Pan-genomic Analysis of Bradyrhizobium japonicum

Ruihan Ma

Northeast Agriculture University, Heilongjiang, 15000, China

Keywords: Bradyrhizobium, Biosphere, Genus.

Abstract: The rhizobium-legume symbiosis is a major source of fixed nitrogen (ammonia) in the biosphere—the

potential for this process to increase agricultural yield while reducing the reliance on nitrogen-based

fertilizers. Bradyrhizobium is an ancient type of soybean nitrogen-fixing symbiotic bacteria. The

Bradyrhizobium japonicum under the bacterial genus classification is widely used as a promotional species

in actual agricultural production. However, the use of rhizobium also faces some practical problems, like Its

nitrogen fixation capacity is unstable. Despite much current research on Bradyrhizobium japonicum, it often

focuses on the molecular mechanism of a certain gene or protein, failing to study the environmental

adaptability of such bacteria, and failing to study the function and characteristics of bacteria from a genomic

perspective. The paper focuses on Pan-genome to study Bradyrhizobium japonicum. Through the obtained

genome information tested for line integrity using CheckM and BUSCO, analysis of the Meverage nucleotide

consistency (similarity) ANI, and analysis of the secondary metabolite, the genomic dynamics of soybean

bradyrhizobium is initially revealed and provides research clues for the analysis of its bacterial functional

evolution mechanism and environmental adaptability.

1 INTRODUCTION

The mutually beneficial symbiosis of rhizobium and

legumes provides plants with rich nitrogen while

actively affecting the soil nitrogen circulation. As a

classic model of bionitrogen fixation, with rhizobium

jointly regulated by plant roots and rhizobium, its

nitrogen fixation occupies more than 60% of the total

bionitrogen fixation (Herridge, 2008) and greatly

alleviates the nitrogen demand in agriculture. It is

worth mentioning that rhizobium

Compound agents (Bradyrhizobium japonicum

and Bacillus subtilis) developed by Indigo (Indigo

Ag, Inc., Charlestown, USA) can increase crop yield

(> 3%) and water absorption efficiency under drought

stress (> 75%) with less nitrogen fertilizer

application. The success of this model has also made

the research and promotion of new bacterial agents or

fertilizers the future development direction of

agriculture. Rhizobium is a special plant tissue

formed by rhizobium and legumes, a process that

involves many chemicals, such as plant-secreted

flavonoids, isoflavones, and terpenoids (Stoksta,

2016). Some certain root secretions (flavonoids-like,

https://orcid.org/0000-0001-5028-5620

isoflavones) can bind to the NodD protein secretion

of rhizobium, causing nod gene expression to produce

tuberoma factor, which then acts with the plant root

cells to activate tuberoma-related gene expression to

form rhizobium (BROGHAMMER, 2012). The

genus rhizoma was established in 1889 by B. Frank,

containing three species: pea rhizobium, alfalfa, and

passion. Bradyrhizobium D.C. Jordan differentiated

from rhizobium in 1982. Bradyrhizobium is an

ancient soybean nitrogen-fixing symbiotic bacteria

widely distributed in different habitats and symbiotic

with different legume-specific hosts. Therefore it is

highly cosmopolitan (SPRENT, 2017).

Bradyrhizobium diazoefficiens USDA110 can form

rhizoma with soybean and has excellent symbiotic

nitrogen fixation properties. The Bradyrhizobium

japonicum under the bacterial genus classification is

widely used as a promotional species in agricultural

production. Interestingly, as taxonomy developed, the

well-known Bradyrhizobium japonicum USDA 110

was eventually divided into Bradyrhizobium

diazoefficiens and named Bradyrhizobium

diazoefficiens USDA 110. However, the use of

rhizobium also faces some practical problems. The

Ma, R.

Pan-genomic Analysis of Bradyrhizobium japonicum.

DOI: 10.5220/0011376000003443

In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics (ICBEB 2022), pages 1031-1040

ISBN: 978-989-758-595-1

1031

specific identification of host-rhizomomyces causes

rhizobium to be unable to colonize all legume crops.

