TANIZAWA, Yasuhiro
Assistant Professor

Genome Informatics Laboratory.

Newly developed DFAST, a pipeline for prokaryotic genome annotation
enabling anyone to make precise annotations of genes- equipped with an additional function for auto-creating a DDBJ registration format

Assistant Prof. Tanizawa specialized in inorganic chemistry up to his Master’s course and shifted to bioinformatics in
his doctoral program after working at his family’s company. He originally developed DDBJ Fast Annotation andSubmission Tool (DFAST), a flexible pipeline enabling anyone from beginners to researchers familiar with information
analysis to analyze microbial genomes simply and with high accuracy. He has been
continuing his work on comparative genome analysis of a wide variety of organisms
Here is a
including lactic acid bacteria (Lactobacillus), liverworts (Marchantia polymorpha L.), andlink to DFAST
novel coronavirus (severe acute respiratory syndrome coronavirus 2).

After many twists and turns,
I decided to follow a path
toward informatics…
I specialized in inorganic chemistry during
the period when I was enrolled at theFaculty of Science, The University of Tokyo,
and then in the Master’s program at theGraduate School, and performed researchon the surface structures of catalysts,
among others. After that, I joined my family’sbusiness and engaged in work including
the building of internal databases, taking
advantage of self-taught knowledge. Being
fond of playing games and operating
computers, I had experience of making
programs to develop my own analytical
tools during the Master’s program. In
2012, I was interested to learn that Prof.

Yasukazu Nakamura at the Genome
Informatics Laboratory, Department ofInformatics, NIG, who was looking fortechnical staff. I applied for a job at thelaboratory and was employed to work on
building websites and databases within
the Nakamura Group. With this as astarting point, I started to pave my way
toward a role of performing research on
bioinformatics. In 2013, I entered the doctoral
program in Computational Biology andMedical Sciences, Graduate School of
Frontier Sciences, The University ofTokyo, and obtained my doctorate.
In the doctoral program, I performed
research on high-accuracy analysis of thewhole genomes of lactic acid bacteria as
the topic for my doctoral dissertation under
the direction of Masanori Arita, former

professor at The University of Tokyo andcurrent professor at NIG (Biological Networks
Laboratory, Department of Informatics)
and director of the DNA Data Bank ofJapan (DDBJ). The lactic acid bacteria,
microorganisms belonging to the
Lactobacillales that are extremely diverse,
can be classified into as many as 200
species. I performed whole-genome
sequencing of individual species of thesebacteria and compared the results. I also
performed an analysis to identify whattypes of characteristic genes are found inwhich groups of these bacteria. At thattime, a variety of genome analysis tools
was available, but they had a number ofproblems, such as being inconvenient andpreviously identified genes turning out tonot actually be genes. Besides, we were1

required to register analyzed genome datain public nucleotide sequence databases
including DDBJ , but the protocols forregistration were complicated, making theregistration of our data difficult.
For this reason, I developed a pipeline,
DFAST, aiming to create an easy-to-use,
high-accuracy analytical pipeline specificallyfor lactic acid bacteria. The first version of
DFAST had a simple design produced by
combining an existing tool with reference
data on these bacteria (such as known
gene sequences and functions) and afile-creating function for DDBJ databaseregistration. Then, I added the species ofanalyzable microorganisms to the tool anddeveloped my original elemental technology.
In this way, I extended the capabilities of
the tool step by step. As the number ofusers increased, the tool gained a growing
reputation because it enabled even
beginners to easily register their data in
DDBJ. It was also held in high esteem by
DDBJ. In this way, my own tool has been
adopted by DDBJ as its official tool, being
effectively used at present.

