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Building and Search SysteIIn for aLarge‐ Scale DNA Database

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Abstracto A nat― rlle systern is inadequate for building,integrating
and searching a large―scale databtte in which the number of entries isincreasing in an explos市

e manner.The DNA database of DDBJ(DNAData Bank of Japan)Was built in a flat― Flle system unti1 2 years ago.
GenBank in the United States helped DDBJ to convertthe nat̲flle data

constructed by E)DBJ

to a relational format and lo install the

Annotators Workbench,AWB.AWB is a tool for building the DNA
database with the so― caned CenBank― schema based on a relationalξ誌
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雛t艦 :Ⅷ ∬胤:盤 漁灘
出急ミ聰 諄
a large amounts of DNA data such as Expressed sequence Tags
(ESTs). In addition,both integrating and searching were not carrled
outin the relational database at DDBJ. Recently,we newly developeda hierarchical relational schema for effeclvely building,integrating,and

scarching the DNA database on the relationd databasl management

system,SYBASE,at DDBJ.The schema is named the"DDBJ‐
schemall. The schema a1lowed us to implement window interfaces tocasily build the DNA database. The DNA database built in the
CenBank― schema using AWB is converted into the relational fonnat of
the DDBJ― schema using a restructuring tool at DDBJ. We propo"dastructured SQL‐ pЮ gramming method to implement the restructuHng
tool and so on. The method is developed through the"vicw‖ function
and the contЮ l flow language(CFL)of SYBASEo Moreover, we
proposed two methodologies by which we can execute these softwaretools on UNIX based workstations connected by a computer network.

1. Introduction

DNA(⊇ eoxyribonucleic acid)is genedc information for a1l organisms except RNA viruses.
DNA is kinds of nucleotides designated by A,T,G,and C.The DNA sequence data and its
related infomation can be stored in the fom of a DNA database whch consists of nucleotide

124〃 κfra々 α″f′ ′α′/Lα rg′ Sca々 DNA D´ 忽bas̀

Rgure l.An exarnple ofthe nat̲■le format(DNA and RNA)sequences and related attributes which are bibliographic and biologicalinforrnation. Each nucleotide sequence data is represented as long stHngs of Ais,1「 's,Cis,and
G=s,along with assoCiated biologlcal annotation.

勁 e DNA Data Bank ofJapan(DDBJ)is One of the lnternational Nucleodde Sequence

Databanks where the EMBL(EuЮ pean Molecular Blology Laboratones)Data Lib町 [1,2]andNCBI(National Center fOr Blotechnology lnforlnati01)/LANL(Los Alamos National
LaboratoHes) [3,4,5]are the European and American representatives,respectively. The
AmeHcan DNA databank is called GenBanko We have been collaborating with these two
databanks in many areas through mutual exchanges of data over the international computer
network. The mutual exchange of data on a daily basis is realized between E)】 〕BJ and thecOuabOrative data banks using a nat̲flle fomat(DDBJ/EMBL/CenBank Fonnats).An exalnple
ofthe flat― flle fomatis shown in Figure l.

The DNA database of DDBJ was builtin a flat―

flle system unti1 2 years ago. The flat― rlle

system has been represented by data descnplon rules or a grammar[61 shown in Appendix‑1.
■に nat Flle system is not adequate for building,integrating,and searching a large― scale DNA
database whose entries are continuously increasing in such an explosive rnanner as is occurnng

today.CenBank helped DDBJ to convert the nat̲rlle data constructed by DDBJ stat to a
relational forrnat and to install the Annotator's Workbench,AWB.AWB is a tool for building
the DNA database with the CenBank― Schema[7]based On the relational database management

system,SYBASE[8]. HoweVer, AWB with the GenBank― schema is not adequate for4 Dα ″わαs′″ κ′′
αたα″′′′α′/Larg̀― Sca′′DⅣレ

simultaneous processing large alnounts of DNA data such as Expressed Sequence Tags(ESTs)19].In addi■ on,both integraung and searching are not caried outin the relational database at

DDBJ。 口に number of data submisslons has increased 3 to 4 dmes in the past 2 years at DDBJ.
In addition,lx〕 number of on― line users has also increased lo 4 to 5 times co■ lpared with alat Of
2 years ago,rnaking it difflcult for the staffto process the data efflciently.

