Open Access

Complete genome sequence of the rapeseed plant-growth promoting Serratia plymuthica strain AS9

  • Saraswoti Neupane1Email author,
  • Nils Högberg1,
  • Sadhna Alström1,
  • Susan Lucas2,
  • James Han2,
  • Alla Lapidus2,
  • Jan-Fang Cheng2,
  • David Bruce2, 3,
  • Lynne Goodwin2, 3,
  • Sam Pitluck2,
  • Lin Peters2,
  • Galina Ovchinnikova2,
  • Megan Lu2, 3,
  • Cliff Han2, 3,
  • John C. Detter2, 3,
  • Roxanne Tapia2, 3,
  • Anne Fiebig5,
  • Miriam Land2, 4,
  • Loren Hauser2, 4,
  • Nikos C. Kyrpides2,
  • Natalia Ivanova2,
  • Ioanna Pagani2,
  • Hans-Peter Klenk5,
  • Tanja Woyke2 and
  • Roger D. Finlay1
Standards in Genomic Sciences20126:6010054

DOI: 10.4056/sigs.2595762

Published: 19 March 2012

Abstract

Serratia plymuthica are plant-associated, plant beneficial species belonging to the family Enterobacteriaceae. The members of the genus Serratia are ubiquitous in nature and their life style varies from endophytic to free-living. S. plymuthica AS9 is of special interest for its ability to inhibit fungal pathogens of rapeseed and to promote plant growth. The genome of S. plymuthica AS9 comprises a 5,442,880 bp long circular chromosome that consists of 4,952 protein-coding genes, 87 tRNA genes and 7 rRNA operons. This genome is part of the project entitled “Genomics of four rapeseed plant growth promoting bacteria with antagonistic effect on plant pathogens” awarded through the 2010 DOE-JGI Community Sequencing Program (CSP2010).

Keywords

motile non-sporulating mesophile Gram-negative free living plant-associated chemoorganotrophic Enterobacteriaceae CSP 2010

Introduction

The genus Serratia belongs to a group of Gammaproteobacteria, commonly found in soil, water, plants, insects and humans [1]. The genus includes antagonists of soil borne pathogens of different plant species, plant growth promoters and insect pathogens, as well as opportunistic human pathogens. The most common human pathogen in this genus is Serratia marcescens which causes nosocomial infections in humans, while other species are harmless. In agriculture, S. plymuthica is successfully used for control of many soil borne fungal pathogens of different crops (e.g. strawberry, rapeseed) [2,3], while S. proteamaculans promotes the growth of poplar trees [4].

S.plymuthica AS9 (= CCUG 61396) was isolated from field samples of rapeseed roots in Uppsala, Sweden. Our interest in S. plymuthica AS9 is attributed to its ability to stimulate rapeseed plant growth, to inhibit soil borne fungal pathogens and to increase oilseed production. Here we present a description of the complete genome sequencing of S. plymuthica AS9 and its annotation.

Classification and features

The bacterial strain AS9 was previously considered a member of the family Enterobacteriaceae [5]. Recently, comparison of 16S rRNA gene sequences with the most recent databases from GenBank using NCBI BLAST [6] under default settings showed that S. plymuthica AS9 shares 99% similarity with many Serratia species including S. plymuthica (AJ233433) and Serratiaproteamaculans (CP000826.1). When considering high-scoring segment pairs (HSPs) from the best 250 hits, the most frequent matches were with various Serratia species (17.2% with maximum identity of 97–100%) with S. plymuthica (5.2% with maximum identity of 97–99%), S. proteamaculans (4.8% with maximum identity of 97–99%), S. marcescens (4.8% with maximum identity of 96–97%) and various Rahnella species. (7% with maximum identity of 97–98%).

Figure 1 shows the phylogenetic relationship of S. plymuthica AS9 with other species within the genus Serratia in a 16S rRNA based tree. The tree shows its close relationship with the type strain of S. plymuthica, which was confirmed by digital DNA-DNA hybridization values [11] above 70% with the (unpublished) draft genome sequence of the S. plymuthica type strain Breed K-7T from a DSM4540 culture using the GGDC web server [12].
Figure 1.

