Molecular Evolution: Computer Analysis of Protein and Nucleic Acid Sequences

725 Pages·1990·11.92 MB·English

by  Abelson J.N.

Preface
Since its initiation, Methods in Enzymology has tried to keep abreast of
developments in all areas important to biochemistry. Increasingly, this has
meant moving into the realm of molecular biology. The main objective has
remained the same, nonetheless: putting ready-to-use methods into the
hands of the at-the-bench scientist, This volume is no exception. Still, this
may be the first Methods in Enzymology volume in which the expression
“pH” is never mentioned and the word buffer, if used at all, has nothing to
do with aqueous solutions!
The past decade has witnessed nothing less than a flood of nucleic acid
and protein sequence data, the management of which would simply be
impossible without computers. The chapters in this volume address a
variety of areas in which computers are used to manage and manipulate
sequences. The manipulations include searching, aligning, and determin-
ing the significance of similarities, as well as the construction of phyloge-
netic trees that show the evolutionary history of related sequences. This
relatively new field of sequence-computing has stimulated interest from a
variety of more established disciplines as is apparent from the diverse
backgrounds of the contributing authors. Thus, investigators in mathemat-
ics and statistics, taxonomy and cladistics, and protein and nucleic acid
chemistry are all represented, each bringing different perspectives and
insights. All the authors were asked, however, to make an effort to write for
the biochemist or molecular biologist who wants to analyze, search, or
manipulate nucleic acid or protein sequence data. Some have met this
charge more aptly than others, and in some instances readers must be
prepared to go the extra mile to find genuine satisfaction. Often this will
mean mastering new terms and jargon, the troublesome persiflage of all
specialized fields. Bootstraps and jackknifes, informative sites and k-tuples,
NP-complete and NP-completeness are all words with simple enough
meanings, and it would be a mistake for readers to turn away from the
methods described merely because of an alien nomenclature or notation.
Thus, bootstraps and jackknifes are computer-intensive stastistical proce-
dures for estimating the quality of a data set. Informative site is a term used
in strict parsimony analysis for those arrays of characters in a set of
sequences that allow a single, simple interpretation. k-Tuples are merely
sets of units: duplets, triplets, quartets, and so on. NP-complete is an
. . .
Xl11
xiv PREFACE
expression used by computer scientists to indicate a set of problems it may
not be possible to solve exactly by dynamic programming. The phylogeny
problem may be NP-complete. I must confess that not too long ago I had
not the faintest notion of what most of these expressions implied.
It was agreed in advance that the computer programs described in this
volume would be made available by the contributing authors, usually only
for the cost of materials (tapes or diskettes) and shipping. Readers must
understand, nonetheless, that there are often problems in transporting
programs from one kind of computer to another and that differences in
operating systems often present stumbling blocks. The authors are very
interested in the community using their programs, however, and they are
prepared to help with any problems that may ensue. Naturally they would
like to hear, also, when the programs work well.
The sequence -computer field is a very fast-moving one, and every
effort was made to produce this volume as rapidly as possible so the
methods would be timely. In this regard, I must thank the authors for
adhering to a set of rigid deadlines. Special thanks are due, also, to Karen
Anderson, who managed many aspects involving the manuscripts and
without whom this volume would likely never have materialized.
RUSSELL F. DOOLITTLE
Contributors to Volume 183
Article numbers are in parentheses following the names of contributors.
Affiliations listed ar-z current.
