016 3744:PLOS ONE 3725:25983555 3676:21678629 3620:24076764 3565:20203603 3508:36572885 3500:21273488 3454:32706331 3403:27383682 3354:29491419 3257:18165802 3222:20676378 3182:PLOS ONE 3163:23670539 3103:11233160 3060:22587947 3034:(1): 3. 3009:16549033 2958:11238470 2950:16368896 2899:21048761 2842:15001713 2789:11864374 2727:14961025 2681:12384570 2573:31384119 2385:16110337 2284:17355177 2152:20195499 2049:See also 1784:hydrogen 1754:stalks, 1736:Biofuels 1651:medicine 1457:16S rRNA 1399:and the 1383:metadata 1304:GeneMark 1282:homology 1223:coverage 1211:Assembly 1101:Illumina 971:plankton 950:bacteria 913:and the 835:archaeal 808:cultured 759:Category 618:Aquatic 491:16S rRNA 487:cultures 480:genomics 337:Category 222:template 213:Genomics 191:Research 96:Mutation 86:Heredity 41:Genetics 7851:Biology 7837:Portals 7572:Biochip 7358:6920425 7337:Bibcode 7329:Sci Rep 7301:8398489 7250:7587107 7201:5856816 7180:Bibcode 7172:Sci Rep 7144:6858796 7030:3374609 7007:Bibcode 6970:3779803 6949:Bibcode 6913:3779803 6884:Bibcode 6719:8518049 6669:NPR.org 6642:3350522 6619:Bibcode 6583:3094067 6568:: 473. 6534:5874163 6485:3113934 6434:2976544 6295:2773367 6246:2944797 6195:3027613 6172:Bibcode 6136:2694162 6085:4440916 6068:: 486. 5918:Microbe 5877:1925728 5762:3293453 5722:2127494 5663:6323928 5614:5210529 5574:4466854 5546:Bibcode 5519:4380804 5491:Bibcode 5424:2790021 5375:3053989 5352:Bibcode 5275:3526429 5224:3627586 5175:3278849 5115:Bibcode 5079:3067235 5058:Bibcode 5011:2533590 4965:bioRxiv 4941:4428112 4890:3428669 4839:3531190 4790:3044276 4736:3245048 4687:2563014 4670:: 386. 4636:3245063 4587:5372838 4536:3194235 4485:6399450 4464:Bibcode 4434:7728395 4382:3443552 4333:1800929 4268:Bibcode 4232:2896542 4183:3166839 4131:4455782 4082:2336801 4033:3488206 3984:2593568 3926:3052304 3903:Bibcode 3824:3605598 3775:3285633 3752:Bibcode 3716:4426941 3611:4010126 3556:3779803 3535:Bibcode 3480:Bibcode 3472:Science 3445:7641418 3394:5017796 3345:5830445 3324:Bibcode 3265:1465786 3213:2911387 3190:Bibcode 3154:4039370 3111:8267748 3083:Bibcode 3051:3351745 3000:1483832 2930:Bibcode 2922:Science 2877:Bibcode 2850:1454587 2812:Bibcode 2804:Science 2735:4420754 2707:Bibcode 2649:Bibcode 2622:8550487 2565:7546604 2529:2066334 2444:2413450 2412:Bibcode 2376:1185649 2353:Bibcode 2325:9818143 2275:1821061 2204:9733676 2143:2829047 2120:Bibcode 2055:Binning 1987:In the 1889:Ecology 1828:of the 1803:enzymes 1795:enzymes 1780:methane 1772:ethanol 1744:biomass 1731:Biofuel 1725:Biofuel 1719:farming 1667:ecology 1630:18S RNA 1626:16S RNA 1614:Viruses 1599:in situ 1532:methane 1405:MG-RAST 1386:ensure 1355:AMPHORA 1335:Binning 1308:GLIMMER 1252:genomes 1233:contigs 1044:vectors 1028:samples 946:species 923:archaea 871:grasses 855:cloning 827:species 724:Chimera 669:viruses 590:By taxa 574: 549:History 507:shotgun 441:genetic 410:cloning 149:History 121:Outline 7480:Fields 7406: 7365: 7355: 7308: 7298: 7257: 7247: 7235:(11). 