This paper will present inethodologies for solving those problems using the relational

database system,SYBASE,in the UNIX en宙Ю nment. We newly developed a relational

schema,DDBJ― schema,lo effectively build,integrate,and search the l)NA database on therelational database management system at DDBJ.¶

he DNA database built with the CenBank―

schema using AWB is converted into the relational format of the DDBJ― schema using a
restructuring tool[10,11]at DDBJ. The restructuring tool is imple面

ented in the"宙 ew"

function,and the contЮ l flow language(CFL)of SYBASE. These software tools can be
executed on UNIX based workstations connected by a computer network.

2. Current System
Figure 2 shows the system conflgura●on for building the DNA Database on the UNIX based

workstation at DDBJ.AWB and the GenBank― schema are software tools developed by LANL
in CenBank.DDBJ:s Reviewers check the form and content of a submitted entw sent by anauthor. Reviewers extract the necessary infomation such as taxonomy,keywords,features
etc.,from ale submitted entry and complete the entry folill according to the intemal(domesdc)
and intemational rules with these tools on the UNIX based workstation.

We developed a program lo siinultaneously process multiple entries at DDBJ,because AWB
does not have a simultaneous processing function for a large amounts of l)NA data. Since
early spHng 1993,wc have been successfully able to process,using this program,many kinds
ofmuldple entries sent by the Human Genome Rttect[9]・

Rgure 2.Current System

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ngure 3.GenBank― SChemaSc睦雁
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The GenBank‐ schema[7]sIЮ wn in Figure 3 has about 60 tables each of which is represented
by a rectangle in the Figure.One entry is parti● oned into smaller entFieS and such entries are
stored according to the tables.These tables can bejoined to each other by thejoin column inthe complex data structure.

Figure 4.Virtual tabies with CenBank‐ schema〃 Kllaた α″′̀r´

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yirrz′ raゎ ′ι∫"ЙView is an altemative way oflooking atthe data in one or more tableso We can consider"view"as a shifting frame which looks like the flat rlle fOmatin the GenBank―

schema.The'view"function provides databank staffand users with an easy way to manage virtual tables despite thecomple対 ty ofale GenBank schema and its condnuous changes.
We developed about 30宙 rtual tables[10]With血 3 GenBank― schema.Each宙 rtual table shownin Figure 4 is represented by a rectangle and it can be connected by column to the accession

numbero Since the SQL language de■ ning‖ view"does not have sufflcient func● on to deinetiviewO',we haVe to respectively derlne more than one virtual table for::accession̲line':,"reference」 ine:1,‖ 10cation̲line",and

quaHrler̲line'1. For example,the"accession̲line:'isdeFlned in two tables. The=taccession̲line'i table has both primary and secondary accession
numbers as columns but each accession number is stored in a different area For that reason,
the Flrst"accession line"table is derlned as being stored with the entry of both the pHmary

accession number and secondary acceSSiOn number.Thё

secondary'iaccessioミ ̲line"table isderlned as being stored with the entry of the pHmary accession number without a second
accesslon number.
We can also sce the real tables which representiltaxonomy・,1ltaxlevelil,and so ono Since

the data ofthe‖ taxonomy"table are all pairs of parent and child nodes in a taxonomy trec,wellanguage(CFLb of

can not search the taxonomy tFee uSing the view function only. The contЮSYBASE discussed in later section is useful for searching the taxonomy tree.

3. Next Ceneration System
We have 2 main goals in establishing an efflcient construction system of the E)NA databaseusing the relational databrase management system at DDBJ.

On‐ line uscr
E‐ MallFigure 5.Next Genera‖ on System

uscr

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irst goal is to implement the newly developed E)DBJ― schema which is more easy

managed than Ⅲc GenBank― schema with its cclmplex data sructure.The DDBJ― schema will becapable of realizing efrlcient simultaneous processing of large amounts of l)NA data and an
efrlcient bullding system for the DNA database.In addidon,it win enable us to easily realizeboth a nexible envirOnment for constructing an integrated database and high perfomance tosupport comfortable on― line service.

獅 e second goalis to implement an effective resmcturing tool by which we can convert血DNA database with the GenBank― schema into relational forlnats with the DDBJ― schema.
Because at DDBJ we are building the DNA database with the GenBank― schema using AWB,it
is ne∝ ssary to convertitinto ule uniFled DNA database.