Phylogenetic tree highlighting the position of S. plymuthica AS9 in relation to other species within the genus Serratia, which is based on 1,479 characters of the 16S rRNA gene sequence aligned in ClustalW2 [7]. The tree was inferred under the maximum likelihood criterion [MEGA5, 8] and rooted with Yersinia pseudotuberculosis (a member of the family Enterobacteriaceae). The branches are scaled in terms of the expected number of substitutions per site. The numbers above branches are support values from 1,000 bootstrap replicates if larger than 60% [9]. Lineages with type strain genome sequences registered in GOLD [10] are shown in blue.

S. plymuthica AS9 is a Gram-negative, rod shaped, motile bacterium, 1–2 µm long and 0.5–0.7 µm wide (Figure 2 and Table 1). It forms red to pink colored colonies 1–2 mm in diameter on tryptic soy agar and potato dextrose agar. The color of the bacterium is the result of its production of the red pigment, prodigiosin, but the colony color or production of pigment depends on the ingredients, pH of the medium and the incubation temperature [2628]. S. plymuthica is a facultative anaerobe, grows between 4 °C and 40 °C and within the pH range 4–10. It can utilize a wide range of carbon sources and also has chitinolytic, proteolytic, cellulolytic, and phospholytic activity [5].
Figure 2.

Scanning electron micrograph of S. plymuthica AS9

Table 1.

Classification and general features of S. plymuthica AS9 according to the MIGS recommendations [13]

MIGS ID

Property

Term

Evidence codea

 

Current classification

Domain Bacteria

TAS [14]

  

Phylum Proteobacteria

TAS [15]

  

Class Gammaproteobacteria

TAS [15,16]

  

Order “Enterobacteriales

TAS [17]

  

Family Enterobacteriaceae

TAS [1820]

  

Genus Serratia

TAS [18,21,22]

  

Species Serratia plymuthica

TAS [18,23]

  

Strain AS9

IDA

 

Gram stain

negative

IDA

 

Cell shape

Rod-shaped

IDA

 

Motility

Motile

IDA

 

Sporulation

Non-sporulating

IDA

 

Temperature range

Mesophilic

IDA

 

Optimum temperature

28°C

IDA

 

Carbon source

Glucose, mannitol, sucrose, arabinose, cellobiose

IDA

 

Energy metabolism

Chemoorganotrophic

NAS

 

Terminal electron receptor

 

MIGS-6

Habitat

Rapeseed roots

NAS

MIGS-6.3

Salinity

Medium

IDA

MIGS-22

Oxygen

Facultative

IDA

MIGS-15

Biotic relationship

Free living

NAS

MIGS-14

Pathogenicity

Non-pathogenic

IDA

 

Biosafety level

1+

TAS [24]

MIGS-4

Geographic location

Uppsala, Sweden

NAS

MIGS-5

Sample collection time

Summer 1998

NAS

MIGS-4.1

Latitude

59.8

NAS

MIGS-4.2

Longitude

17.65

NAS

MIGS-4.3

Depth

0.1 m

NAS

MIGS-4.4

Altitude

24-25 m

NAS

a) Evidence codes - IDA: Inferred from Direct Assay; TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project [25]. If the evidence code is IDA, then the property was observed by one of the authors, or an expert mentioned in the acknowledgements.

Chemotaxonomy

The whole cell lipid pattern of S. plymuthica AS9 contains a mixture of saturated and unsaturated fatty acids. The main fatty acids in AS9 strain comprise C16:0 (24.13%), C16:1ω7c (19.41%), C18:1ω7c (18.76%), C14:0 (5.24%) along with other minor fatty acid components. Previously it has been shown that Serratia spp. contain a mixture of C14:0, C16:0, C16:1 and C18:1+2 fatty acids of which 50–80% of the total was C14:0 and other were less than 3% each [29]. This is consistent with the fact that the C14:0 3OH is characteristic of the family Enterobacteriaceae.