Their nitrogen fixation capacity is good or bad, not as

predictable as chemical fertilizers. On the one hand,

this is related to rhizobium's genomes and involves

the interaction between rhizobium and plants and

indigenous microorganisms. Traditionally, most

researchers focus on the individual gene or protein to

enhance the nitrogen fixation capacity of the

rhizobium and rare to focus on genomes, but the

effect was not ideal. This paper adopts a new research

method, which is to use Pan-genome to study

Bradyrhizobium. The Pan-genome is defined as the

entire non-redundant gene bank that constitutes the

genome, including the core genome, a set of genes

(almost) present in all genomes; accessory genome,

present in more than two genomes; unique genome,

found only in a bacterial genome. In this paper, Pan-

genome analysis focuses on Bradyrhizobium, first

with identifying core genes, accessory genes, unique

genes, and this-based gene function analysis;

secondly, the openness and closure of the genome are

also important concepts. This paper analyzes the

genome sequence of all 21 Bradyrhizobium

japonicum and one Bradyrhizobium diazoefficiens

USDA 110(from the NCBI due to historical naming).

According to the Heap rule, the closed Pan

genome contains all possible genes, and even

increasing the scale of genome sequencing, only a

small amount of genes are added to the Pan

genome.For an open Pan genome, the sequencing of

the new genome will increase a lot of undiscovered

genes, where its Pan genome is open (L R, V M, P-E

F, 2015).Usually, bacterial biogenomes with multiple

hosts or frequent habitat changes are more open

because their gene islands are more varied; Once

specialized intracellular, pathogens are not in

constant contact with other bacteria and lose large

amounts of genes in evolution to fully adapt to the

host. Thus, their genomes are very compact and more

closed (BARSY, 2016). The differentiation of the

genus rhizobium dates back 200 million years ago (L

M, A M, B D, 2001). However, beumes occurred 60

million years ago (MATT, 2005). This and its

mismatch suggest that rhizobium's symbiotic

nitrogen fixation capacity occurs in modern times,

possibly caused by the horizontal transfer of genes.

However, whether current genomes are open and how

to open rhizobium is still worth studying. The study

of the general genome of the rhizome helps to deepen

the understanding of the soybean-rhizome symbiosis,

provides a theoretical basis for the agricultural

production and application of rhizome, and is of great

significance to the study of the global nitrogen

ecological cycle.

2 METHODS

2.1 Data Source

The genomic data for 21 Bradyrhizobium japonicum

and 1 Bradyrhizobium diazoefficiens analynome

database and the zed in this paper are from NCBI

Gedata format of fasta, is shown in Table 1.In genome

assembly, it is assembled from contig into

scaffold,contig represents the consensus sequences

found from short reads obtained from large-scale

sequencing.The first step in assembly is the assembly

of contig. from a pair-end library.Further based on

mate-pair libraries of different lengths, the originally

isolated contig are connected in order, this step

yielding scaffolds. Finally, scaffold merged adjusted

based on genetic or optical maps to form a

chromosome.

Table 1: The strain information used in the study analysis.

species Bacterial

strain

BioSample

numbe

Assembly

level

Genome Size

(Mb)

GC% Scaffolds

numbe

Host

information

B. japonicum USDA 6 SAMD00060992 Complete 9.20738 63.7 1 absent

J5 SAMN05890661 Complete 10.1387 63.3 1 soybean

nodulation

5038 SAMN15394813 Complete 9.22625 63.7 1 Soybean

nodulation

E109 SAMN03262953 Complete 9.22421 63.7 1 Farmland

soybean

rhizoma

SEMIA

5079

SAMN02726028 Chromosome 9.58303 63.5 1 Duress soybean

plants

NBRC

14783

SAMD00097546 Contig 9.09656 63.7 177 soybean

5873 SAMN13738681 Scaffold 9.16023 63.7 141 soybean

Is-34 SAMN03083461 Scaffold 10.3266 63 248 soybean

nodulation

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22 SAMN02441445 Scaffold 7.50456 64.5 4 absent