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3.′Figure 5 shows the system configuration for achieving the previously stated goals on theUNIX based workstation at DDBJ.Since the CenBank― schema has a complex data structure,
the propm for simultaneous pr∝ essing does not provide us with sufflcient efflciency. We aregoing to change the ourput ofthe execu● on into relational fomats with the DDBJ― schema

We developed the Dl)BJ― schema for storing the integrated E》 NA databasc and theresmcturing mechanism which is an interface between the GenBank―
schema.In this way,we were able to transfer about 3,0∞

schema and the DDBJ―

entries with the GenBank― schema

into me DDBJ¨ schema in about onc hour on the UNIX based workstation.
¶に integrated DNA database needs to re∝ ive DNA data with the NCBVGenBank― nat ttle of

NCBIand EMBL― nat rlle of the EMBL Data Library. In addition,we need to convert therelational fomat with the DDBJ― schema into u¨ GenBank nat rlle fOmat and vice versa.

For this reason, we developed conversion programs#1,#2, #3, as wen as twO types ofbuilding systems for the integrated DNA database at DDBJ. If we can change the current
systcm into the next generation system,on‐ line users and E‐ mall users will be able to access theu面 ned DNA database overthe computer network.

3.2 DD3J‐ Sε λθ″αFigure 6 shows the DDBJ― schema which is more easily managed than the CenBank‐

schema.

We successfully developed the hierarchical DDBJ‐ schema宙 th the layers.

Sixteen tables in the first layer are connected horizontally by an accession number,:'acc̲nunl':,and include the contents ofthe nat rlle fOmats. We can provide these tables ibr

integrating and searching the integrated DNA database. The DDBJ―

schema also includes

dictionaries which store biological infollllatiOn,a list of persons,and a list of addresses indle〃 κf″ 々αSca′ ιDNし4 Dara枚 2s̀
′′´′/Larg′ ―"′Figure 6.DDBJ‐ schema

second layero We use the dictionanes to automatically rlllin the blanks ofule 16 tables. In thethird laycL the DDBJ― schema includes system controltables which are shown in the lowest partof Figure 6.T降 system control tables aFe uSed for data restructuring,data transpontion,anddata nOw management.

¶に E"lph shown in Figure 7 compares■ E realtaЫ esin the DDBJ― schema with the virtualtables in the CenBank― schema in tems ofsearch speed andjoin processing.The real tables inthe DDBJ― schema are about 3 to 10 1mes faster than the virtual tables in the GenBank― schema.

Thus,the DDBJ― schema will provide efncient perfomance for on―

10000

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Flgure 7.Perfomance of DDBJ‐ schema

130″.Kiraた α″j̀ra′ /La■ 7̀― Sca″ DNA Darabas′

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FiguFe 8.Window inteface impletrented in X―

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ngure 9 window interface implemented in DB―

Libraryロ

Scα ′′DNA Dα ″れ2sι./Lα rg′ ―tab″ ′′′α′″.κ ′ngure lo.RestructuHng mechanism

We developed two types of window interface to build the 16 tables in the DDBJ― schema.

The rlrst type has an interface,YAMATO,implemented in X―

window and can be used on

UNIX based workstations oVer cOmputer networks. The second type has an interface,

ASUKA,implemented in the DB‐ Library of SYBASE and can be used on characterterminals
over telephone networks.Both also have a window interface similar to the flat Flle forlnat.

We show an exalnple of YAMATO in Rgure 8.The window shows the range ofdata from"l∝ us line"to nsource lineWin the nat■ le fomat.

C)ther lines can be displayed by clicking a rnouse button after users move the pointer to either"REFERENCE"or "FEATURE". ASUKA is shown in Figure 9. 1■

e window shows therange of data from‖ locus̲line"to"segmentline"in the nat file format.Other lines can bedisplayed by pressing the retum kcy of the keyboard after users move the pointer to either
l:Seq!'',=iComment!:1,"Reference!",‖Source!‖ ,ori:Feature!".

g
33 Srryθ ″″ごS2ι ‐Prοg″ ― ノ″This subsec● on descHbes two examples,restructuHng and tree search,ofthe structured SQL‐pЮ grarnming method to be used to implementthe system.This programming is achieved by,garding set oftables as data structure and procedure written in CFL as algorithm.