Genome sequencing information

S. plymuthica AS9, one of the strains isolated from rapeseed roots and rhizosphere soils was selected for sequencing on the basis of its ability to promote rapeseed growth and inhibit soil borne fungal pathogens. The genome project is deposited in the Genomes On Line Databases [10] and the complete genome sequence is deposited in GenBank. Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI). A summary of the project information is shown in Table 2 and its association with MIGS identifiers.
Table 2.

Genome sequencing project information

MIGS ID

Property

Term

MIGS-31

Finishing quality

Finished

MIGS-28

Libraries used

Three libraries: one 454 standard library, one 454 PE library (12.5 kb insert size), one Illumina library

MIGS-29

Sequencing platforms

Illumina GAii, 454 GS FLX Titanium

MIGS-31.2

Sequencing coverage

323.5 × Illumina; 8.8 × pyrosequencing

MIGS-30

Assemblers

Velvet v. 0.7.63, Newbler v. 2.3 pre-release, phrap version SPS - 4.24

MIGS-32

Gene calling method

Prodigal 1.4, GenePRIMP

 

NCBI project ID

60457

 

INSDC ID

CP002773

 

Genbank Date of Release

October 12, 2011

 

GOLD ID

Gc01772

MIGS-13

Source material identifier

CCUG 61396

 

Project relevance

Biocontrol, Agricultural

Growth conditions and DNA isolation

S. plymuthica AS9 was grown in Luria Broth (LB) medium at 28°C for 12 hours (cells were in the early stationary phase) and the DNA was isolated using a standard CTAB protocol for bacterial genomic DNA isolation which is available at JGI [30].

Genome sequencing and assembly

The genome of strain AS9 was sequenced using a combination of Illumina [31] and 454 sequencing platforms [32]. The details of library construction and sequencing are available at the JGI website [30]. The sequence data from Illumina GAii (1,790.7 Mb) were assembled with Velvet [33] and the consensus sequence computationally shredded into 1.5 kb overlapping fake reads. The sequencing data from 454 pyrosequencing (102.2 Mb) were assembled with Newbler (Roche). The initial draft assembly contained 41 contigs in one scaffold and consensus sequences were computationally shredded into 2 kb overlapping fake reads. The 454 Newbler consensus reads, the Illumina velvet consensus reads and the read pairs in the 454 paired end library were integrated using a software phrap (High Performance Software, LLC) [34]. Possible mis-assemblies were corrected with gapResolution [30], Dupfinisher [35], or by sequencing cloned bridging PCR fragments with subcloning or transposon bombing (Epicentre Biotechnologies, Madison, WI). The gaps between contigs were closed by editing in the software Consed [3638], by PCR and by Bubble PCR (J.-F. Chang, unpublished) primer walks. Thirty seven additional reactions were necessary to close gaps and to raise the quality of the finished sequence. The sequence reads from Illumina were used to correct potential base errors and increase consensus quality using the software Polisher, developed at JGI [39]. The final assembly is based on 47.3 Mb of 454 draft data which provides an average 8.8× coverage of the genome and 1,746.8 Mb of Illumina draft data which provides an average 323.5× coverage of the genome.

Genome annotation

Genes were identified using Prodigal [40] as part of the genome annotation pipeline at Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA, followed by a round of manual curation using the JGI GenPRIMP pipeline [41]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) non-redundant database, Uniport, TIGR-Fam, Pfam, PRIAM, KEGG, COG and InterPro databases. The tRNAScanSE tool [42] was used to find tRNA genes. Additional gene prediction analysis and functional annotation were performed within the Integrated Microbial Genomes - Expert Review (IMG-ER) platform [43].

Genome properties

The S. plymuthica AS9 genome includes a single circular chromosome of 5,442,880 bp with 55.96% GC content. The genome had 5,139 predicted genes of which 4,952 were assigned as protein-coding genes, 113 RNA genes and 75 pseudogenes [Figure 3]. The majority of protein coding genes (87.42%) was assigned as a putative function while those remaining were annotated as hypothetical proteins [Table 3]. The distribution into COG functional categories is presented in Table 4.
Figure 3.