in8p8 SAMN02440647 Scaffold 7.58992 63.8 52 absent

is5 SAMN02440582 Contig 7.58879 63.8 60 absent

USDA 38 SAMN02440784 Scaffold 9.60897 63.5 107 soybean

FN1 SAMN02666820 Scaffold 9.1385 63.7 87 soil

UBMA197 SAMN06077198 Contig 10.4422 63.3 287 Panleaf pinoma

rhizoma

USDA 123 SAMN02441447 Scaffold 10.4577 63.3 517 soybean

CCBAU

25435

SAMN02469483 Contig 9.46079 63.5 520 absent

CCBAU

15618

SAMN02469476 Contig 9.82401 63.4 691 absent

USDA 135 SAMN02441452 Scaffold 7.70332 64 547 soybean

CCBAU

15354

SAMN02469475 Contig 10.1266 63.3 951 absent

CCBAU

15517

SAMN02469482 Contig 9.91703 63.4 1129 absent

CCBAU

83623

SAMN02469465 Contig 10.0743 63.3 1212 absent

B. diazoefficiens USDA 110 SAMN03573437 Complete 9.10606 64.1 1 absent

2.2 Genomic Integrity

The genomic information obtained is tested with

CheckM (PARKS, 2015) and BUSCO (SIMAO,

2015), and the genome with insufficient

completeness or high contamination is not conducive

to the Pan-genomic subsequent analysis. CheckM

evaluates genome integrity and contamination by

specific to a species lineage and unique genes in the

database. Cds of genome are predicted through

Prodigal (HYATT, 2010) software that Prodigal

shows excellent robustness to gene structure

prediction, translation starting site recognition, and

false positives. BUSCO constructed a single-copy

conserved gene set of genomome Rhizobiales

through the OrthoDB database, compared the

transcript results by Augustus software, and then the

proportion and integrity to evaluate genome integrity.

2.3 Pan-genome Analysis

Genomes were first annotated through Prokka

software, analyzed with gbk files of generated

GeneBank through BPGA (CHAUDHARI, 2016)

(V1.3), selected default parameters. BPGA adopted

Neighbour Joining Tree achievements for core genes

and used USEARCH Clustering Algorithm genome

annotation is mainly based on COG and KEGG

databases. The Pipeline of, panX (DING, 2018),

PGCGAP (https://github.com/yikedou/pgcgap).

2.4 Analysis of Secondary Metabolites

The secondary metabolites of microorganisms are a

class of complex functional compounds synthesized

by primary metabolites through complex synthetic

paths and processes, such as antibiotics, pheromones,

toxins, etc., which is very important for the growth

and competition of microorganisms. The more

complex the life history, the wider the host, the

greater the living environment changes. The more

frequent the communication with the host, the more

metabolites of the secondary level. Secondary

metabolites can be predicted through published

microbial genomic data. Secondary metabolites

analysis can be analyzed based on antiSMASH. Still,

the online version is more abundant, comprehensive

and accurate than the local version, so the online

version of antiSMASH (https: / / antismash.

secondary etabolites.org), the parameters are default.

The strictness of the test is relaxed.

3 RESULTS AND DISCUSSION

3.1 Genomic Integrity

After the genome integrity analysis of 22 soybean

slow biological rhizomas, we found that the selected

genome integrity was higher, all above 97%, but only

a few genomes could reach 100%, as shown in Figure

1. The CheckM results showed that the remaining

genome was relatively complete except for a weak B.

japonicum CCBAU series sequence deletion (Figure

1), consistent with the BUSCO results (Figure 2).In

addition, most of the genome has a small number of

Pan-genomic Analysis of Bradyrhizobium japonicum

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gene pollution, the main reason for this phenomenon

may be wrong sequencing, foreign genes (human,

bacteria in the air, etc.), pollution or sequence splicing

in the sequencing process, but this part is relatively

low and does not affect the subsequent

analysis.BUSCO analysis showed a small number of

genes (Figure 1B yellow section), generally due to

insufficient sequencing depth or incomplete genome

splicing. In addition, the BUSCO results show

multiple copies of parts of the Marker gene in the

rhizobium genome. Overall, the NCBI uploads high

genome integrity and allows downstream generic

genomic and other analysis processes.

Figure 1: 22 Genome integrity assessment of Bradyrhizobium(checkM Assessment Result).

Figure 2: 22 Genome integrity assessment of Bradyrhizobium(BUSCO Assessment result).

