Open Access

Genome sequence of Ensifer meliloti strain WSM1022; a highly effective microsymbiont of the model legume Medicago truncatula A17

  • Jason Terpolilli1,
  • Yvette Hill1,
  • Rui Tian1,
  • John Howieson1,
  • Lambert Bräu2,
  • Lynne Goodwin3,
  • James Han4,
  • Konstantinos Liolios4,
  • Marcel Huntemann4,
  • Amrita Pati5,
  • Tanja Woyke4,
  • Konstantinos Mavromatis5,
  • Victor Markowitz5,
  • Natalia Ivanova3,
  • Nikos Kyrpides3 and
  • Wayne Reeve1Email author
Standards in Genomic Sciences20139:9020315

https://doi.org/10.4056/sigs.4608286

Published: 20 December 2013

Abstract

Ensifer meliloti WSM1022 is an aerobic, motile, Gram-negative, non-spore-forming rod that can exist as a soil saprophyte or as a legume microsymbiont of Medicago. WSM1022 was isolated in 1987 from a nodule recovered from the roots of the annual Medicago orbicularis growing on the Cyclades Island of Naxos in Greece. WSM1022 is highly effective at fixing nitrogen with M. truncatula and other annual species such as M. tornata and M. littoralis and is also highly effective with the perennial M. sativa (alfalfa or lucerne). In common with other characterized E. meliloti strains, WSM1022 will nodulate but fixes poorly with M. polymorpha and M. sphaerocarpos and does not nodulate M. murex. Here we describe the features of E. meliloti WSM1022, together with genome sequence information and its annotation. The 6,649,661 bp high-quality-draft genome is arranged into 121 scaffolds of 125 contigs containing 6,323 protein-coding genes and 75 RNA-only encoding genes, and is one of 100 rhizobial genomes sequenced as part of the DOE Joint Genome Institute 2010 Genomic Encyclopedia for Bacteria and Archaea-Root Nodule Bacteria (GEBA-RNB) project.

Keywords

root-nodule bacteria nitrogen fixation rhizobia Alphaproteobacteria

Introduction

An available source of nitrogen (N) is essential to life on Earth. Although the atmosphere consists of approximately 80% N, the overwhelming proportion of this is present in the form of dinitrogen (N2) which is biologically inaccessible to the vast majority of higher organisms. Only a subset of microbes has the necessary molecular machinery to make atmospheric N2 bioavailable by enzymatically reducing N2 to NH3. The fact that plant growth is most commonly limited by the availability of N may have provided the selective pressure for a wide range of plant genera, most of which are legumes, to evolve a symbiotic relationship with these N2-fixing microbes. These microsymbionts, collectively termed root nodule bacteria, receive a carbon source from the plant and in return supply the host with biologically fixed N. When these symbiotic interactions are optimally harnessed in agriculture, all the N-requirements of the host can be met, without the need to apply industrially synthesized N-based fertilizers, thereby increasing both the economic and environmental sustainability of the farming system [1].

Forage and fodder legumes play an integral role in sustainable farming practice, providing feed for stock while also enriching soil with bioavailable N. Worldwide, there are approximately 110 million ha of forage and fodder legumes under production [2], of which members of the Medicago genus comprise a considerable component. Two bacterial species, Ensifer meliloti and E. medicae are known to nodulate and fix N2 with Medicago spp. [3], although they differ in their symbiotic properties on some Medicago hosts. Specifically, while E. medicae can nodulate and fix N2 with M. murex, M. arabica and M. polymorpha, E. meliloti does not nodulate M. murex, does not fix with M. polymorpha and fixes N2 very poorly with M. arabica [46].