Graphical circular map of the chromosome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red, other RNAs black), GC content, GC skew.

Table 3.

Genome statistics

Attribute

Value

% of totala

Genome size (bp)

5,442,880

100.00%

DNA coding region (bp)

4,739,233

87.07%

DNA G+C content (bp)

3,045,898

55.96%

Total genesa

5,139

100.00%

RNA genes

113

2.19%

rRNA operons

7

 

Protein-coding genes

4,952

96.36%

Pseudo genes

75

1.46%

Genes in paralog clusters

124

2.4%

Genes assigned to COGs

3,807

74.08%

Genes assigned in Pfam domains

4,185

81.43%

Genes with signal peptides

677

13.17%

Genes with transmembrane helices

1,227

23.87%

CRISPR repeats

1

 

a) The total is based on either the size of the genome in base pairs or the total number of protein coding genes in the annotated genome.

Table 4.

Number of genes associated with the 25 general COG functional categories

Code

Value

%agea

Description

J

201

4.27

Translation, ribosomal structure and biogenesis

A

1

0.02

RNA processing and modification

K

481

10.22

Transcription

L

160

3.40

DNA replication, recombination and repair

B

1

0.02

Chromatin structure and dynamics

D

37

0.79

Cell division and chromosome partitioning

Y

0

0.00

Nuclear structure

V

64

1.36

Defense mechanisms

T

187

3.97

Signal transduction mechanisms

M

265

5.63

Cell envelope biogenesis, Outer membrane

N

94

2.00

Cell motility and secretion

Z

0

0.00

Cytoskeleton

W

0

0.00

Extracellular structure

U

116

2.47

Intracellular trafficking and secretion

O

153

3.25

Posttranslational modification, protein turnover, chaperones

C

272

5.78

Energy production and conversion

G

424

9.01

Carbohydrate transport and metabolism

E

470

9.99

Amino acid transport and metabolism

F

106

2.25

Nucleotide transport and metabolism

H

185

3.93

Coenzyme metabolism

I

135

2.87

Lipid metabolism

P

285

6.06

Inorganic ion transport and metabolism

Q

133

2.83

Secondary metabolites biosynthesis, transport and catabolism

R

537

11.41

General function prediction only

S

398

8.46

Function unknown

-

917

17.85

Not in COG

a) The total is based on the total number of protein coding genes in the annotated genome.

Declarations

Acknowledgements

We would like to gratefully acknowledge the help of Elke Lang for providing cell pastes of reference material and Evelyne-Marie Brambilla for extraction of DNA for digital DNA-DNA hybridizations with the reference strains (both at DSMZ). The work conducted by the U.S. Department of Energy Joint Genome Institute is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Authors’ Affiliations

(1)
Uppsala BioCenter, Department of Forest Mycology and Pathology, Swedish University of Agricultural Sciences
(2)
DOE Joint Genome Institute
(3)
Bioscience Division, Los Alamos National Laboratory
(4)
Oak Ridge National Laboratory
(5)
Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures

References

  1. Grimont F, Grimont PAD. The genus Serratia. In: The Prokaryotes, Balows A, Trüper HG, Dworkin M, Harder W, Schleifer K-H (eds), New York: Springer. 1992;2822–2848.Google Scholar
  2. Müller H, Berg G. Impact of formulation procedures on the effect of the biocontrol agent Serratia plymuthica HRO-C48 on Verticillium wilt in oilseed rape. BioControl 2008; 53:905–916. http://dx.doi.org/10.1007/s10526-007-9111-3View ArticleGoogle Scholar
  3. Kalbe C, Marten P, Berg G. Strains of genus Serratia as beneficial rhizobacteria of oilseed rape with antifungal properties. Microbiol Res 1996; 151:433–439. PubMed http://dx.doi.org/10.1016/S0944-5013(96)80014-0View ArticlePubMedGoogle Scholar
  4. Taghavi S, Garafola C, Monchy S, Newman L, Hoffman A, Weyens N, Barac T, Vangronsveld J, van der Lelie D. Genome survey and characterization of endophytic bacteria exhibiting a beneficial effect on growth and development of poplar trees. Appl Environ Microbiol 2009; 75:748–757. PubMed http://dx.doi.org/10.1128/AEM.02239-08PubMed CentralView ArticlePubMedGoogle Scholar
  5. Alström S. Characteristics of bacteria from oilseed rape in relation to their biocontrol activity against Verticillium dahliae. J Phytopathol 2001; 149:57–64. http://dx.doi.org/10.1046/j.1439-0434.2001.00585.xView ArticleGoogle Scholar
  6. Altschul SF, Thomas LS, Alejandro AS, Jingui Z, Webb M, David JL. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res 1997; 25:3389–3402. PubMed http://dx.doi.org/10.1093/nar/25.17.3389PubMed CentralView ArticlePubMedGoogle Scholar
  7. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007; 23:2947–2948. PubMed http://dx.doi.org/10.1093/bioinformatics/btm404View ArticlePubMedGoogle Scholar
  8. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Mol Biol Evol 2011; 28:2731–2739. PubMed http://dx.doi.org/10.1093/molbev/msr121PubMed CentralView ArticlePubMedGoogle Scholar
  9. Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME, Stamatakis A. How many bootstrap replicates are necessary? Lect Notes Comput Sci 2009; 5541:184–200. http://dx.doi.org/10.1007/978-3-642-02008-713View ArticleGoogle Scholar
  10. Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM, Kyrpides NC. The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2010; 38:D346–D354. PubMed http://dx.doi.org/10.1093/nar/gkp848PubMed CentralView ArticlePubMedGoogle Scholar
  11. Auch AF, von Jan M, Klenk HP, Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci 2010; 2:117–134. PubMed http://dx.doi.org/10.4056/sigs.531120PubMed CentralView ArticlePubMedGoogle Scholar
  12. Auch AF, Klenk HP, Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci 2010; 2:142–148. PubMed http://dx.doi.org/10.4056/sigs.541628PubMed CentralView ArticlePubMedGoogle Scholar
  13. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol 2008; 26:541–547. PubMed http://dx.doi.org/10.1038/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
  14. Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria and Eucarya. Proc Natl Acad Sci USA 1990; 87:4576–4579. PubMed http://dx.doi.org/10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
  15. Garrity GM, Bell JA, Lilburn T. Phylum XIV. Proteobacteria phyl. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 1.View ArticleGoogle Scholar
  16. List Editor. Validation of publication of new names and new combinations previously effectively published outside the IJSEM. List no. 106. Int J Syst Evol Microbiol 2005; 55:2235–2238. http://dx.doi.Org/10.1099/ijs.0.64108-0
  17. Garrity GM, Holt JG. Taxonomic Outline of the Archaea and Bacteria. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 155–166.Google Scholar
  18. Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol 1980; 30:225–420. http://dx.doi.org/10.1099/00207713-30-1-225View ArticleGoogle Scholar
  19. Rahn O. New principles for the classification of bacteria. Zentralbl Bakteriol Parasitenkd Infektionskr Hyg 1937; 96:273–286.Google Scholar