7208: 7198: 7151: 7141: 7133: 7092: 7084: 7076: 7037: 7027: 6977: 6967: 6941:Nature 6920: 6910: 6902: 6876:Nature 6849: 6798: 6775: 6767: 6726: 6716: 6649: 6639: 6590: 6580: 6541: 6531: 6492: 6482: 6441: 6431: 6372: 6325: 6302: 6292: 6253: 6243: 6202: 6192: 6143: 6133: 6119:: 10. 6092: 6082: 6039: 5875: 5867: 5822: 5814: 5769: 5759: 5720: 5712: 5670: 5660: 5621: 5611: 5572: 5564: 5538:Nature 5517: 5509: 5483:Nature 5466: 5431: 5421: 5382: 5372: 5323: 5282: 5272: 5231: 5221: 5182: 5172: 5135: 5086: 5076: 5018: 5008: 4967: 4948: 4938: 4897: 4887: 4873:: 92. 4846: 4836: 4797: 4787: 4743: 4733: 4694: 4684: 4643: 4633: 4594: 4584: 4543: 4533: 4492: 4482: 4432: 4424: 4389: 4379: 4340: 4330: 4288: 4239: 4229: 4190: 4180: 4138: 4128: 4089: 4079: 4040: 4030: 3991: 3981: 3933: 3923: 3874: 3866: 3831: 3821: 3782: 3772: 3723: 3713: 3674: 3664: 3618: 3608: 3563: 3553: 3527:Nature 3506: 3498: 3452: 3442: 3401: 3391: 3352: 3342: 3263: 3255: 3220: 3210: 3161: 3151: 3109: 3101: 3058: 3048: 3007: 2997: 2983:: 57. 2956: 2948: 2897: 2869:Nature 2848: 2840: 2822: 2787: 2780:139013 2777: 2733: 2725: 2699:Nature 2679: 2672:137870 2669: 2620: 2613:177699 2610: 2571: 2563: 2527: 2520:208098 2517: 2473: 2442: 2435:391288 2432: 2383: 2373: 2323: 2282: 2272: 2229: 2202: 2195:107498 2192: 2150: 2140: 1958:health 1819:insect 1815:biogas 1764:sugars 1707:metals 1248:Celera 1099:, the 964:, and 958:Baltic 880:marine 757: 609:Pollen 604:Fungal 584: 535:genome 484:clonal 388:) are 335: 249:Fields 106:Allele 81:Genome 7787:(USA) 7547:Socio 7090:S2CID 6773:S2CID 6381:(PDF) 6350:(PDF) 6010:(PDF) 6003:(PDF) 5895:(PDF) 5873:S2CID 5847:arXiv 5820:S2CID 5794:arXiv 5718:S2CID 5690:(PDF) 5570:S2CID 5515:S2CID 4564:PeerJ 4430:S2CID 3872:S2CID 3504:S2CID 3428:(8). 3261:S2CID 3107:S2CID 2954:S2CID 2846:S2CID 2731:S2CID 2569:S2CID 1740:fuels 1711:crops 1679:soils 1576:(the 1424:MEGAN 1367:SLIMM 1359:mOTUs 1343:MEGAN 1339:BLAST 1294:MEGAN 1290:BLAST 1244:Phrap 1184:rumen 966:Black 638:Other 614:Algae 509:" or 126:Index 7811:List 7793:(UK) 7781:(EU) 7775:(JP) 7404:PMID 7363:PMID 7306:PMID 7255:PMID 7206:PMID 7149:PMID 7131:ISSN 7082:PMID 7074:ISSN 7035:PMID 6975:PMID 6918:PMID 6900:ISSN 6847:ISBN 6828:2011 6796:ISBN 6765:ISSN 6724:PMID 6677:2014 6647:PMID 6588:PMID 6539:PMID 6490:PMID 6439:PMID 6389:2012 6370:PMID 6323:ISBN 6300:PMID 6251:PMID 6200:PMID 6141:PMID 6090:PMID 6037:ISBN 6018:2011 5980:2011 5865:PMID 5812:PMID 5767:PMID 5710:PMID 5668:PMID 5619:PMID 5562:PMID 5507:PMID 5464:PMID 5429:PMID 5380:PMID 5321:PMID 