E. meliloti strain WSM1022 was isolated in 1987 from a nodule collected from the annual M. orbicularis growing on the Cyclades Island of Naxos in Greece. E. meliloti WSM1022 is a highly effective microsymbiont of Medicago, forming efficient N2-fixing associations with the annual species M. littoralis and M. tornata [7]. In common with E. medicae WSM419 [8], WSM1022 also fixes approximately twice as much N2 as E. meliloti 1021 on the model legume M. truncatula A17 [7]. However, unlike E. medicae WSM419, E. meliloti WSM1022 is also highly effective with the perennial M. sativa (alfalfa or lucerne) [7]. Therefore, E. meliloti WSM1022 is a broadly effective microsymbiont of Medicago spp. and as such represents a unique tool for the molecular analysis of effective N2 fixation with fully sequenced macro-and microsymbionts. Here we present a summary classification and a set of general features for E. meliloti strain WSM1022 together with a description of its genome sequence and annotation.

Classification and features

E. meliloti WSM1022 is a motile, Gram-negative rod (Figure 1 Left and Center) in the order Rhizobiales of the class Alphaproteobacteria. It is fast growing, forming colonies within 3–4 days when grown on half strength Lupin Agar (½LA) [9], tryptone-yeast extract agar (TY) [10] or a modified yeast-mannitol agar (YMA) [11] at 28°C. Colonies on ½LA are white-opaque, slightly domed and moderately mucoid with smooth margins (Figure 1Right).
Figure 1.

Images of Ensifer meliloti WSM1022 using scanning (Left) and transmission (Center) electron microscopy and the appearance of colony morphology on a solid medium (Right).

Minimum Information about the Genome Sequence (MIGS) is provided in Table 1. Figure 2 shows the phylogenetic neighborhood of E. meliloti WSM1022 in a 16S rRNA sequence based tree. This strain shares 99.92% and 99.61% sequence identity (over 1290 bp) to the 16S rRNA of the fully sequenced E. meliloti 1021 [29] and E. medicae WSM419 [8] strains, respectively.
Figure 2.

Phylogenetic tree showing the relationship of Ensifer meliloti WSM1022 (shown in bold print) to other Ensifer spp. in the order Rhizobiales based on aligned sequences of the 16S rRNA gene (1,290 bp internal region). All sites were informative and there were no gap-containing sites. Phylogenetic analyses were performed using MEGA, version 5 [25]. The tree was built using the Maximum-Likelihood method with the General Time Reversible model [26]. Bootstrap analysis [27] with 500 replicates was performed to assess the support of the clusters. Type strains are indicated with a superscript T. Brackets after the strain name contain a DNA database accession number and/or a GOLD ID (beginning with the prefix G) for a sequencing project registered in GOLD [28]. Published genomes are indicated with an asterisk.

Table 1.

Classification and general features of Ensifer meliloti WSM1022 according to the MIGS recommendations [12]

MIGS ID

Property

Term

Evidence code

 

Current classification

Domain Bacteria

TAS [13]

 

Phylum Proteobacteria

TAS [14]

 

Class Alphaproteobacteria

TAS [15,16]

 

Order Rhizobiales

TAS [16,17]

 

Family Rhizobiaceae

TAS [18,19]

 

Genus Ensifer

TAS [2022]

 

Species Ensifer meliloti

TAS [21]

 

Gram stain

Negative

IDA

 

Cell shape

Rod

IDA

 

Motility

Motile

IDA

 

Sporulation

Non-sporulating

NAS

 

Temperature range

Mesophile

NAS

 

Optimum temperature

28°C

NAS

 

Salinity

Non-halophile

NAS

MIGS-22

Oxygen requirement

Aerobic

TAS [7]

 

Carbon source

Varied

NAS

 

Energy source

Chemoorganotroph

NAS

MIGS-6

Habitat

Soil, root nodule, on host

TAS [7]

MIGS-15

Biotic relationship

Free living, symbiotic

TAS [7]

MIGS-14

Pathogenicity

Non-pathogenic

NAS

 

Biosafety level

1

TAS [23]

 

Isolation

Root nodule

TAS [11]

MIGS-4

Geographic location

Naxos, Greece

TAS [11]

MIGS-5

Soil collection date

28 April 1987

IDA

MIGS-4.1

Longitude

37.107772

IDA

MIGS-4.2

Latitude

25.387841

 

MIGS-4.3

Depth

0–10cm

 

MIGS-4.4

Altitude

Not recorded

 

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 [24].