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

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3.2 Pan-genomic Statistics

This paper counted the number of core, accessory,

and unique genome (specific) and unique deletion

genome of 22 Rhizobium strains, as shown in Table

2. Bradyrhizobium diazoefficiens USDA 110 is

found more common genomics (794) specific

deletion genes (63), so although its genome is

complete, it still varies from Bradyrhizobium

japonicum, so it is understandable to divide it into

other categories. The Pan-genomic statistics of 22

rhizobium counted 3,807 core genes, which is very

small. The core genome is the genes shared by all

strains involved in basic biological processes such as

gene expression, energy production, amino acid

metabolism, etc. Some strains have even more

accessory genomes than the number of core genomes.

Accessory genomes represent some specific

functions and have a relatively strong metabolic

ability. Unique genomes represent that some of their

achievements are more competitive. The more unique

genomes, the stronger the resistance to environmental

adaptability. Thus it can be seen B.japonicum

UBMA197, B. japonicum USDA_135, B. japonicum

22 metabolic ability, environmental adaptability

ability are very strong; B.japonicum 5038, B.

japonicum 5873, B. japonicum E109, B. japonicum

FN1 is highly metabolizing, but it is less

heterophenetic and less adaptable. Many genomes

have more unique genomes like B. japonicum

USDA_135, B. japonicum 22, B. diazoefficiens

USDA_110, B. japonicum UBMA197, which make

each biometabolic process rich and will be beneficial

to the expansion of habitat (Konstantinidis, 2004),

which may be the reason why the wide range of

Bradyrhizobium adapted to (Tian, 2012).

Table 2: 22 Pangenic statistics of rhizoma strains.

Species Core genes accessory

gene

unique gene(specific) Specific

deletion gene

B. diazoefficiens USDA_110 3807 3213 794 63

B. japonicum USDA_123 3807 4745 527 12

B. japonicum USDA_135 3807 2242 717 114

B. japonicum 22 3807 2019 758 114

B. japonicum 5038 3807 4155 1 0

B. japonicum 5873 3807 4148 0 1

B. japonicum CCBAU_15354 3807 5010 132 24

B. japonicum CCBAU_15517 3807 4985 170 22

B. japonicum CCBAU_15618 3807 4422 433 22

B. japonicum CCBAU_25435 3807 4122 347 22

B. japonicum CCBAU_83623 3807 5032 266 21

B. japonicum E109 3807 4152 1 0

B. japonicum FN1 3807 4152 6 1

B. japonicum in8p8 3807 2919 4 1

B. japonicum is5 3807 2918 12 1

B. japonicum Is-34 3807 4409 645 0

B. japonicum J5 3807 4359 400 1

B. japonicum NBRC_14783 3807 4135 10 3

B. japonicum SEMIA_5079 3807 4143 246 1

B. japonicum UBMA197 3807 4176 1048 8

B. japonicum USDA_6 3807 4141 17 5

B. japonicum USDA_38 3807 4276 314 1

3.3 COG Analysis

COG analysis found that,as shown in figure 3, the

genome was mainly focused on related functions such

as [R]General function prediction only, [E]Amino

acid transport and metabolism,[K]Transcription. The

proportion of the core genome, accessory genome,

and unique genome is almost the same in these

functions, directly related to biological trait

expression and basic functions, so the genome plays

a major role in biological trait expression.

Pan-genomic Analysis of Bradyrhizobium japonicum

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The numbers of genomes related with [M] cell

wall\ membrane\ evelope biogenesis, [T] singal

transduction mechanism, [L] replication,

recombination and repair, [C] energy production and

conversation, [G] Carbohydrate transport and

metabolism, [I] lipid transport and metabolism, [Q]

secondary metabolites biogenesis, transport, and

catabolism, [P]inorganic ion transport and

metabolism are similar. It shows that the strain gene

is mostly concentrated in the metabolic process and

cell differentiation process. It is preliminarily

speculated that this is suitable for the nitrogen

fixation process of rhizobium and legume symbiosis.

The nitrogen fixation process is very complex. It

includes many symbiotic processes, such as rhizoma

infection, bacteria-like differentiation, and tuberous

nitrogen fixation. Their differentiation and

rhizobiums require the expression of related genes in

a large number of cell components. The invasion and

symbiotic nitrogen fixation process with rhizomes

involves biological processes, as well as signal

exchange, interaction, material transportation, and

metabolism, so it requires the participation of many

genes related to molecular function and biological

processes (Wang, 2014). The above inferences now

require further testing.