YVON ABEL (26), Centre de Recherches D-6900 Heidelberg, Federal Republic of
Mathematiques, Universite de Montreal, Germany
Montreal, Quebec H3C 3J7. Canada ROBERT CEDERGREN (19, 26), Departement
WAYNE F. ANDERSON (27), Department of de Biochimie, Universite de Montreal,
Biochemistry, Vanderbilt University, Montreal, Quebec H3C 357, Canada
Nashville, Tennessee 37232 JEAN-MICHEL CLAVERIE (15) Computer
PATRICK ARGOS (21), European Molecular Science Unit, Institut Pasteur, 75724 Paris
Biology Laboratory, D-6900 Heidelberg, Cedex 1.5. France
Federal Republic of Germany JOHN F. COLLINS (30), Biocomputing Re-
DAVID J. BACON (27), Department of Bio search Unit, Department of Molecular Bi-
chemistry, University of Alberta, Edmon- ology, University of Edinburgh, Edinburgh
ton, Alberta T6G 2H7, Canada EH9 3JR, Scotland
WINONA C. BARKER (3, 20), Protein Identi- ANDREW F. W. COULSON (30), Biocomput-
fication Resource, National Biomedical ing Research Unit, Department of Moiecu-
Research Foundation, Georgetown Univer- lar Biology, University of Edinburgh, Ed-
sity Medical Center, Washington, DC. inburgh EH9 3JR, Scotland
20007 JOHN CZELUSNIAK (37), Department of
GEOFFREY J. BARTON (25) Laboratory of Anatomy and Cell Biology, Wayne State
Molecular Biophysics, University of Ox- University School of Medicine, Detroit,
ford, Oxford OXI 3QU. Engiand Michigan 48201
DAVID BENTON (l), IntelliGenetics, Incorpo- RUSSELL F. D~OLITTLE (6, 23, 41), Center
rated, Mountain View, Cahfornia 94040 for Molecular Genetics, University of Cali-
B. EDWIN BLAISDELL (24), Department of fornia, San Diego, La Jolla, California
Mathematics, Stanford University, Stan- 92093
ford, Cahfornia 94305 MANFRED EIGEN (32), MaxPlanck-Institut
TOM L. BLUNDELL (42), Laboratory of MO- fir Biophysikalische Chemie, D-3400 Got-
lecular Biology, Department of Crystallo tingen. Federal Republic of Germany
graphy, Birkbeck College, University of DAVID EISENBERG (9), Molecular Biology
London, London WCIE 7HX, England Institute, University of California, Los An-
LYDIE BOUGUELERET (15), Computer geles, Los Angeles, California 90024
Science Unit, Institut Pasteur, 75724 Paris DA-FEI FENG (23, 4 l), Center for Molecular
Cedex IS, France Genetics. University of Caltfornia. San
VOLKER BRENDEL (24), Department of Diego, La Jolla, California 92093
Mathematics, Stanford University, Stan- WALTER M. FITCH (38), Department of
ford, California 94305 Ecology and Evolutionary Biology, Uni-
JOSEPH P. BROWN (7), Genetic Systems Cor- versity of California, Irvine, Irvine, Cali-
poration, Seattle, Washington 98121 fornia 92717
CHRISTIAN BURKS (I), Theoretical Biology DANIEL GAUTHERET (19), Departement de
and Biophysics Group, Los Alamos Na- Biochimie, Universite de Montreal, Mon-
tional Laboratory, Los Alamos, New Mex- treal, Quebec H3C 3J7, Canada
ico 8 7545 DAVID G. GEORGE (3, 20), Protein Identi-
GRAHAM CAMERON (2), The European MO- fication Resource, National Biomedical
lecular Biology Laboratory Data Library, Research Foundation, Georgetown Univer-
ix
X CONTRIBUTORS TO VOLUME 183
sity Medical Center, Washington, D.C. D-6900 Heidelberg, Federal Republic of
20007 Germany
TAKASHI GOJOBORI (33), Department of SAMUEL KARLIN (24), Department of Math-
Evolutionary Genetics, National Institute ematics, Stanford University, Stanford,
of Genetics. Mishima 411, Japan California 94305
MORRIS GOODMAN (37), Department of SUZANNE M. KEHOE (37), Department of
Anatomy and Cell Biology, Wayne State Anatomy and Cell Biology, Wayne State
University School of Medicine, Detroit, University School of Medicine, Detroit,
Michigan 48201 Michigan 48201
MANOLO GOUY (40), Laboratoire de Bibme- BORIVOJ KEIL (4), Institut Pasteur, 75015
trie, Universite Lyon I, 69622 Villewr- Paris, France
banne Cedex, France MOTOO KIMURA (33), Department of Popu-
MICHAEL GRIBSKOV (9), BRI-Basic Re- lation Genetics, National Institute of Ge-
search Program, National Cancer netics, Mishima 411. Japan
Institute- Frederick Cancer Research Fa- HIROHISA KISHINO (34), The Institute of
cility, Frederick, Maryland 21701 Statistical Mathematics, Minato-ku.