Symbiotaxonomy

E. meliloti strain WSM1022 was isolated in 1987 from a nodule collected from the annual M. orbicularis growing on the Cyclades Island of Naxos in Greece. The site of collection was a gentle slope and the soil a sandy-loam texture of pH 7.5–8.0. E. meliloti forms nodules (Nod+) and fixes N2 (Fix+) on a range of annual Medicago spp. as well as the perennial M. sativa (Table 2). In common with other characterized E. meliloti strains, WSM1022 does not nodulate M. murex, does not fix N2 with M. polymorpha and M. arabica [4,5] and is a poorly effective microsymbiont of M. sphaerocarpos [11]. However, WSM1022 is broadly effective with the alkaline soil-adapted annuals M. littoralis and M. tornata as well as the widely grown perennial forage legume M. sativa. In addition, WSM1022 is also a highly effective microsymbiont for the model legume M. truncatula A17.
Table 2.

Nodulation and N2 fixation properties of E. meliloti WSM1022 on selected Medicago spp. Data compiled from [7,11]

Species Name

Cultivar or Accession

Growth Habit

Nodulation

N2 fixation

Comment

M. truncatula

A17

Annual

Nod+

Fix+

Highly effective

M. truncatula

Jemalong

Annual

Nod+

Fix+

Highly effective

M. truncatula

Caliph

Annual

Nod+

Fix+

Highly effective

M. littoralis

Harbinger

Annual

Nod+

Fix+

Highly effective

M. tornata

Tornafield

Annual

Nod+

Fix+

Highly effective

M. sphaerocarpos

Orion

Annual

Nod+

Fix+

Poorly effective

M. arabica

SA36043

Annual

Nod+

Fix

No fixation

M. polymorpha

Santiago

Annual

Nod+

Fix

No fixation

M. murex

Zodiac

Annual

Nod

Fix

No nodulation

M. sativa

Sceptre

Perennial

Nod+

Fix+

Highly effective

Note that ‘+’ and ‘−’ denote presence or absence, respectively, of nodulation (Nod) or N2 fixation (Fix).

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its environmental and agricultural relevance to issues in global carbon cycling, alternative energy production, and biogeochemical importance, and is part of the Community Sequencing Program at the U.S. Department of Energy, Joint Genome Institute (JGI) for projects of relevance to agency missions. The genome project is deposited in the Genomes OnLine Database [28] and an improved-high-quality-draft genome sequence in IMG. Sequencing, finishing and annotation were performed by the JGI. A summary of the project information is shown in Table 3.
Table 3.

Genome sequencing project information for E. meliloti WSM1022.

MIGS ID

Property

Term

MIGS-31

Finishing quality

Improved high-quality draft

MIGS-28

Libraries used

1× Illumina library

MIGS-29

Sequencing platforms

Illumina HiSeq 2000

MIGS-31.2

Sequencing coverage

Illumina: 275×

MIGS-30

Assemblers

Velvet version 1.1.04; Allpaths-LG version r42328

MIGS-32

Gene calling methods

Prodigal 1.4, GenePRIMP

 

GOLD ID

Gi08916

 

NCBI project ID

78233

 

Database: IMG

2510065057

 

Project relevance

Symbiotic N2 fixation, agriculture

Growth conditions and DNA isolation

E. meliloti WSM1022 was cultured to mid logarithmic phase in 60 ml of TY rich medium [30] on a gyratory shaker at 28°C. DNA was isolated from the cells using a CTAB (Cetyl trimethyl ammonium bromide) bacterial genomic DNA isolation method [31].