Figure 3: COG analyse.

3.4 KEGG Analysis

As shown in figure 4, KEGG analysis found a high

proportion of genome distribution in amino acid

metabolism, carbohydrate metabolism, membrane

transport, overview, etc. In these fundamental

functions, like amino acid metabolism, core genomes

play a major role. Amino acid transport and

metabolism are relatively many genes, and it is

preliminarily speculated that this may be related to its

high activity efficiency. Because complex amino acid

circulation is essential for symbiotic nitrogen

fixation, both sides will control the substance

exchange by controlling amino acid metabolism

(Lodwig, 2003); (Prell, 2006). At the same time, the

genes are distributed in cardiovascular diseases,

cellular community, development, digestive system,

excretory. The number of specific functions such as

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system, sensory system, signaling molecules, and

interaction\ substance dependence\ transcription is

small. Therefore, it can be seen that these bacteria all

have a strong basic function, but the specific

environment is poorly adaptable.

Figure 4. KEGG analyse

3.5 Panogenomic Fitting Equations

The correlation parameters of the fitting equation, as

shown in figure 5, of the generic genome size (T)

relation to genome number (X) are shown in the

figure, showing that the number of genes in the

generic genome of Bradyrhizobium increases as the

number of the genome increases. Different genomes

have the same gene family, and when the number of

genomes in each family increases, the genes in this

family are relatively open (Sun, 2013). The change is

unique number, and the curve shows the core gene

number with an increasing genome. Open here means

that the species is able to exchange genetic material

with other species in many different ways to acquire

new genes. The Bradyrhizobium genome has

extremely high plasticity, suggesting that it may more

readily acquire new genes to accommodate complex

changes in the environment.

Figure 5: Panogenomic fitting equations.

Pan-genomic Analysis of Bradyrhizobium japonicum

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3.6 Analysis of Secondary Metabolites

Secondary metabolites are predicted through

published microbial genomic data and are analyzed

using an online version of antiSMASH (https: / /

antismash. secondary etabolites.org). Similar

similarities were found between strains, as shown in

table 3.

lanthipeptide-class-v,

cyanobactin(cyanobacteria), beta lactone, T3PKS,

T1PKS, phosphonate, is compounds do not occur in

other species. Hserlactone and RiPP-like, terpene,

LAP, proteusin all exist to maintain the basic

metabolic process. Lipoids such as beta lactone,

Hserlactone can serve as stored energy in extreme

environments or hungry situations for microbial

growth to provide carbon sources and energy

(Kadouri, 2005). Compounds such as terpene are

present in all types of strains, are associated with the

growth and development of plants, and participate in

the plant defensive response to (LYU, 2017).

Therefore, the enrichment of lipid metabolism and

transport pathway and the participation of compounds

such as terpene may be mechanisms for the effective

environmental adaptation of Bradyrhizobium.

Lanthipeptides and RiPP-like is a large class of

natural peptide products synthesized by ribosomal

and translates modified. Such compounds are widely

produced in different bacteria, with rich structural and

biological activity diversity; T3PKS and T1PKS all

belong to the antimicrobial proteins generated by the

ribosomal pathway. RRE-containing rarely occurs,

only where Bradyrhizobium japonicum CCBAU

15517, Bradyrhizobium japonicum E109, is endemic

to secondary metabolites. RRE-containing is related

to RNA transcription and gene expression, so

Bradyrhizobium japonicum CCBAU 15517,

Bradyrhizobium japonicum E109 will have some

specific functions, representing some specific

functions its strong environmental adaptability.

Table 3: Analysis of the secondary metabolites of 22 rhizoma strains.