Tokyo 106. Japan
NOMI L. HARRIS (16), Laboratory of Com-
puter Science, Massachusetts Institute of CECILIA LANAVE (35), Centro Studi sui Mi-
Technology, Cambridge, Massachusetts tocondri e Metabolism0 Energetico, CNR,
02139 Bari. 70126 Bari, Italy
MASAMI HASEGAWA (34), The Institute of GAD M. LANDAU (31), Division of Com-
Statistical Mathematics, Minato-ku, puter Sciences, Polytechnic University,
Tokyo 106, Japan Brooklyn, New York 11201
JOTUN HEIN (39) Centre de Recherche de CHARLES B. LAWRENCE (a), Department of
Mathematiques Appliques, UniversitP de Cell Biology, Baylor College of Medicine,
Houston, Texas 77030
Montreal, Montreal, Quebec H3C 357,
Canada WEN-HSIUNG LI (40) Center for Demo-
graphic and Population Genetics, Health
STEVEN HENIKOFF (7), Fred Hutchinson
Science Center at Houston, University of
Cancer Research Center, Seattle, Wash-
Texas, Houston, Texas 77225
ington 98104
ROLAND LOTHY (9), Molecular Biology In-
LOIS T. HUNT (3, 20), Protein IdentiJcation stitute, University of Caltfornia, Los An-
Resource, National Biomedical Research
geles, Los Angeles, California 90024
Foundation, Georgetown University Medi-
cal Center, Washington, D.C. 20007 FRANCOIS MAJOR (19), Departement d’ In-
formatique et Recherche Operationnelle,
JOHN A. JAEGER (17), Department of Chem- Universite de Montreal, Montreal, Quebec
istry, University of Rochester, Rochester, H3C 3J7, Canada
New York 14627
HUGO M. MARTINEZ (IS), Department of
MARK S. JOHNSON (42), Laboratory of Mo- Biochemistry and Biophysics, University
lecular Biology, Department of Crystallo- of California, San Francisco, San Fran-
graphy, Birkbeck College, University of cisco, California 94143
London, London WClE 7HX. England
NANCY D. MONCRIEF (37), Department of
ROBERT JONES (14), Thinking Machines Biology, University of Virginia, Charlottes-
Corporation, Cambridge, Massachusetts ville, Virginia 22901
02142
ETSUKO N. MORIYAMA (33), Department of
PATRICIA KAHN (2), The European Molecu- Evolutionary Genetics, National Institute
lar Biology Laboratory Data Library, of Genetics, Mishima 411, Japan
CONTRIBUTORS TO VOLUME 183 xi
M~~suo MURATA (22), Department of Bio- RODGER STADEN (10, 12), Laboratory of
chemistry, University of Georgia, Athens, Molecular Biology, Medical Research
Georgia 30602 Council, Cambridge CB2 2QH, England
RUTH NUSSINOV @I), Sackler Institute of GARY D. STORMO (13), Department of Mo-
Molecular Medicine, Tel pviv University, lecular, Cellular, and Developmental Biol-
Tel Aviv 69978, Israel, and Laboratory of ogy, University of Colorado, Boulder, Col-
Mathematical Biology, National Cancer orado 80309
Institute, National Institutes ofHealth. Be- WILLIAM R. TAYLOR (29), Laboratory of
thesda, Maryland 20892 Mathematical Biology, National Institute
WILLIAM R. PEARSON (5), Department of for Medical Research, Medical Research
Biochemistry, University of Virginia, Council, London NW7 IAA, England
Charlottesville, Virginia 22908
DOUGLAS H. TURNER (17), Department of
GRAZIANO PESOLE (35), Dipartimento di Chemistry, University of Rochester, Roch-