33.IR̀srr

ε′r′ gFigure 10 shows the restructuHng mechanism[H]fOr interfacing between the GenBank―
schema and the DDBJ― schema.Itisimplemented by the structured SQL― programming method.

The method pro宙 des us with a program including the virtual tables and/or rcal tables as data
structure.The prograln is wHtten in both CFL and SQL.
h real tables with the CenBank‐

schema are transfomed into virtual tables through the"view"function. The virtual tables and the real tables with the DDBJ―

schema are similar toeach other,but they are not exactly the sarne. This is due to liniitations in the capability ofthe::viewl'function as already pointed out. We implemented the data transiation algorithm using

both CFL and SQL ofSYBASE.In our trial system,we successfully restructured fЮ m the132

Sca′ ′DNA Darab´ s′〃 κi″ 々α″f′ ′´′んα′ ―=′GenBank― schemato the DDBJ‐ schema using both the data translation algoHthm and the virtualtables. Ittook one hourto pЮ cess about 3,(XX)entries.

In the curent system,re宙ewers bulld the DNA database incrementally with the GenBank―

schemain the daydme.Ifthey update an entry from a rpnvate"mode to a"distribute"mode,atrigger is Ared and the accession number ofthe entry related to the update is recorded in a tablewith the DDBJ‐ schema.At midnight,the incremental restructuring program is executed andnew entries are automatically transferred from the GenBank― schemato the DDBJ― schema everyday.

3.3.2 rràScarε Й■■Ю tree search functions include an engine to manage taxonomy database. The engine isderlned as recursive join for the taxonomy database.All the taxonomy databases constructedwith the DNA databases ofthe intemalonal DNA databanks are powerful electronic dic●onaneswhich aid in biological research by computer.The taxonomy databasё s are,however notconsistently integrated with a relational forlnat. If we can achieve consiStent uniFlcation of thetaxonomy databases,it will bc useful in comparing many research results,and investigating
future research directions from existent research results.In particular,it will be useful incomparing relationships between phylogenetic trees inferred from molecular data and those
constructed from morphologlcal data.

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FiguFe ll.Tree search mnctiOns

RankinLnanle螂⁚螂並興Node naln

動動動⁚NodヽnameRanking̲nam

Depth

〃 κ′
rala″ ′α α′/La慇 ′―Scaた DNA Dara肋The systein has many kinds of the tree search functions which are lineage,homology,

posteHty,and so on.An the func● Ons are implemented in the structured SQL‐pЮ gramming

method.These functions are shown in Figure ll.
For exalnple,the lineage function scarches for a path from a given■ode to the root■ ode,which docs not have any parent node in the tree structure. The path is a set of nodes found by

searching in the"taxonomy'=table. Appendix‐ 2 shows an example ofthe program that was

implemented in the control flow language of SYBASE caned the::stored procedure'1. Our
approach includes the obiect‑Odented database concept since the procedure is a kind of method
for hiding the table structures of the"taxonomy"table.If we apply an artiflcial intenigenceappЮ ach, we can Obtain another kind of a pЮ gram implemented in prolog[12]. Thisapproach shown in Appendix‑3 is constructed with a smaller program than in the previous

appЮ ach.If we need more complex and higher processing to unify taxonomy databases in the
future,the artiflcial intenigence approach would be preferable in implementing more efEcient
processing.

3′ L%dBα ra″ θJ慇Itis necesstt for the next generatlon system to include the following pr∝ esses:(1)Building the DNA database using AWB on the CenBank―

schema and restructu● ng from ale

GenBank― schema to J℃ DDBJ― schema(2)Maintenance for EMBrS and NCB1/LANLis satellites(3)ProceSSing simultaneously large alnounts ofDNA data(4)Building,integra● on,and on― line service forthe unined DNA database

Figure 12.Two― phase method〃 κJra滋

134

Sc´ た DМ 4 Dα rabα s′′′′′′/ι α′=̀―Figuに 13 0ne― phase method

lf we execute the above processes(1)― (4)on one WOrkstation or a computer,the response ti"eis quite slowo We have to distribute the above processes alnong several computers connectedby a computer network.For exalnple,let us consider the case in which we execute process(1)on the UNIX based workstalon,SUN4/490,(2)on the mini― super computer,CRAY S― MP42,
and(3)― (4)on SUN4/2.In this case,it is necessary to transport the DNA database from

SUN4/490 to SUN4/2,and from CRAY S‐

MP42 to SUN4/2. The former transportation iscarned out wlth a two‐ phase method shown in Figure 12 and the latter with a one― phase method

shown in Figure 13. Since the two phase lnethod does not have the restructuHng pЮ
data transportation,the transportation does■

cess in theot nced more CPU power than the one phasemethodo Since the CRAY S― MP42 has higher performance than the SUN workstation,wechoose the one phase method for the latter transportation.