Genome sequencing and assembly

The genome of Ensifer meliloti WSM1022 was sequenced at the Joint Genome Institute (JGI) using Illumina technology [32]. An Illumina standard shotgun library was constructed and sequenced using the Illumina HiSeq 2000 platform which generated 12,082,430 reads totaling 1812.4 Mbp.

All general aspects of library construction and sequencing performed at the JGI can be found at the JGI website [31]. All raw Illumina sequence data was passed through DUK, a filtering program developed at JGI, which removes known Illumina sequencing and library preparation artifacts (Mingkun, L., Copeland, A. and Han, J., unpublished). The following steps were then performed for assembly: (1) filtered Illumina reads were assembled using Velvet [33] (version 1.1.04), (2) 1–3 kb simulated paired end reads were created from Velvet contigs using wgsim (https://github.com/lh3/wgsim), (3) Illumina reads were assembled with simulated read pairs using Allpaths-LG [34] (version r42328). Parameters for assembly steps were: 1) Velvet (velveth: 63 -shortPaired and velvetg: -veryclean yes -exportFiltered yes -mincontiglgth 500 -scaffolding no-covcutoff 10) 2) wgsim (-e 0 -1 100 -2 100 -r 0 -R 0 -X 0) 3) Allpaths-LG (PrepareAllpathsInputs:PHRED64=1 PLOIDY=1 FRAGCOVERAGE=125 JUMPCOVERAGE=25 LONGJUMPCOV=50, RunAllpath-sLG: THREADS=8 RUN=stdshredpairs TARGETS=standard VAPIWARNONLY=True OVERWRITE=True). The final draft assembly contained 125 contigs in 121 scaffolds. The total size of the genome is 6.6 Mb and the final assembly is based on 1,812.4 Mbp of Illumina data, which provides an average 275× coverage of the genome.

Genome annotation

Genes were identified using Prodigal [35] as part of the DOE-JGI annotation pipeline [36]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. The tRNAScanSE tool [37] was used to find tRNA genes, whereas ribosomal RNA genes were found by searches against models of the ribosomal RNA genes built from SILVA [38]. Other non-coding RNAs such as the RNA components of the protein secretion complex and the RNase P were identified by searching the genome for the corresponding Rfam profiles using INFERNAL (http://infernal.janelia.org). Additional gene prediction analysis and manual functional annotation was performed within the Integrated Microbial Genomes (IMG-ER) platform [39].

Genome properties

The genome is 6,649,661 nucleotides with 62.16% GC content (Table 4) and comprised of 121 scaffolds (Figure 3) of 125 contigs. From a total of 6,398 genes, 6,323 were protein encoding and 75 RNA only encoding genes. The majority of genes (80.78%) were assigned a putative function whilst the remaining genes were annotated as hypothetical. The distribution of genes into COGs functional categories is presented in Table 5.
Figure 3.

Graphical map of the genome of Ensifer meliloti WSM1022 showing the seven largest scaffolds. From bottom to the top of each scaffold: Genes on forward strand (color by COG categories as denoted by the IMG platform), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, sRNAs red, other RNAs black), GC content, GC skew.

Table 4.

Genome Statistics for Ensifer meliloti WSM1022

Attribute

Value

% of Total

Genome size (bp)

6,649,661

100.00

DNA coding region (bp)

5,733,017

86.22

DNA G+C content (bp)

4,133,661

62.16

Number of scaffolds

121

 

Number of contigs

125

 

Total gene

6,398

100.00

RNA genes

75

1.17

rRNA operons

1

0.02

Protein-coding genes

6,323

98.83

Genes with function prediction

5,168

80.78

Genes assigned to COGs

5,147

80.45

Genes assigned Pfam domains

5,331

83.32

Genes with signal peptides

563

8.80

Genes with transmembrane helices

1,437

22.93

CRISPR repeats

0

 
Table 5.

Number of protein coding genes of Ensifer meliloti WSM1022 associated with the general COG functional categories.