Biochimica e Biologia Molecolare, Univer- ester, New York 14627
sita di Bari, 70126 Bari, Italy
MAUNO VIHINEN (28) Department of Bio-
GIULIANO PREPARATA (35), Dipartimento chemistry, University of Turku, SF-20500
di Fisica, Universitd di Milano, 20100
Turku. Finland
Milano. Italy
MARTIN VINGRON (21), European Molecu-
CECILIA SACCONE (35), Dipartimento di
lar Biology Laboratory, D-6900 Heidel-
Biochimica e Biologia Molecolare, Univer-
berg, Federal Republic of Germany
sitd di Bari, 70126 Bari, Italy
NARUYA SAITOU (36), Department of An- Uzr VISHKIN (31), Institute for Advanced
thropology, Faculty of Science, The Uni- Computer Studies, University of Mary-
land, College Park, Maryland 20742, and
versity of Tokyo, Hongo, Bunkyo-ku,
Tokyo 113, Japan Department of Computer Science, School
of Mathematical Sciences, Tel Aviv Uni-
ANDREJ SALI (42), Laboratory of Molecular versity, Tel Aviv 69978, Israel
Biology, Department of Crystallography,
Birkbeck College, University of London, JAMES C. WALLACE (7), Fred Hutchinson
Cancer Research Center, Seattle, Wash-
London WCIE 7HX? England
ington 98104
DAVID SANKOFF (26), Centre de Recherches
Mathematiques, Universite de Montreal, MICHAEL S. WATERMAN (14), Departments
Montreal, Quebec H3C 3J7, Canada of Mathematics and Molecular Biology,
University of Southern California, Los An-
ISABELLE SAUVAGET (15), Computer
geles, California 90089
Science Unit, Institut Pasteur, 75 724 Paris
Cedex 15, France PATRICK L. WILLIAMS (38), College of
PERIANNAN SENAPATHY ( 16), Biotechno Veterinary Medicine, North Carolina
State University, Raleigh, North Carolina
logy Center, University of Wisconsin,
Madison, Wisconsin 53706 27606
MARVIN B. SHAPIRO (16), Laboratory of RUTHILD WINKLER-OSWATITSCH (32),
Statistical and Mathematical Methodol- Max-Planck-Institut fir Biophysikalische
ogy, Division of Computer Research and Chemie, D-3400 Gdttingen, Federal Re-
Technology, National Institutes of Health, public of Germany
Bethesda, Maryland 20892 MICHAEL ZUKER ( 17), Division of Biological
JOHN C. W. SHEPHERD (1 l), Cell and Molec- Sciences, National Research Council of
ular Biology Laboratory, University of Canada, Ottawa, Ontario KlA OR6, Can-
Sussex, Brighton BNl 9QG, England ada
r11 GENBANK 3
[l] GenBank: Current Status and Future Directions
&I CHRISTIAN BURKS, MICHAEL J. CINKOSKY, PAUL GILNA, JAMIE
E.-D. HAYDEN, YUKI ABE, EDWIN J. ATENCIO, STEVE BARNHOUSE,
DAVID BENTON, CONNIE A. BUENAFE, KAREN E. CUMELLA, DAN B.
DAVISON, DAVID B. EMMERT, MARY Jo FAULKNER, JAMES W. FICKETT,
WILLIAM M. FISCHER, MARK GOOD, DEBORAH A. HORNE, F. KAY
HOUGHTON, PRAFUL M. KELKAR, TOM A. KELLEY, MICHAEL KELLY,
MELINDA A. KING, BERNARD J. LANGAN, JEFFREY T. LAUER, NATALIE
LOPEZ, CONRAD LYNCH, JANET LYNCH, JANET B. MARCHI, THOMAS G.
MARR, FRANCES A. MARTINEZ, MIA J. MCLEOD, PAT A. MEDVICK,
SANTOSH K. MISHRA, JOHN MOORE, CHRISTINE A. MUNK, SOCORRO M.
MONDRAGON, KEVIN K. NASSERI, DEBRA NELSON, WILL NELSON, TAN
NGUYEN, GLORIA REISS, JOHN RICE, JULIE RYALS, MARGARITA D.
SALAZAR, STEPHEN R. STELTS, BRIAN L. TRUJILLO, LAURIE J.