5280:PMID 5229:PMID 5180:PMID 5133:PMID 5084:PMID 5016:PMID 4946:PMID 4895:PMID 4844:PMID 4795:PMID 4741:PMID 4692:PMID 4641:PMID 4592:PMID 4541:PMID 4490:PMID 4422:PMID 4387:PMID 4338:PMID 4286:PMID 4237:PMID 4188:PMID 4136:PMID 4087:PMID 4038:PMID 3989:PMID 3931:PMID 3864:PMID 3829:PMID 3780:PMID 3721:PMID 3672:PMID 3662:ISBN 3616:PMID 3561:PMID 3496:PMID 3450:PMID 3399:PMID 3350:PMID 3253:PMID 3218:PMID 3159:PMID 3099:PMID 3056:PMID 3005:PMID 2946:PMID 2895:PMID 2838:PMID 2785:PMID 2723:PMID 2677:PMID 2618:PMID 2561:PMID 2525:PMID 2471:ISBN 2440:PMID 2381:PMID 2321:PMID 2280:PMID 2227:ISBN 2200:PMID 2148:PMID 1910:and 1853:and 1845:and 1789:The 1782:and 1752:corn 1738:are 1713:and 1703:iron 1677:The 1665:and 1584:and 1574:mRNA 1559:and 1526:and 1466:KEGG 1432:KEGG 1428:SEED 1353:and 1306:and 1046:for 823:rRNA 627:fish 478:and 7426:at 7394:doi 7390:249 7353:PMC 7345:doi 7296:PMC 7286:doi 7245:PMC 7237:doi 7196:PMC 7188:doi 7139:PMC 7121:doi 7066:doi 7025:PMC 7015:doi 6965:PMC 6957:doi 6945:464 6908:PMC 6892:doi 6880:464 6755:doi 6714:PMC 6704:doi 6637:PMC 6627:doi 6578:PMC 6570:doi 6529:PMC 6521:doi 6480:PMC 6470:doi 6429:PMC 6421:doi 6362:doi 6290:PMC 6282:doi 6241:PMC 6231:doi 6190:PMC 6180:doi 6131:PMC 6121:doi 6080:PMC 6070:doi 5949:doi 5857:doi 5843:162 5804:doi 5790:161 5757:PMC 5749:doi 5702:doi 5658:PMC 5650:doi 5609:PMC 5601:doi 5554:doi 5542:536 5499:doi 5487:442 5456:doi 5419:PMC 5411:doi 5370:PMC 5360:doi 5348:108 5311:doi 5307:102 5270:PMC 5260:doi 5219:PMC 5211:doi 5170:PMC 5160:doi 5123:doi 5074:PMC 5066:doi 5006:PMC 4998:doi 4936:PMC 4926:doi 4885:PMC 4875:doi 4834:PMC 4826:doi 4785:PMC 4775:doi 4731:PMC 4723:doi 4682:PMC 4672:doi 4631:PMC 4623:doi 4582:PMC 4572:doi 4531:PMC 4521:doi 4480:PMC 4472:doi 4414:doi 4377:PMC 4369:doi 4328:PMC 4320:doi 4276:doi 4227:PMC 4219:doi 4178:PMC 4170:doi 4126:PMC 4118:doi 4077:PMC 4069:doi 4028:PMC 4020:doi 3979:PMC 3971:doi 3921:PMC 3911:doi 3856:doi 3819:PMC 3811:doi 3770:PMC 3760:doi 3711:PMC 3703:doi 3654:doi 3606:PMC 3598:doi 3551:PMC 3543:doi 3531:464 3488:doi 3476:331 3440:PMC 3430:doi 3389:PMC 3381:doi 3340:PMC 3332:doi 3291:doi 3245:doi 3208:PMC 3198:doi 3149:PMC 3141:doi 3091:doi 3046:PMC 3036:doi 2995:PMC 2985:doi 2938:doi 2926:311 2885:doi 2873:468 2830:doi 2808:304 2775:PMC 2765:doi 2715:doi 2703:428 2667:PMC 2657:doi 2608:PMC 2600:doi 2596:178 2553:doi 2515:PMC 2507:doi 2503:173 2463:doi 2430:PMC 2420:doi 2371:PMC 2361:doi 2311:doi 2270:PMC 2260:doi 2190:PMC 2182:doi 2178:180 2138:PMC 2128:doi 1941:or 1932:on 1876:to 1801:of 1538:or 1491:GUI 1464:or 1462:COG 1430:or 1246:or 1038:in 863:PCR 850:PCR 815:RNA 804:DNA 694:PCR 511:PCR 463:or 382:DNA 76:RNA 71:DNA 7875:: 7402:. 7388:. 7384:. 7361:. 7351:. 7343:. 7331:. 7327:. 