Code

Value

% age

COG Category

J

194

3.38

Translation, ribosomal structure and biogenesis

A

0

0.00

RNA processing and modification

K

497

8.65

Transcription

L

196

3.41

Replication, recombination and repair

B

1

0.02

Chromatin structure and dynamics

D

38

0.66

Cell cycle control, mitosis and meiosis

Y

0

0.00

Nuclear structure

V

61

1.06

Defence mechanisms

T

235

4.09

Signal transduction mechanisms

M

301

5.24

Cell wall/membrane biogenesis

N

71

1.24

Cell motility

Z

0

0.00

Cytoskeleton

W

1

0.02

Extracellular structures

U

113

1.97

Intracellular trafficking and secretion

O

177

3.08

Posttranslational modification, protein turnover, chaperones

C

357

6.21

Energy production conversion

G

606

10.54

Carbohydrate transport and metabolism

E

623

10.84

Amino acid transport metabolism

F

109

1.90

Nucleotide transport and metabolism

H

200

3.48

Coenzyme transport and metabolism

I

207

3.60

Lipid transport and metabolism

P

312

5.43

Inorganic ion transport and metabolism

Q

158

2.75

Secondary metabolite biosynthesis, transport and catabolism

R

708

12.32

General function prediction only

S

583

10.14

Function unknown

-

1,251

19.55

Not in COGS

Total

5,748

-

-

Declarations

Acknowledgements

This work was performed under the auspices of the US Department of Energy’s Office of Science, Biological and Environmental Research Program, and by the University of California, Lawrence Berkeley National Laboratory under contract No. DE-AC02-05CH11231, Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344, and Los Alamos National Laboratory under contract No. DE-AC02-06NA25396. We gratefully acknowledge the funding received from the Murdoch University Strategic Research Fund through the Crop and Plant Research Institute (CaPRI) and the Centre for Rhizobium Studies (CRS) at Murdoch University. We also acknowledge ECR funding for J. Terpolilli awarded by the School of Veterinary and Life Sciences at Murdoch University.

Authors’ Affiliations

(1)
Centre for Rhizobium Studies, Murdoch University
(2)
School of Life and Environmental Sciences, Deakin University
(3)
Bioscience Division, Los Alamos National Laboratory
(4)
DOE Joint Genome Institute
(5)
Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory

References

  1. Howieson JG, O’Hara GW, Carr SJ. Changing roles for legumes in Mediterranean agriculture: developments from an Australian perspective. Field Crops Res 2000; 65:107–122. http://dx.doi.org/10.1016/S0378-4290(99)00081-7View ArticleGoogle Scholar
  2. Herridge DF, Peoples MB, Boddey RM. Global inputs of biological nitrogen fixation in agricultural systems. Plant Soil 2008; 311:1–18. http://dx.doi.org/10.1007/s11104-008-9668-3View ArticleGoogle Scholar
  3. Graham P. Ecology of the root-nodule bacteria of legumes. In: Dilworth MJ, James EK, Sprent JI, Newton WE, editors. Nitrogen-Fixing Leguminous Symbioses. Dodrecht, The Netherlands: Springer; 2008. p 23–43.Google Scholar
  4. Garau G, Reeve WG, Brau L, Yates RJ, James D, Tiwari R, O’Hara GW, Howieson JG. The symbiotic requirements of different Medicago spp. suggest the evolution of Sinorhizobium meliloti and S. medicae with hosts differentially adapted to soil pH. Plant Soil 2005; 276:263–277. http://dx.doi.org/10.1007/s11104-005-0374-0View ArticleGoogle Scholar
  5. Rome S, Cleyet-Marel JC, Materon LA, Normand P, Brunel B. Rapid identification of Med cago nodulating strains by using two oligonucleotide probes complementary to 16S rDNA sequences. Can J Microbiol 1997; 43:854–861. PubMed http://dx.doi.org/10.1139/m97-124View ArticlePubMedGoogle Scholar
  6. Brunel B, Rome S, Ziani R, Cleyet-Marel JC. Comparison of nucleotide diversity and symbiotic properties of Rhizobium meliloti populations from annual Medicago species. FEMS Microbiol Ecol 1996; 19:71–82. http://dx.doi.org/10.1111/j.1574-6941.1996.tb00200.xView ArticleGoogle Scholar
  7. Terpolilli JJ, O’Hara GW, Tiwari RP, Dilworth MJ, Howieson JG. The model legume Medicago truncatula A17 is poorly matched for N2 fixation with the sequenced microsymbiont Sinorhizobium meliloti 1021. New Phytol 2008; 179: 62–66. PubMed http://dx.doi.org/10.1111/j.1469-8137.2008.02464.xView ArticlePubMedGoogle Scholar
  8. Reeve W, Chain P, O’Hara G, Ardley J, Nandesena K, Brau L, Tiwari R, Malfatti S, Kiss H, Lapidus A, et al. Complete genome sequence of the Medicago microsymbiont Ensifer (Sinorhizobium) medicae strain WSM419. Stand Genomic Sci 2010; 2:77–86. PubMed http://dx.doi.org/10.4056/sigs.43526PubMed CentralView ArticlePubMedGoogle Scholar
  9. Howieson JG, Ewing MA, D’antuono MF. Selection for acid tolerance in Rhizobium meliloti. Plant Soil 1988; 105:179–188. http://dx.doi.org/10.1007/BF02376781View ArticleGoogle Scholar
  10. Beringer JE. R factor transfer in Rhizobium leguminosarum. J Gen Microbiol 1974; 84:188–198. PubMed http://dx.doi.org/10.1099/00221287-84-1-188PubMedGoogle Scholar
  11. Terpolilli JJ. Why are the symbioses between some genotypes of Sinorhizobium and Medicago suboptimal for N2 fixation? Perth: Murdoch University; 2009. 223 p.Google Scholar
  12. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen M, Angiuoli SV, et al. Towards a richer description of our complete collection of genomes and metagenomes “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
  13. 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
  14. 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
  15. Garrity GM, Bell JA, Lilburn T. Class I. Alphaproteobacteria class. In: Garrity GM, Brenner DJ, Kreig NR, Staley JT, editors. Bergey’s Manual of Systematic Bacteriology. Second ed: New York: Springer-Verlag; 2005, p. 1.View ArticleGoogle Scholar
  16. Validation List No. 107. List of new names and new combinations previously effectively, but not validly, published. Int J Syst Evol Microbiol 2006; 56:1–6. PubMed http://dx.doi.org/10.1099/ijs.0.64188-0
  17. Kuykendall LD. Order VI. Rhizobiales ord. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 2, Part C, Springer, New York, 2005, p. 324.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. Conn HJ. Taxonomic relationships of certain non-sporeforming rods in soil. J Bacteriol 1938; 36:320–321.Google Scholar
  20. Casida LE. Ensiferadhaerens gen. nov., sp. nov.: a bacterial predator of bacteria in soil. Int J Syst Bacteriol 1982; 32:339–345. http://dx.doi.org/10.1099/00207713-32-3-339View ArticleGoogle Scholar