TOMLINSON, MARK G. WEINER, FRANK J. WELCH, SUSAN E. WIIG,
KATHERINE YUDIN, AND LARRY B. ZINS
The GenBank’ database provides a collection of nucleotide sequences
as well as relevant bibliographic and biological annotation. We present an
updated view of the size and scope of the database, and we also describe
recent developments in the strategies, protocols, and software for collect-
ing, maintaining, and distributing the data.
Introduction
GenBank, the genetic sequence data bank, is chartered to provide a
computer database of all published (and, increasingly, unpublished) DNA
and RNA sequences and related bibliographic and biological information.
The project is funded through an NIGMS contract with IntelliGenetics,
Inc. (IG) which, in turn, contracts with the DOE acting on behalf of Los
Alamos National Laboratory (LANL). The project is funded with cospon-
sorship from other institutes of the National Institutes of Health, National
Library of Medicine (NLM), DRR, USDA, NSF, DOE, and DOD. Data
collection and distribution are carried out in collaboration with the EMBL
Data Library (EMBL) and the DNA Data Bank of Japan (DDBJ). Inquiries
’ “GenBank” is a registeredt rademark of the U.S. Department of Health and Human
services.
Copyright 0 1990 by Academic Pra, Inc.
METHODS IN ENZYMOLOGY, VOL. 183 All rights of sproduction in any form reserved.
4 DATABASES 111
regarding data distribution and release should be addressed to IG,2 inqui-
ries regarding data submissions and collection should be addressed to
LANL.3
Background. Computer databases offer several advantages for collect-
ing, maintaining, analyzing, and distributing data sets: compact storage,
low-error rates for data archiving or transmission, more precise specifica-
tion and organizatioh of data, less effort in varying complex queries, and
less effort in reorganizing data. We have previously discussed both the
scientific community’s move 10 years ago to apply these advantages to
nucleotide sequence data and the resulting establishment of the GenBank
database. The database was chartered as described above and intended to
provide4p5 (1) an archive, for long-term storage and preservation of se-
quence data; (2) retrieval of nucleotide sequences, with delineation by
sequence-specific, bibliographic, physical, or functional criteria; and (3) a
research platform, for examination and analysis of sequences grouped by
sequence-specific or annotation-specific criteria.
Over the past several years there have been a number of developments
in the database project. GenBank has passed into a second contract period
with considerably expanded resources, allowing us to address many of the
issues that arose as challenges in the early phase of the project. The
nucleotide sequence database collaboration has recently been extended
from GenBank and EMBL6,’ to include DDBJ,* which began operations in
1987.
The unanticipated exponential growth in the amount of nucleotide
sequence data being published as well as the possibility of another order of
magnitude increase in the number of sequences being determined- as
emphasized in recent discussions of the possibility of a human genome
* Postal service: GenBank; IntelliGenetics, Inc.; 700 El Camino Real East; Mountain View,
CA 94040. Electronic mail: “[email protected]”. Telephone: [phone].
3 Postal service: GenBank, T- 10, MS K7 10, Los Alamos National Laboratory; Los Alamos,
NM 87545. Electronic mail: “genbank%[email protected]” (general); or “gbsub%[email protected]”
(data submissions and questions regarding submissions). Telephone: [phone]. ,’
4 C. Burks, J. W. Fickett, W. B. Goad, M. Kaneshisa, F. I. Lewitter, W. P. Rindone, C. D.
Swindell, C.-S. Tung, and H. S. Bilofsky, Comput. Appl. Biosci. 1,225 (1985).
5 J. W. Fickett and C. Burks, in “Mathematical Models for DNA Sequences” (M. S. Water-
man, ed.), p. 1. CRC Press, Boca Raton, Florida, 1988.
6 G. Cameron, Nucleic Acids Res. 16, 1865 (1988).
7 P. Kahn and G. Cameron, this volume [2].
* S. Miyazawa, in “Computers and DNA” (G. I. Bell and T. Marr, eds.), p. 47. Addison-
Wesley, New York, 1989.