Baterial name Number of

secondary

metabolites

ene clusters

secondary metabolite

Bradyrhizobium japonicum 22 11 hserlactone, RiPP-like, T1PKS, terpene, lanthipeptide-

class-v, cyanobactin, redox-cofacto

, beta lactone

Bradyrhizobium japonicum 5038 10 RiPP-like, proteusin, NRPS, ectoine, NRPS, terpene, LAP,

redox-cofacto

, hserlactone

Bradyrhizobium japonicum 5873 10 hserlactone, RiPP-like, NRPS, redox-cofactor, LAP,

roteusin, terpene

Bradyrhizobium japonicum CCBAU 15354 15 T3PKS, hserlactone, RiPP-like, terpene, NRPS, redox-

cofacto

, LAP, lanthipeptide-class-v, RiPP-like

Bradyrhizobium japonicum CCBAU 15517 13 RRE-containing, hserlactone, NRPS, RiPP-like, LAP,

ter

ene, T3PKS,

roteusin

Bradyrhizobium japonicum CCBAU 15618 14 hserlactone, terpene, LAP, redox-cofactor, proteusin,

NRPS, NRPS-like

Bradyrhizobium japonicum CCBAU 25435 13 terpene, LAP, hserlactone, redox-cofactor, RiPP-like

NRPS,

roteusin

Bradyrhizobium japonicum CCBAU 83623 14 redox-cofactor, hserlactone, NRPS, terpene, RiPP-like,

LAP, T3PKS, ectoine,

roteusin

Bradyrhizobium japonicum E109 10 hserlactone, redox-cofactor, terpene, LAP, RiPP-like,

NRPS, ectoine,

roteusin, RRE-containin

Bradyrhizobium japonicum FN1 10 hserlactone, redox-cofactor, LAP, terpene, NRPS, RiPP-

like,

roteusin

Bradyrhizobium japonicum in8p8 9 hserlactone, redox-cofactor, terpene, T1PKS, RiPP-like,

NRPS,

eta lactone

Bradyrhizobium japonicum is5 9 hserlactone, redox-cofactor, terpene, T1PKS, RiPP-like,

eta lactone

Bradyrhizobium japonicum Is-34 12 redox-cofactor, NRPS, LAP, phosphonate, hserlactone,

NRPS, ter

ene,

roteusin, hserlactone, RiPP-like

Bradyrhizobium japonicum J5 15 hserlactone, redox-cofactor, RiPP-like, terpene, LAP,

NRPS, ectoine,

roteusin,

hos

honate, T3PKS

Bradyrhizobium japonicum NBRC 14783 10 LAP, terpene, hserlactone, RiPP-like, NRPS, redox-

cofacto

roteusin

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

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Bradyrhizobium japonicum SEMIA 5079 11 RiPP-like, proteusin, ectoine, NRPS, terpene, LAP,

T1PKS, redox-cofacto

, hserlactone

Bradyrhizobium japonicum UBMA197 17 hserlactone, phosphonate, proteusin, LAP, RiPP-like,

NRPS, T3PKS, ter

ene, redox-cofacto

Bradyrhizobium japonicum USDA 6 10 hserlactone, redox-cofactor, terpene, LAP, RiPP-like,

NRPS, ectoine,

roteusin

Bradyrhizobium japonicum USDA 38 12 LAP, RiPP-like, NRPS, hserlactone, proteusin, terpene,

redox-cofacto

Bradyrhizobium japonicum USDA 123 20 terpene, redox-cofactor, LAP, hserlactone, T3PKS, NRPS,

RiPP-like, T1PKS,

roteusin, ectoine

Brad

rhizobium

onicum USDA 135

10 hserlactone, RiPP-like, redox-cofactor, NRPS, ectoine,

ter

ene, NRPS

Bradyrhizobium diazoefficiens USDA 110 9 hserlactone, proteusi, RiPP-like, NRPS, ectoine, terpene,

NRPS-like, LAP, redox-cofacto

4 CONCLUSION

This paper systematically studied the genome

sequence of 22 Bradyrhizobium strains, which finds

that the genome size is within the range of

7.50456Mb-10.4577Mb, and the selected genome

integrity is high, all above 97%. The genomes all have

3807 core genes, with an open genome.COG analysis

found that the Pseudomonas genome had a higher

proportion of genes related to the underlying

metabolic functions such as General function

prediction only, Amino acid transport and

metabolism, Transcription. Analysis of the secondary

metabolites found that most of the secondary

metabolites of the strain were T3PKS, peptides,

terpene, and esters. However, due to the length and

the small number of reference whole genomes, the

separation environment, and evolutionary

relationship still need to be strengthened. In later

work, broader Bradyrhizobium strains can be

collected, with more systematic and in-depth research

on the relationship between evolutionary history and

environmental adaptation, evolutionary environment,

and genomic characteristics.