Aiming to enable annotationsof genetic structures andfunctions to be performed
easily with high accuracy
The first step of the genome analysis
process is the nucleotide sequencing ofDNA. In a typical bacterial genome analysis,
the second step is to assemble thesequenced DNA fragments together toreconstruct the original whole-genome
sequence (genome assembly). With thewide spread of next-generation sequencers
capable of performing rapid sequencing
and improvements in assembly technology,
we became able to acquire highly accurate
genome sequences easily; however, thegenome sequences at this stage are no
more than string data consisting four
letters each representing a nucleotide
base. The next very important step is to
extract biological information (annotation)from the data. Annotation is largely classified
into two types: structural annotation forpredicting regions encoding genes andfunctional annotation for predicting their
biological roles and functions.
Organisms are classified into eukaryotes,
having a nuclear structure in the cell, andprokaryotes, having no such structure.
Animals including humans and plants areeukaryotes, while bacteria such as lactic
acid bacteria and archaea typified bythermophiles/methanogens are prokaryotes.
Structural annotation of prokaryotes isrelatively easy because of their small
genome size and simple gene structure.
On the other hand, functional annotation isbased on the comparison with known
sequences available from public sequence
databases such as DDBJ and UniProtKB,
using them as references for picking up
genes with similar functions to predict thefunction of the target potential gene byanalogy. However, the results obtained byfunctional annotation cannot be usedwithout manual modification due to noiseand variations such as spelling errors inreference data and genes with the samefunction being redundantly registered withdifferent gene names. To address these
problems, in developing DFAST mycolleagues and I started with making
highly reliable reference data that cangenerate reliable results ready to submit to
DDBJ without any further modification.
The initial reference data for lactic acidbacteria were developed by collecting dataon the genomes of these bacteria fromdatabases and extracting the genesequences already identified. Among these
data, similar genes were collected andclassified into groups (clustering). The
names of proteins (gene products) produced
based on genetic information were checked
for each group and erroneous descriptions
were corrected. This work was so
unsophisticated, requiring over 2 months
to compile a huge amount of data into
satisfactory reference data. At that time,reference data for Escherichia coli,
Lactobacillus bifidus, Helicobacter pylori,
and others were prepared in the samemanner. Later, I planned to expand thenumber of species that could be analyzed
by DFAST to all prokaryotes. I collectedsequence data of representative genomes
from well-studied microorganism species
and compiled them into a reference
database. Now DFAST can be used to awider variety of prokaryotes.
The DFAST pipeline is composed of two
main elements: one is the web service,
which is operated by the user through a
web browser (web version), and the otheris an annotation engine element(DFAST_core), working inside the Web
Version. The web version was designedwith the aim of enabling even beginners tooperate it intuitively without being confused.
In particular, by simply filling in data in the
web form according to the given instructions,

Microbial genome analysis pipeline, DFAST,
enabling the user to perform a series of tasksof assembling, annotating, and registering in
DDBJ.
[DDBJ Fast Annotation and Submission Tool
(DFAST)]

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Yasuhiro Tanizawa

Graduated from Department of Chemistry, Faculty of Science, The
University of Tokyo. Completed the doctoral course at The University ofTokyo Graduate School of Computational Biology and Medical Sciences.
Received a Ph.D. in Science. Since 2012, he has been working at
Department of Informatics, National Institute of Genetics (NIG). In 2018, he
was appointed as Assistant Professor after working as a technical staff
member and a project researcher.

Assistant Prof. Tanizawa conducts all daily research activities on a computer.

users can automatically create a necessary
file for registering data in DDBJ. An
additional function to manage many jobs
executed by the user has been integrated.
My experience in developing web service
and databases at the Nakamura Groupwas very helpful in this work.
Another element, DFAST_core acts as
an internally working annotation engine.
DFAST_core uses MetaGeneAnnotator, agene region prediction tool originallydeveloped by Hideki Noguchi, a Project
Professor at Advanced Genomics Center,
NIG, and GHOSTX, a fast search tool foramino acid sequences, developed at
Tokyo Institute of Technology. GHOSTX iscapable of performing computations fasterthan the commonly used BLAST by a factor
of approximately 10, contributing to a
reduction in DFAST execution time. One of
the features of DFAST_core is leveraging
these softwares developed by Japanese
researchers. DFAST_core’s flexible
integration of existing tools and reference
databases enables the user to easily
perform customization, providing one of
the main advantages of DFAST.