4。

Conclusion

We have realized effecttve join pЮ cessing with the newly developed DDBJ― schema which iseasy to usc,because its structure looks like the flat rlle fOmat. 獅 eE)1)BJ― schema was
successfully implemented as a hierarchical relational schema with t柿 ee layers.The tables with

the DDBJ‐ schema are 3 1o 10 times faster in processing time than the virtual tables with the

CenBank― schema.Thus,it is possible to pЮ 宙de the SQL― service for on― line and E― mailusers.Moreover,we developed atoolto convert EMBL and NCB1/GenBank―
relational fomat with the DDBJ― schema

fomats into theιDブ Ⅵ4Darabα s′〃 κfraた ´ ′′′α′/Lα ′′ SC´ ′
̀―We have succeeded in restructuring data with the CenBank‐

schema into those with the

DDBJ― schema by use of the structured SQL programming methOd.MOreoveFl inCremental
restuctu五 ng was carried out using the tngger function and the CЮ n systern in UNIX.

We have also succeeded in achieving distributed processing over the computer network to.Asexecute our sotware tools for database building,database integration,an1 0n̲line sewi∝
a result,we have developed a multi‐ server database system over the network.

We developed two kinds of window interfaces for building the E)NA database with the

DDBJ― schema.

The Rice Genome Pr● ect iS planning to building a DDBJ:s satellite for recei宙ng theintcgrated DNA database over the network.The Rice Genome ProieCtiS quite far from DDBJ.
For this reason,itis important to develop a fault tolerance system to consistently transport the

DNA data from DDBJtothe Ricc Cenome R● ectin Case of network failure.
We are planning to move the curentsystem to the next generation system.

Acknowledg口 ents
We wish to thank PЮ l A.Makinouchi of Kyushu University and Dr.M.Arikawa of Hiroshima
City University for their valuable suggestions.This research was carried out at the Fuiitsu―

donated Laboratory of the National lnstitute of Genedcso We also thank all the DDBJ‐ staff
involved in developing the DNA database system for their help.

ReFerences

1]PabiCia Kahn and Grahalln Calneron:EMBL Data Library,Methods in Enzymology,Vol.183,1990【

2]Desmond G.Higgins,Rainer Fuchs,Peter J.Stocher and Graham N.Cameron:The EMBL Data Library,〔
Nucleic Acids Research,Vol.20,Oxford University Press,1992.
[3〕

ChHstian Burks,Michael J Cinkosky,Paul Giina,et al:GenBank:Current Status and Future Direcdons,

Methods in Enzymology,Vol.183, 1990
4]Michael J cinkosky,James W Fickett,Paul Giina,and ChHstian Burks:Electronic Data Publishing and〔

GenBank,Science,Vol.252,1991.
[5]Ch● stian Burks,Michael J.Cinkosky,William M Fischer,Paul Gllna,Jamic E―

D Hayden,Gifford M.

Keen,Michael Kelly,David K五 stofferson and Julie Lawrence:GenBank,Nucleic Acids Research,Vol.20,
Oxford Un市 ersity Press,1992.
[61 GenBank Releasc Notes,Release 69.0,Tape Distribution,InteniGenetics lnc,September 1991
[7]GB‐ Schema News From GenBank,Summer/Autumn 1991,Vo1 4,No 4,cノo lntelliCenetics,Inc,700 East

EI Camino Rcal,Mountain View,CA 94040[8〕

SYBASE Transact‐ SQL Users Guide,Sybase lnc.,May 1989

〃 Fitattm′ ″ a′ ./■ arga‐Scaセ DNADacttse

136

191 Kousaku Okubo,Nachiro Hori,Ryo Mato取 L TOShiyuki Nilyalna,Atsushi Fukushima・ Yuko Koiima andKenthi Matsubara:Large Scale cDNA Sequencing for Analysis ofQuandtative and Qualitative Aspects ofCene
Expression,Nattlre Cenedcs,Vol.2,Nov 1992.
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in Bulledn of the Japan Federation for Culture Collections,Vd.8,No.2(■[11l Httime Ktakami and Yukiko Yalnazaki:In
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1121 Pro10g by BIM(BI― Og)Reference Manual,BIM celgium),1990.