  21. Young JM. The genus name Ensifer Casida 1982 takes priority over Sinorhizobium Chen et al. 1988, and Sinorhizobium morelense Wang et al. 2002 is a later synonym of Ensiferadhaerens Casida 1982. Is the combination Sinorhizobium adhaerens (Casida 1982) Willems et al. 2003 legitimate? Request for an Opinion. Int J Syst Evol Microbiol 2003; 53:2107–2110. PubMed http://dx.doi.org/10.1099/ijs.0.02665-0View ArticlePubMedGoogle Scholar
  22. Judicial Commission of the International Committee on Systematics of Prokaryotes. The genus name Sinorhizobium Chen et al. 1988 is a later synonym of Ensifer Casida 1982 and is not conserved over the latter genus name, and the species name ‘Sinorhizobium adhaerens’ is not validly published. Opinion 84. Int J Syst Evol Microbiol 2008; 58:1973. PubMed http://dx.doi.org/10.1099/ijs.0.2008/005991-0View ArticleGoogle Scholar
  23. Gubler M, Hennecke H, Fix A. B and C genes are essential for symbiotic and free-living, microaerobic nitrogen fixation. FEBS Lett 1986; 200:186–192. http://dx.doi.org/10.1016/0014-5793(86)80536-1View ArticleGoogle Scholar
  24. 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. The Gene Ontology Consortium. Nat Genet 2000; 25:25–29. PubMed http://dx.doi.org/10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
  25. 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
  26. Nei M, Kumar S. Molecular Evolution and Phylogenetics. New York: Oxford University Press; 2000.Google Scholar
  27. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 1985; 39:783–791. http://dx.doi.org/10.2307/2408678View ArticleGoogle Scholar
  28. Liolios K, Mavromatis K, Tavernarakis N, Kyrpides NC. The Genomes On Line Database (GOLD) in 2007: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2008; 36:D475–D479. PubMed http://dx.doi.org/10.1093/nar/gkm884PubMed CentralView ArticlePubMedGoogle Scholar
  29. Galibert F, Finan TM, Long SR, Puhler A, Abola P, Ampe F, Barloy-Hubler F, Barnett MJ, Becker A, Boistard P, et al. The composite genome of the legume symbiont Sinorhizobium meliloti. Science 2001; 293:668–672. PubMed http://dx.doi.org/10.1126/science.1060966View ArticlePubMedGoogle Scholar
  30. Reeve WG, Tiwari RP, Worsley PS, Dilworth MJ, Glenn AR, Howieson JG. Constructs for insertional mutagenesis, transcriptional signal localization and gene regulation studies in root nodule and other bacteria. Microbiology 1999; 145:1307–1316. PubMed http://dx.doi.org/10.1099/13500872-145-6-1307View ArticlePubMedGoogle Scholar
  31. DOE Joint Genome Institute user home. http://my.jgi.doe.gov/general/index.html
  32. Bennett S. Solexa Ltd. Pharmacogenomics 2004; 5:433–438. PubMed http://dx.doi.org/10.1517/14622416.5.4.433View ArticlePubMedGoogle Scholar
  33. Zerbino DR. Using the Velvet de novo assembler for short-read sequencing technologies. Current Protocols in Bioinformatics 2010; Chapter 11:Unit 11 5.Google Scholar
  34. Gnerre S, MacCallum I, Przybylski D, Ribeiro FJ, Burton JN, Walker BJ, Sharpe T, Hall G, Shea TP, Sykes S, et al. High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proc Natl Acad Sci USA 2011; 108:1513–1518. PubMe http://dx.doi.org/10.1073/pnas.1017351108PubMed CentralView ArticlePubMedGoogle Scholar
  35. 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
  36. Mavromatis K, Ivanova NN, Chen IM, Szeto E, Markowitz VM, Kyrpides NC. The DOE-JGI Standard operating procedure for the annotations of microbial genomes. Stand Genomic Sci 2009; 1:63–67. PubMed http://dx.doi.org/10.4056/sigs.632PubMed CentralView ArticlePubMedGoogle Scholar
  37. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 1997; 25:955–964. PubMedPubMed CentralView ArticlePubMedGoogle Scholar
  38. Pruesse E, Quast C, Knittel K. Fuchs BdM, Ludwig W, Peplies J, Glöckner FO. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 2007; 35:7188–7196. PubMed http://dx.doi.org/10.1093/nar/gkm864PubMed CentralView ArticlePubMedGoogle Scholar
  39. Markowitz VM, Mavromatis K, Ivanova NN, Chen IM, 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

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