Microbial genome annotation
pipeline DFAST was madeopenly accessible to the public.
In 2016, we reported the web version in
our first research paper entitled “Microbial

genome annotation pipeline DFAST” (*1).
The initial web version had been intended
to analyze lactic acid bacteria. Then, an
original annotation engine, DFAST_core,
was developed to expand the targets forsearches to all prokaryotes, resulting in
the prototype of the current DFAST (*2).
Initially, DFAST was operated using myown server, but, in 2021, the web service
moved to the supercomputer at NIG.
Consequently, the analytical performancedramatically improved enough to provide
the result of analysis of a bacterial genome
with a typical size of millions of base pairsin 2 or 3 minutes. Simply by uploading a filecontaining DNA sequences, analysis can be
performed and the results can be provided
at high speed, as indicated by the name
DFAST; therefore, I also recommend
beginners use DFAST. A wide variety ofpipelines other than DFAST have beendeveloped. I recommend DFAST as thefirst step of a series of analysis just to findout what information come out.
DFAST_core has been disclosed forresearchers familiar with information analysis
to execute directly by command operation. It
has advantages such as the pipeline being
flexibly customizable, as well as batch data
being processible at high speed by acommand operation when substantial data
are processed in a relatively large-scale
analysis project. As an advantage in common
with the web version, a file for registrationin DDBJ may be automatically created.

Auto-creation of registration
format and fast processing
appeal to users, achieving thenumber of usages of 80,000
I have been satisfied to hear that DFAST
has been used by many users in Japan andelsewhere. My paper on DFAST is alsoranked first in total citations by field among
the papers recently published (2016–2021)
by researchers at NIG. Web Version has
been used approximately 80,000 times and,at present, approximately 2,000 times amonth. Overall, 30% to 40% of the users are
based outside Japan. DFAST is also usedin the Global Catalogue of Microorganisms(GCM) 10K type strain sequencing project,which is an international genome
sequencing project aiming to determine
the genomes of type strains (strains used
as references in species classification) of
10,000 species of microorganism depositedin bioresource preservation/collection
centers in various countries. Japan
Collection of Microorganisms (JCM), RIKEN
BioResorce Center (BRC), and NBRC of
National Institute of Technology and
Evaluation in Japan are participating inthis project. The results obtained at theinitial state of this project were reported in
papers. This 5-year project is ongoing andsome of the genomes determined by the
project have been disclosed through DDBJ.
Examples of the use in large-scale genome3analysis research include comparative
analysis of E. coli genomes, which we
conducted in joint research with Kyushu
University. In this joint research, to acquiredetailed information on gene functions,reference gene data on E. coli were preparedand DFAST was used to annotate
approximately 800 E. coli genomes isolated
from the bovine intestinal tract. The findings
revealed that enterohemorrhagic E. coli,
which is highly pathogenic to humans, isderived from bovine-residing E. coli andthat it produces specific virulence factors
enabling it to survive in the bovine intestinal
tract. During the course of developing
DFAST, I found that Lactobacillus gasseri,
one of the lactic acid bacteria widely usedin yogurt products, is largely classified into
two groups and proposed a new species
named Lactobacillus paragasseri. Generally,
the name of new species is proposed basedon the strain isolated by a microbiologist ina field survey; in contrast, this research
has a unique advantage that it focused on
information analysis using openly available
data obtained from a database. The efforts
made together with Dr. Ipputa Tada, an
ex-student at Dept. of Genetics of The
Graduate University for Advanced Studies,
SOKENDAI, bore fruit in the discovery of
the new species (*3).
As I mentioned earlier, DFAST’s strength4lies in the fact that annotation and registrationin DDBJ can be easily performed. To register
the genomes of bacteria in GenBank, aninternational genetic sequence databasein the U.S., the PGAP pipeline is available.
However, no standard tool for registering
data in DDBJ was available; I thus takepride in considerably reducing the burden on
the user in registering genome sequences
via DFAST. Moreover, the annotations
made by using DFAST satisfy a given
quality standard; accordingly, the burden
on the curators, who check the content ofdata to be registered, on the side of DDBJ
may be reduced. Actually, in the year of
2020, the share has been so increased
that DFAST was used in 90% of the
genomes of bacteria with annotations
registered in DDBJ.
At present, to publish papers concerning
newly determined DNA sequences inmany academic journals, it is necessary toregister the data in a public sequence
database. I think this requirement is not
only a simply obligation, but also very
important for researchers. It provides
researchers with the advantages of ensuring
the reliability and reproducibility of theirstudies and enabling their own research toinfluence other studies when researchers
refer to their data or reuse it. In that sense,
data registration may be considered as an

essential part of research publication.