111 GENBANK 5
initiative9J0 and other large-scale sequencing projects-has led us (and
other$ to focus on the need for alternatives for processing the much larger
streams of data coming into the database. r1,r2 Similarly, the recognition of
a need for improved cross-refereacing and, eventually, automatic cross-
linking of GenBank and related databases (which figures heavily in recent
discussions of a matrix of biological knowledge)r3 has led us to consider
alternative data representations that would provide the basis for such
cross-linking. Finally, computer science tools (e.g., relational databases)r4
previously in use in other contexts have evolved to the point that it is
appropriate to begin exploring their application to GenBank.
Focus of Chapter. We begin by providing an update on the kinds and
amount of data present in the database and the objectives (completeness,
timeliness, and depth of annotation) of GenBank with respect to the user
community. We describe our two primary thrusts at this time: shifting our
data collection effort over to a system that relies on direct, computer-read-
able submissions from authors, and restructuring the database in the con-
text of a relational database management system (RDBMS). An overview
of the current media and formats for data distribution is given. We close
with a description of the directions in which the database effort is moving
as well as a discussion of the challenges ‘facing us now.
Current Span and Size of Database
What Data Are in the Database? The primary datum in the database is
nucleotide (DNA and RNA) sequences (i.e., actggcagacagggtcatt . . . ).
Each contiguous sequence determined by a single research group and
submitted (or published) as a single entity is maintained as such. Occa-
sionally, when more than one sequence for the same gene in the same
organism is available, and the sequences overlap, a merged view of the
sequences is presented in the distributed versions of the database.
9 B. M. Alberts, D. Botstein, S. Brenner, C. Cantor, R. F. Doolittle, L. Hood, V. A.
McKusick, D. Nathans, M. V. Olson, S. Orkin, L. E. Rosenberg, F. H. Ruddle, S. Tilgh-
man, J. Tooze, and J. D. Watson, “Mapping and Sequencing the Human Genome.”
National Academy Press, Washington, D.C., 1988.
lo U.S. Congress, Office of Technology Assessment, “Mapping Our Genes-The Genome
Projects: How Big, How Fast?” U.S. Govt. Printing Office, Washington, D.C., 1988.
ii L. Phillipson, Nature (London) 332,676 (1988).
I2 G. I. Bell and T. Mat-r, eds., “Computers and DNA.” Addison-Wesley, New York, 1989.
I3 H. J. Morowitz and T. F. Smith, “Report of the Matrix of Biological Knowledge Work-
shop.” Santa Fe Institute, Santa Fe, New Mexico, 1987.
I4 C. J. Date, “An Introduction to Database Systems,” 4th Ed. Addison-Wesley, Reading,
Massachusetts, 1986.
6 DATABASES 111
The database provides the bibliographic context of the sequence. This is
most often represented by a specific journal citation, although GenBank
accepts and cites submissions of original data published in books, theses,
and other sources. Increasingly, unpublished nucleotide sequences are ap
pearing in the database,15 although most often directly tied to a publication
that describes the sequence without presenting it explicitly. Unpublished
submissions are cited as such.
The physical context of a sequence, i.e., the organism, chromosome,
map position, etc., that describes its origin in viva is included when known
and made available to GenBank. Official nomenclature lists and map
assignments are beginning to be made available to us in a form that allows
GenBank to dynamically maintain proper, uniform values for these data
items. The functional context of a sequence (or parts of a sequence) is also
annotated in the database. A good example is protein-coding regions,
which are annotated to support automatic extractioni6*i7 of the coding
regions from the sequences in which they are embedded (we use such a tool
for checking the integrity of coding regions in the database). Most of this
information is presented in the GenBank FEATURES table. Finally, a
limited number of data items providing the administrative context of a
sequence are provided. These indicate when data were last revised, the
degree of review the data have received from GenBank stalf, etc.
A sample GenBank entry in the current magnetic tape flat file distribu-
tion format is presented in Fig. 1. A more detailed presentation of the
various data items has been given previously5; up-to-date descriptions and
planned changes can be found in the release notes accompanying GenBank
releases.2
How Many Data Are in the Database? The current release (Release
61.0) of the database contains about 3.5 X 10’ nucleotides (based on over
4.0 X 10’ nucleotides, with the reduction being due to the merging de-
scribed above) in about 2.9 X lo4 entries. The exponential growth rate of
nucleotide sequence data over the past 10 years has been characterized
elsewhere’* (see also Fig. 3). The database includes 150 entries containing
104 or more contiguous nucleotides; 5 of these entries contain over lo5
contiguous nucleotides. There are about 1200 organisms (counting indi-
vidual animal, plant, and microorganism species as well as viruses) repre-
I5 C. Burks, in “Biomolecular Data: A Resource in Transition” (R. R. Colwell, ed.), p. 327.