AppendixⅢ l. Gramlnatical Structure of the Flat‐■le Format

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./Larg̀― Scα ル JttVA D′ ′"′Appendix‐ 2. An Example oF PrograΠ ‖ning for a Lineage Search lmplemented

in both SQL and CFLneage@nodename char(80)as

create procedure

deciare@tuples int

declare Ocnt int
select (pcntal
create tab:e tempdb.‖ nea9o(tx :d char(16),tx̲idp char(16),Ieve: tinyint ,:eveLname char(32),node̲name char(30))
create table tempdb.tempitable(tx̲id char(16),tx̲idp char(16),levei tinyint ,ieveLname char(32),node̲name char(80))
create tabie tempdb.work̲table(tX」 d Char(16),tx̲idp char(16),!eve: tinyint ,level̲name char(32),node̲name char(80))
insert tempdb..temptttab:ese!ect tx̲id,txitx̲idp,@cnt,t!̲levname,tx̲nodenamefromtaxonomy,tax!evel

where tx‖and:d=J idbK̲nodenameゃ nOdename

insert tempdb..work̲tablo
select・ from tempdb.temptttab!einsert tempdb.:ineage
se:ect・ fЮ m tempdb̲.temp tableselect()tuples=count(・ )frOm tempdb.temp̲tablodelete tempdb..temp tabie

WHb@tutted釣
begin
selcxl(2cnt=(2Cnt+1
insen tempdb..tema tableselect x.acc̲num,y.tx̲id,y tx̲tx̲idp,@Cnt,tl̲!evname,tx̲nodename
from
where

and

tempdb work tabie x,taxonomy y,tax:eveltx̲J̲id=ti̲idy tttid=x恢 」dp

deiete tempdb work tablel,Sett tempdb.work tabb

se!ect'from tempdb.temp」 able

insert tempdb.‖ neage

se!ect'fЮ m tempdb temptttablo

sebct@tu口 eS→ Ount(・ )from tempdb temptttab:ede:ete tempdb..tempitableend

se!ect'from tempdb.‖ neage
neage,tempdb temptttable,tempdb.work tabiedЮ p tabie tempdb.

〃 κ′ra僣腕J′ ′α′/Lα ′ Scaル D7VA Dα ″わαs′̀̀―Append破 ‐■ Al諸

br a uneage search:‖ 庶 e:l『 雛硼踏‖neage(NODENAME,[lTX=ID,TX TX二 :DP,LEVELNAME,NODENAME]IResultl)■

taxonomy(TX ID,TX TL̲:D,TXttTX̲:DP,NODENAME),
taxleve:(TttTL̲lD,LEVELNAME),

search(TX TX iDP,Resun)
search(TX̲!D,[[TX ID,TX TX̲:DP,LEVELNAME,NODENAME]IResult]):‐taxonomy(TX iD,TX̲TL̲:D,TX TX IDP,NODENAME),
taxlevel(TX TL̲lD,LEVELNAME),
search「 X TX̲:DP,Result)search(TX̲lD,日 )̲

taxonomy(TX̲:D,TX=TL̲:D,TX TX :DP,NODENAME):‐retrieve(db̲taxonomy(TX̲lD,TX̲TL̲lD,TX̲TX̲lDP,NODENAME,̲,̲,̲'̲'̲,̲,̲,̲,̲,̲,̲)),!
taxlevel(TX TL̲:D,LEVELNAME):‐retrieve(dbtttaxlevel(TX̲TL̲:D,LEVELNAME,̲,̲)),!

The'ldb̲taXOnOmy"and‖ db̲taxlevelit tables are two tables of the taxonomy databasedeflned in section 2. A systenl conflguration for the deductive approach is shown in the
fo1lowing Figure:PЮ :Og system(BIM― PrOiog)