REFERENCES

BROGHAMMER A, KRUSELL L, BLAISE M, et al.

Legume receptors perceive the rhizobial lipochitin

oligosaccharide signal molecules by direct binding[J].

PNAS, 109(34): 13859-13864 (2012).

BARSY M D, FRANDI A, PANIS G L, et al. Regulatory

(pan-)genome of an obligate intracellular pathogen in

the PVC superphylum[J]. The ISME Journal:

Multidisciplinary Journal of Microbial Ecology, 10(Pt

2)2016.

CHAUDHARI N M, GUPTA V K, DUTTA C. BPGA- an

ultra-fast pan-genome analysis pipeline [J]. Scientific

Reports, 6 (2016).

DING W, BAUMDICKER F, NEHER R A. panX: pan-

genome analysis and exploration [J]. Nucleic Acids

Research, 46(1) (2018).

Herridge, D.F., Peoples, M.B. & Boddey, R.M. Plant Soil

311, 1–18 (2008).

HYATT D, CHEN G-L, LOCASCIO P F, et al. Prodigal:

prokaryotic gene recognition and translation initiation

site identification [J]. Bmc Bioinformatics, 11 (2010).

Konstantinidis KT, Tiedje JM. Trends between gene

content and genome size in prokaryotic species with

larger genomes [J]. PNAS, 101 (9): 3160-3165 (2004).

Kadouri D, Jurkevitch E, Okon Y, Castro-Sowinski S.

Ecological and agricultural significance of bacterial

polyhydroxyalkanoates[J]. Crit Rev Microbiol, 31 (2):

55-67 (2005)

L R, V M, P-E F, et al. The bacterial pangenome as a new

tool for analysing pathogenic bacteria[J]. New

microbes and new infections, 7 (2015).

L M, A M, B D, et al. Nodulation of legumes by members

of the beta-subclass of Proteobacteria[J]. Nature,

411(6840) (2001),.

Lodwig EM, Hosie AH, Bourdes A, Findlay K, Allaway D,

Karunakaran R, Downie JA, Poole PS. Amino-acid

cycling drives nitrogen fixation in the legume-

Rhizobium symbiosis [J]. Nature, 422 (6933): 722-726

(2003).

LYU HZ, LIU WJ, HEL, etal. Advances on the study of

gene clusters involved in plant secondary metabolism

[J]. Plant science journal, (in Chinese with English

abstract) ,35 (4):609G610,612G621(2017)

MATT L, S H P, F W M. Evolutionary Rates Analysis of

Leguminosae Implicates a Rapid Diversification of

Lineages during the Tertiary [J]. Narnia, 54(4) (2005).

PARKS D H, IMELFORT M, SKENNERTON C T, et al.

CheckM: assessing the quality of microbial genomes

recovered from isolates, single cells, and

metagenomes[J]. Genome Research, 25(7): 1043-1055

(2015).

Prell J, Poole P. Metabolic changes of rhizobia in legume

nodules [J]. Trends Microbiol, 14 (4): 161-168 (2006)

Stoksta E. Science, 353(6305): 1225-1227 (2016).

SPRENT J I, ARDLEY J, JAMES E K. Biogeography of

nodulated legumes and their nitrogen-fixing

symbionts[J]. New Phytologist, 215(1): 40-56 (2017) .

Pan-genomic Analysis of Bradyrhizobium japonicum

1039

SIMAO F A, WATERHOUSE R M, IOANNIDIS P, et al.

BUSCO: assessing genome assembly and annotation

completeness with single-copy orthologs [J].

Bioinformatics, 31(19): 3210-3212 (2015).

Sun C. Research and development of comparative

genomics visualization system (CGVS) [D]. Beijing:

The University of Chinese Academy of Sciences,

(2013).

Tian CF, Zhou YJ, Zhang YM, Li QQ, Zhang YZ, Li DF,

Wang S, Wang J, Gilbert LB, Li YR, Chen WX.

Comparative genomics of rhizobianodulating soybean

suggests extensive recruitment of lineage-specific

genes in adaptations [J]. PNAS,109(22):8629-8634

(2012).

Wang SM. Whole-genome sequencing and comparative

genomic analysis of Mesorhizobium huakuii strain

7653R [D]. Wuhan: Huazhong Agriculture University

(2014).

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