DFAST being improved andfurther enhanced with theaim of conducting mutation
analysis of novel coronavirus
Last year, a function (DFAST_QC) tocheck the names of species of genomes
and data integrity was additionallyintegrated into DFAST. In sequence
databases including DDBJ, assessments
are conducted to prevent inappropriate
data from being registered; however, data
describing an erroneous species name orpoor quality genome data may be missed
and registered in some cases. We aimed
to solve this problem via a new function,
DFAST_QC.
In addition, we are endeavoring tointegrate DFAST with the DDBJ dataregistration system. Previously, we madeannotations using DFAST and thenexchanged e-mails with the person in
charge of registration in DDBJ to registerbase sequences. Successful integration
may enable us to transfer the results to
DDBJ by one click for data registration. I
hope that data assessment, which iscurrently conducted manually, becomes
automated to provide a one-stop service

aimed at enabling the user to seamlessly
follow a series of steps from making
annotations to data publication.
NIG started to work on analysis of the
genomes of new variants of novel coronavirus
in cooperation with Shizuoka Prefecture.
In this program, the whole-genome
sequences of specimens collected in
Shizuoka are determined, mutation sites
are identified, and annotations are madeto these sites to make the data publicly
available from DDBJ. I am responsible fordata registration in DDBJ in this programand have already built a customized version
of DFAST for novel coronavirus using theexisting pipeline. NIG is equipped with all
the facilities for genome analysis, agenome sequencing center Advanced
Genomics Center for genome sequencing,a supercomputer capable of large-scale
analysis, and DDBJ, a portal for dataregistration. As a result of this, publishingcorrect data rapidly may contribute to
tracking the route of infection of COVID-19
and identifying its new variants.

Bioinformaticians are a
melting pot of a wide varietyof backgrounds
Four researchers apart from me work at
the laboratory. We are communicating
using an online chat tool among laboratory
members even before the COVID-19
pandemic, so I do not feel that it isinconvenient teleworking from home, aslong as I have access to a computer. The

individual researchers are proceeding with
their own projects. We can report the
progress of our projects and consult or
discuss them with others via the chat toolat any time.
I am very grateful to my boss, Prof.
Nakamura, for letting me pursue my own
research. In the laboratory, a project
intended to support other researchers in
performing genome analysis (Grant-in-Aid
for Scientific Research on Innovative
Areas -“Platform for Advanced Genome
Science (PAGS)”) is also ongoing, throughwhich we perform comparative genome
analysis of liverworts (Marchantia
polymorpha L.), diatoms (Bacillariophyceae),
and others in cooperation with Prof.
Nakamura.
I entered the doctoral program afterworking at my family’s company. Since then,I have been working as a researcher in thefield of bioinformatics. As my backgroundshows, one’s path in life can change at any
time. I believe that there are opportunities
for anyone who seeks a change of direction
to go toward their goal. Researchers in thefield of bioinformatics in particular have awide variety of backgrounds. Some
researchers in this field have always been
engaged in informatics from the beginningof their career. Some other researchers
have shifted their field of research to
informatics because they had to perform
information analysis when conducting
experimental work; with this as a starting
point, they became engaged in informatics.
The background of the members of the
Nakamura Lab is also highly diverse.

Recently, various tools for genome
analysis have become available, lowering
the barrier to conducting information
analysis, which may have contributed to anincrease in the number of researchers inthis field, as mentioned above. Researchers
who disseminate information on how to use
the tool and its usability have considerablyincreased. From my experience, forresearchers unfamiliar with biology to enter
the field of bioinformatics, it is important toacquire the necessary knowledge fromone’s colleagues little by little.

Interviewer: Naoko Nishimura, a science writer
Pictures taken by: Mitsuhiko Kurusu, NIG ORD
Designed by: Naho Kanazawa, NIG ORD■ Cited references■ Other related links*1---------■ DFAST and DAGA: web-based integrated■ Bioinformation and DDBJ Center

July 2021

genome annotation tools and resources
Tanizawa, et al. 2016 BMFH.

*2---------■ DFAST: a flexible prokaryotic genome■ Advanced Genomics Center

annotation pipeline for fastergenome publication

Tanizawa, et al. 2018 Bioinformatics.
*3---------■ Revealing the genomic differences between

two subgroups in Lactobacillus gasseri■ The Department of Genetics of The Graduate

University for Advanced Studies, SOKENDAI

Tada et al. 2017 BMFH.

■ Lactobacillus paragasseri sp. nov., a sistertaxon of Lactobacillus gasseri, based onwhole-genome sequence analyses■ "Platform for Advanced Genome Science"(PAGS)

Tanizawa et al. 2018 IJSEM

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