  20. Judicial Commission. Conservation of the family name Enterobacteriaceae, of the name of the type genus, and designation of the type species OPINION NO. 15. Int Bull Bacteriol Nomencl Taxon 1958; 8:73–74. http://dx.doi.org/10.1099/0096266X-8-1-73Google Scholar
  21. Bizio B. Lettera di BartolomeoBizio al chiarissimocanonico Angelo Bellani sopra il fenomeno della polenta porporina. Biblioteca Italiana o sia Giornale di Letteratura. [Anno VIII]. Scienze e Arti 1823; 30:275–295.Google Scholar
  22. Sakazaki R. Genus IX. Serratia Bizio 1823, 288. In: Buchanan RE, Gibbons NE (eds), Bergey’s Manual of Determinative Bacteriology, Eighth Edition, The Williams and Wilkins Co., Baltimore, 1974, p. 326–326.Google Scholar
  23. Breed RS, Murray EGD, Hitchens AP. In: Breed RS, Murray EGD, Hitchens AP (eds), Bergey’s Manual of Determinative Bacteriology, Sixth Edition, The Williams and Wilkins Co., Baltimore, 1948, p. 481–482.Google Scholar
  24. BAuA. 2010, Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466, p. 200.
  25. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene Ontology: tool for the unification of biology. Nat Genet 2000; 25:25–29. PubMed http://dx.doi.org/10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
  26. Bennett JW, Bentley R. Seeing red: the story of prodigiosin. Adv Appl Microbiol 2000; 47:1–32. PubMed http://dx.doi.org/10.1016/S0065-2164(00)47000-0View ArticlePubMedGoogle Scholar
  27. Alström S, Gerhardson B. Characteristics of a Serratia plymuthica isolate from plant rhizospheres. Plant Soil 1987; 103:185–189. http://dx.doi.org/10.1007/BF02370387View ArticleGoogle Scholar
  28. Khanafari A, Assadi MM, Fakhr FA. Review of prodigiosin pigmentation in Serratia marcescens. J Biol Sci 2006; 6:1–13.View ArticleGoogle Scholar
  29. Bergan T, Grimont AD, Grimont F. Fatty acids of Serratia determined by gas chromatography. Curr Microbiol 1983; 8:7–11. http://dx.doi.org/10.1007/BF01567306View ArticleGoogle Scholar
  30. DOE Joint Genome Institute. http://www.jgi.doe.gov
  31. Bennett S. Solexa Ltd. Pharmacogenomics 2004; 5:433–438. PubMed http://dx.doi.org/10.1517/14622416.5.4.433View ArticlePubMedGoogle Scholar
  32. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature 2005; 437:326–327. PubMedView ArticleGoogle Scholar
  33. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829. PubMed http://dx.doi.org/10.1101/gr.074492.107PubMed CentralView ArticlePubMedGoogle Scholar
  34. Phrap and Phred for Windows. MacOS, Linux, and Unix. http://www.phrap.com
  35. Han C, Chain P. 2006. Finishing repeat regions automatically with Dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology. Arabina HR, Valafar H (eds), CSREA Press. June 26–29, 2006: 141–146.
  36. Gordon D, Abajian C, Green P. Consed: a graphical tool for sequence finishing. Genome Res 1998; 8:195–202. PubMedView ArticlePubMedGoogle Scholar
  37. Ewing B, Green P. Base-calling of automated sequencer traces using Phred. II. error probabilities. Genome Res 1998; 8:186–194. PubMedView ArticlePubMedGoogle Scholar
  38. Ewing B, Hillier L, Wendl MC, Green P. Base-Calling of automated sequencer traces using Phred. I. accuracy assessment. Genome Res 1998; 8:175–185. PubMedView ArticlePubMedGoogle Scholar
  39. Lapidus A, LaButti K, Foster B, Lowry S, Trong S, Goltsman E. POLISHER: An effective tool for using ultra short reads in microbial genome assembly and finishing. AGBT, Marco Island, FL, 2008Google Scholar
  40. Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
  41. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods 2010; 7:455–457. PubMed http://dx.doi.org/10.1038/nmeth.1457View ArticlePubMedGoogle Scholar
  42. Schattner P, Brooks AN, Lowe TM. The tRNAScanSE, snoscan and snoGPS we servers for the detection of tRNAs and snoRNAs. Nucleic Acids Res 2005; 33:W686–W689. PubMed http://dx.doi.org/10.1093/nar/gki366PubMed CentralView ArticlePubMedGoogle Scholar
  43. Markowitz VM, Ivanova NN, Chen IMA, Chu K, Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics 2009; 25:2271–2278. PubMed http://dx.doi.org/10.1093/bioinformatics/btp393View ArticlePubMedGoogle Scholar

Copyright

© The Author(s) 2012