7304:. 7294:. 7280:. 7276:. 7253:. 7243:. 7233:58 7231:. 7227:. 7204:. 7194:. 7186:. 7174:. 7170:. 7147:. 7137:. 7129:. 7117:20 7115:. 7111:. 7088:. 7080:. 7072:. 7062:20 7060:. 7056:. 7033:. 7023:. 7013:. 7001:. 6997:. 6973:. 6963:. 6955:. 6943:. 6939:. 6916:. 6906:. 6898:. 6890:. 6878:. 6874:. 6861:^ 6819:. 6771:. 6763:. 6749:. 6745:. 6722:. 6712:. 6700:21 6698:. 6694:. 6667:. 6645:. 6635:. 6625:. 6613:. 6609:. 6586:. 6576:. 6564:. 6560:. 6537:. 6527:. 6515:. 6511:. 6488:. 6478:. 6464:. 6460:. 6437:. 6427:. 6417:42 6415:. 6411:. 6397:^ 6368:. 6358:14 6356:. 6352:. 6337:^ 6298:. 6288:. 6278:85 6276:. 6272:. 6249:. 6239:. 6225:. 6221:. 6198:. 6188:. 6178:. 6166:. 6162:. 6139:. 6129:. 6115:. 6111:. 6088:. 6078:. 6064:. 6060:. 5988:^ 5971:. 5943:. 5939:. 5916:. 5897:. 5871:. 5863:. 5855:. 5841:. 5818:. 5810:. 5802:. 5788:. 5765:. 5755:. 5745:18 5743:. 5739:. 5716:. 5708:. 5698:12 5696:. 5692:. 5666:. 5656:. 5646:47 5644:. 5640:. 5617:. 5607:. 5597:45 5595:. 5591:. 5568:. 5560:. 5552:. 5540:. 5536:. 5513:. 5505:. 5497:. 5485:. 5462:. 5452:22 5450:. 5427:. 5417:. 5407:20 5405:. 5401:. 5378:. 5368:. 5358:. 5346:. 5342:. 5319:. 5305:. 5301:. 5278:. 5268:. 5256:13 5254:. 5250:. 5227:. 5217:. 5207:41 5205:. 5201:. 5178:. 5168:. 5154:. 5131:. 5121:. 5111:11 5109:. 5105:. 5082:. 5072:. 5064:. 5054:77 5052:. 5048:. 5028:^ 5014:. 5004:. 4994:14 4992:. 4988:. 4944:. 4934:. 4922:16 4920:. 4916:. 4893:. 4883:. 4871:13 4869:. 4865:. 4842:. 4832:. 4822:41 4820:. 4816:. 4793:. 4783:. 4771:12 4769:. 4765:. 4753:^ 4739:. 4729:. 4719:40 4717:. 4713:. 4690:. 4680:. 4666:. 4662:. 4639:. 4629:. 4619:40 4617:. 4613:. 4590:. 4580:. 4566:. 4562:. 4539:. 4529:. 4517:12 4515:. 4511:. 4488:. 4478:. 4470:. 4460:10 4458:. 4454:. 4442:^ 4428:. 4420:. 4410:10 4408:. 4385:. 4375:. 4363:. 4359:. 4336:. 4326:. 4316:17 4314:. 4310:. 4298:^ 4284:. 4274:. 4262:. 4258:. 4235:. 4225:. 4215:38 4213:. 4209:. 4186:. 4176:. 4166:21 4164:. 4160:. 4148:^ 4134:. 4124:. 4112:. 4110:G3 4108:. 4085:. 4075:. 4065:18 4063:. 4059:. 4036:. 4026:. 4016:40 4014:. 4010:. 3987:. 3977:. 3967:72 3965:. 3961:. 3943:^ 3929:. 3919:. 3909:. 3897:. 3893:. 3870:. 3862:. 3852:36 3850:. 3827:. 3817:. 3807:29 3805:. 3801:. 3778:. 3768:. 3758:. 3746:. 3742:. 3719:. 3709:. 3697:. 3693:. 3670:. 3660:. 3628:^ 3614:. 3604:. 3594:10 3592:. 3588:. 3576:^ 3559:. 3549:. 3541:. 3529:. 3525:. 3502:. 3494:. 3486:. 3474:. 3462:^ 3448:. 3438:. 3424:. 3420:. 3397:. 3387:. 3377:31 3375:. 3371:. 3348:. 3338:. 3330:. 3318:. 3314:. 3285:. 3281:. 3259:. 3251:. 3239:. 3216:. 3206:. 3196:. 3184:. 3180:. 3157:. 3147:. 3135:. 3131:. 3119:^ 3105:. 3097:. 3089:. 3077:. 3054:. 3044:. 3030:. 3026:. 3003:. 2993:. 2979:. 2975:. 2952:. 2944:. 2936:. 2924:. 2910:^ 2893:. 2883:. 2871:. 