Oxford University Press, Oxford, 1989.
I6 J. W. Fickett, Trends Biochem. Sci. 11, 190 (1986).
I7 J. W. Fickett, Trends B&hem. Sci. 11, 382 (1986).
I8 C. Burks, in “Biomolecular Data: A Resource in Transition” (R. R. Colwell, ed.), p. 17.
Oxford University Press, Oxford, 1989.
111 GENBANK 7
LOCUS HUMCRYGAl 465 bp ds-DNA PRI 15-MAR-1989
DEFINITION Human gamma-A-crystallin gene (gamma-G5), exons 1 and 2.
ACCESSION Ml7315 ,_
KEYWORDS crystallin; gamma-crystallin.
SEGMENT 1 df 2
SOURCE Human fetal liver DNA, clone lambda-16G3.
ORGANISM Homo sapiens
Eukaryota: Metazoa; Chordata: irertebrata; Tetrapoda: Marmnalia;
Eutheria: Primates; Anthropoidea; Hominoidea: Hominidae.
REFERENCE 1 (bases 1 to 465)
AUTHORS Meakin,S.O., Du,R.P.,, Tsui,L.-C. and Breitman,M.L.
TITLE Gamma-crvstallins of the human eve lens: Expression analvsis of
five members of the gene family -
JOURNAL Mol. Cell. Biol. 7, 2671-2679 (1987)
STANDARD full staff-entry
COMMENT
FEATURES from to/span description
PePt 109 117 gamma-A-crystallin, axon 1 /nomgen="CRYG5"
/map- "2q33-q35"
219 + 461 ganuna-A-crystallin, exon 2
IVS 118 218 CRY-g-A intron A
IVS 462 > 465 CRY-g-A intron B
refnumbr 2 2 numbered 1 in (11
BASE COUNT 91 a 137 c 111 g 126 t
ORIGIN Chromosome 2q33-35.
1 aggtcccttt tgtgttgttt ttgccaacac agcagcttcc ctgctatata taccagttgc
61 ccctttgtcc ctatcatact agatgctaat caccctctgt caacaaccat ggggaaggtg
121 agcctgtgga ggtgctgtgc catgtctatt gggggtctgt ggtgtgtggg gatgttcctt
181 ccaoctaact atctactatc accttatttc tacctcagat caccttctac gaggaccgag
241 actftcaggg <cgctgc<ac aattgcatca gtgactgccc caacctgcgg gtctacttca
301 gccgctgcaa ct'ccatccga gtagacagcg gctgctggat gctctatgag cgtcccaatt
361 accagggcca ccagtacttc ctgcgccgag gcaagtaccc cgactatcag cactggatgg
421 gcctcagcga ctcggtccaa tcctgccgta taattcctca tgtga
FIG. I. Sample GenBank entry. The entry is in the standard line-type format used in the
magnetic tape distribution of GenBank.
sented in the database. Of the sequences for which feature annotation is
available, roughly one-half represent protein-coding regions. However,
many other functional categories are also well represented: for example,
there are over 400 Alu repeats annotated in the database and over 1600
tRNA gene sequences.
There has been a greatly enhanced interest in “complete” genomes over
the past few years. There are enough Escherichia coli DNA sequence data
in GenBank to account for roughly 28% of the E. coli genome (though the
apparent percentage of the genome covered would be smaller if potentially
overlapping segments were merged). On the other hand, there are only
enough Homo sapiens DNA sequence data in GenBank to account for, at
most, 0.2% of the human genome. If one includes viruses, plasmids, and
organellar chromosomes, there are about 150 “complete” genomes repre-
sented in the database, but the highly parasitic nature of these latter entities
would require that one include a significant amount of host genetic mate-
rial in the complete specification of the life cycle.