Sequence formats and
databases in bioinformatics
• Definitions/Basics
• Sequence formats
• Databases in Biology
Dinesh Gupta
Structural and Computational Biology Group
ICGEB
dinesh@icgeb.res.in
What is Bioinformatics?
•Bioinformatics is the use of computers to solve biological and
biomedical problems.
•Bioinformatics is the application of information technology to mine,
visualize, analyze, integrate, and manage biological and genetic
information, which can then be applied in, among other things,
accelerating drug discovery and development.
•Application of tools of computation and analysis to the capture and
interpretation of biological data.
•Biological Data management and analysis.
•NIH definition of Bioinformatics (http://www.bisti.nih.gov/CompuBioDef.pdf)
Research, development, or application of computational tools and
approaches for expanding the use of biological, medical,
behavioral or health data, including those to acquire, store,
organize, archive, analyze, or visualize such data.
Use of Bioinformatics
• DNA analysis
– Genome sequencing
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Sequence assembly
Sequence/gene annotations
Genefinding/Sequence translation tools
Sequence Similarity searching (eg. BLAST,
ClustalW)
• Comparison between genomes
• Evolution of sequences (Phylogenetic analysis)
• Gene expression
Use of Bioinformatics (..contd.)
• Protein analysis
– Structure
• X-ray crystallography
• Homology based models
• Drug designing
– Sequence
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Sequence similarity
Protein family assignments
Conserved motifs
Proteomics data analysis
Protein Evolution
Uses of Bioinformatics (..contd.)
• Other uses:
– Drug designing
– Vaccine development
– Dairy technology
– Forensics
– Crop improvement
– Designing enzymes for detergents
– Genetic counseling
Bioinformatics: Integration of several fields
Physics
Computer
Science
Biological
Science
Bioinformatics
Mathematics
Chemistry
Statistics
Recent events making bioinformatics more
important
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Exponential expansion of biological information
Expansion of multiple types of information
Cheaper high throughput technologies
Improvement in computation power
Lack of standards/quality
Need for micro and macro analysis
Need for better algorithms
Vast Growth in (Structural)
Data...
but number of Fundementally
New (Fold) Parts Not
Increasing that Fast
Total in Databank
New Submissions
New Folds
Bioinformatics Analysis?
It is like any other lab analysis!
• You need to know your data/input sources
• You need to understand your methods and their
assumptions
• You need a plan to get from point A to point B
• You need to understand your equipment
• You need to be critical and understand potential sources
of error
• You need to interpret your results
• Your results need to be reproducible
• Your results should be testable
References, but not limited to:•
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http://www.ncbi.nlm.nih.gov/About/primer/bioinformatics.html
http://icgeb.res.in/whotdr
http://en.wikipedia.org/wiki/Bioinformatics
• Baxevanis & Ouellette 2001. Bioinformatics: A Practical Guide to the
Analysis of Genes and Proteins 2nd Edition. John Wiley Publishing.
• Gibas & Jambeck 2001. Developing Bioinformatics Computer Skills.
O’Reilly.
• Bioinformatics: Genome Sequence Analysis Mount 2001
• Bioinformatics For Dummies – Claverie & Notredame 2003
• Introduction to Bioinformatics – Lesk 2002
Sequence formats: Basics
• Why different formats?
– Type of information
– Software requirements
– Database requirements
Main file formats used in Bioinformatics
•ASN.1
•EMBL, Swiss Prot
•FASTA
•GCG
•GenBank/GenPept
•PHYLIP
•PIR
ASN 1: Abstract Syntax Notation 1
used by NCBI
Seq-entry ::= set {
class phy-set ,
descr {
pub {
pub {
article {
title {
name "Cross-species infection of blood parasites between resident
and migratory songbirds in Africa" } ,
authors {
names
std {
{
name
name {
last "Waldenstroem" ,
first "Jonas" ,
initials "J." } } ,
{
name
name {
last "Bensch" ,
first "Staffan" ,
initials "S." } } ,
{
name
name {
last "Kiboi" ,
first "Sam" ,
initials "S." } } ,
{
name
name {
last "Hasselquist" ,
first "Dennis" ,
initials "D." } } ,
{
name
name {
EMBL/Swiss Prot
(http://www.ebi.ac.uk/help/formats_frame.html)
• The first line of each sequence entry is the ID definition line which contains entry name,
dataclass, molecule, division and sequence length.
• XX line contains no data, just a separator
• The AC line lists the accession number.
• DE line gives description about the sequence
• FT precise annotation for the sequence
• Sequence information SQ in the first two spaces.
• The sequence information begins on the fifth line of the sequence entry.
• The last line of each sequence entry in the file is a terminator line which has the two
characters // in the first two spaces.