2867:. 2844:. 2836:. 2828:. 2818:. 2806:. 2783:. 2773:. 2759:. 2755:. 2729:. 2721:. 2713:. 2701:. 2689:^ 2675:. 2665:. 2655:. 2645:99 2643:. 2639:. 2616:. 2606:. 2594:. 2590:. 2567:. 2559:. 2549:43 2547:. 2523:. 2513:. 2501:. 2497:. 2469:. 2438:. 2428:. 2418:. 2408:82 2406:. 2402:. 2379:. 2369:. 2359:. 2347:. 2343:. 2319:. 2305:. 2301:. 2278:. 2268:. 2254:. 2250:. 2225:. 2221:. 2198:. 2188:. 2176:. 2172:. 2160:^ 2146:. 2136:. 2126:. 2114:. 2110:. 2088:^ 2045:. 2008:. 1849:, 1832:. 1786:. 1694:, 1669:. 1661:, 1657:, 1653:, 1235:. 1050:. 1000:. 973:. 960:, 889:, 579:• 525:, 467:. 459:, 455:, 384:, 7839:: 7465:e 7458:t 7451:v 7410:. 7396:: 7369:. 7347:: 7339:: 7333:9 7312:. 7288:: 7282:9 7261:. 7239:: 7212:. 7190:: 7182:: 7176:8 7155:. 7123:: 7096:. 7068:: 7041:. 7017:: 7009:: 7003:8 6981:. 6959:: 6951:: 6924:. 6894:: 6886:: 6855:. 6830:. 6804:. 6779:. 6757:: 6751:6 6730:. 6706:: 6679:. 6653:. 6629:: 6621:: 6615:7 6594:. 6572:: 6566:7 6545:. 6523:: 6517:3 6496:. 6472:: 6466:4 6445:. 6423:: 6391:. 6364:: 6331:. 6306:. 6284:: 6257:. 6233:: 6227:6 6206:. 6182:: 6174:: 6168:6 6147:. 6123:: 6117:2 6096:. 6072:: 6066:6 6045:. 6020:. 5982:. 5957:. 5951:: 5945:7 5879:. 5859:: 5849:: 5826:. 5806:: 5796:: 5773:. 5751:: 5724:. 5704:: 5674:. 5652:: 5625:. 5603:: 5576:. 5556:: 5548:: 5521:. 5501:: 5493:: 5470:. 5458:: 5435:. 5413:: 5386:. 5362:: 5354:: 5327:. 5313:: 5286:. 5262:: 5235:. 5213:: 5186:. 5162:: 5139:. 5125:: 5117:: 5090:. 5068:: 5060:: 5022:. 5000:: 4973:. 4952:. 4928:: 4901:. 4877:: 4850:. 4828:: 4801:. 4777:: 4747:. 4725:: 4698:. 4674:: 4668:9 4647:. 4625:: 4598:. 4574:: 4568:5 4547:. 4523:: 4496:. 4474:: 4466:: 4436:. 4416:: 4393:. 4371:: 4365:9 4344:. 4322:: 4292:. 4278:: 4270:: 4264:3 4243:. 4221:: 4194:. 4172:: 4142:. 4120:: 4114:4 4093:. 4071:: 4044:. 4022:: 3995:. 3973:: 3937:. 3913:: 3905:: 3899:6 3878:. 3858:: 3835:. 3813:: 3786:. 3762:: 3754:: 3748:7 3727:. 3705:: 3699:9 3678:. 3656:: 3622:. 3600:: 3567:. 3545:: 3537:: 3510:. 3490:: 3482:: 3456:. 3432:: 3426:6 3405:. 3383:: 3356:. 3334:: 3326:: 3320:9 3299:. 3293:: 3287:6 3267:. 3247:: 3241:5 3224:. 3200:: 3192:: 3186:5 3165:. 3143:: 3137:9 3113:. 3093:: 3085:: 3079:2 3062:. 3038:: 3032:2 3011:. 2987:: 2981:7 2960:. 2940:: 2932:: 2901:. 2887:: 2879:: 2852:. 2832:: 2814:: 2791:. 2767:: 2761:3 2737:. 2717:: 2709:: 2683:. 2659:: 2651:: 2624:. 2602:: 2575:. 2555:: 2531:. 2509:: 2479:. 2465:: 2446:. 2422:: 2414:: 2387:. 2363:: 2355:: 2349:1 2329:. 2327:. 2313:: 2307:5 2286:. 2262:: 2256:5 2235:. 2206:. 2184:: 2154:. 2130:: 2122:: 2116:6 1483:k 1165:) 1161:( 1157:. 787:e 780:t 773:v 426:F 424:( 414:D 412:( 406:E 404:( 398:B 394:A 386:C 365:e 358:t 351:v 224:) 215:( 160:) 156:( 20:)

Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.