ID
XX
AC
XX
DE
DE
DE
RX
RX
XX
FT
FT
FT
FT
FT
FT
SQ
//
AA03518 standard; DNA; FUN; 237 BP. XX AC U03518;
U03518;
Aspergillus awamori internal transcribed spacer 1 (ITS1) and 18S
rRNA and 5.8S rRNA genes, partial sequence.
rRNA and 5.8S rRNA genes, partial sequence.
MEDLINE; 94303342.
PUBMED; 8030378.
rRNA
<1..20
/product="18S ribosomal RNA"
misc_RNA 21..205
/standard_name="Internal transcribed spacer 1 (ITS1)"
rRNA
206..>237
/product="5.8S ribosomal RNA"
Sequence 237 BP; 41 A; 77 C; 67 G; 52 T; 0 other;
aacctgcgga aggatcatta ccgagtgcgg gtcctttggg cccaacctcc catccgtgtc 60
tattgtaccc tgttgcttcg gcgggcccgc cgcttgtcgg ccgccggggg ggcgcctctg 120
ccccccgggc ccgtgcccgc cggagacccc aacacgaaca ctgtctgaaa gcgtgcagtc 180
tgagttgatt gaatgcaatc agttaaaact ttcaacaatg gatctcttgg ttccggc
237
FASTA
•A sequence in Fasta format begins with a single-line description,
•followed by lines of sequence data.
•The description line is distinguished from the sequence data by a greaterthan (">") symbol in the first column.
•It is recommended that all lines of text be shorter than 80 characters in
length.
>U03518 Aspergillus awamori internal transcribed spacer 1 (ITS1)
AACCTGCGGAAGGATCATTACCGAGTGCGGGTCCTTTGGGCCCAACCTCCCATCCGTGTCTATTGTACCC
TGTTGCTTCGGCGGGCCCGCCGCTTGTCGGCCGCCGGGGGGGCGCCTCTGCCCCCCGGGCCCGTGCCCGC
CGGAGACCCCAACACGAACACTGTCTGAAAGCGTGCAGTCTGAGTTGATTGAATGCAATCAGTTAAAACT
TTCAACAATGGATCTCTTGGTTCCGGC
GCG
•Exactly one sequence
•Begins with annotation lines
•Start of the sequence is marked by a line ending with "..“
•This line also contains the sequence identifier, the sequence length
and a checksum
ID
XX
AC
XX
DE
DE
XX
AA03518 standard; DNA; FUN; 237 BP.
U03518;
Aspergillus awamori internal transcribed spacer 1 (ITS1) and 18S
rRNA and 5.8S rRNA genes, partial sequence.
SQ Sequence 237 BP; 41 A; 77 C; 67 G; 52 T; 0 other; AA03518 Length: 237 Check: 4514
..
1
61
121
181
aacctgcgga
tattgtaccc
ccccccgggc
tgagttgatt
aggatcatta
tgttgcttcg
ccgtgcccgc
gaatgcaatc
ccgagtgcgg
gcgggcccgc
cggagacccc
agttaaaact
gtcctttggg
cgcttgtcgg
aacacgaaca
ttcaacaatg
cccaacctcc
ccgccggggg
ctgtctgaaa
gatctcttgg
catccgtgtc
ggcgcctctg
gcgtgcagtc
ttccggc
GenBank/GenPept
The nucleotide (GenBank) and protein (Gen Pept) database entries
are available from Entrez in this format
•Can contain several sequences
•One sequence starts with: “LOCUS”
•The sequence starts with: "ORIGIN“
•The sequence ends with: "//“
LOCUS
AAU03518 237 bp DNA PLN 04-FEB-1995
DEFINITION Aspergillus awamori internal transcribed spacer
18S
rRNA and 5.8S rRNA genes, partial sequence.
ACCESSION U03518
BASE COUNT 41 a 77 c 67 g 52 t
ORIGIN
1 aacctgcgga aggatcatta ccgagtgcgg gtcctttggg cccaacctcc
61 tattgtaccc tgttgcttcg gcgggcccgc cgcttgtcgg ccgccggggg
121 ccccccgggc ccgtgcccgc cggagacccc aacacgaaca ctgtctgaaa
181 tgagttgatt gaatgcaatc agttaaaact ttcaacaatg gatctcttgg
//
1 (ITS1) and
catccgtgtc
ggcgcctctg
gcgtgcagtc
ttccggc
Phylip format
2 2000
G019uabh ATACATCATA ACACTACTTC CTACCCATAA GCTCCTTTTA ACTTGTTAAA
G028uaah CATAAGCTCC TTTTAACTTG TTAAAGTCTT GCTTGAATTA AAGACTTGTT
GTCTTGCTTG AATTAAAGAC TTGTTTAAAC ACAAAAATTT AGAGTTTTAC
TAAACACAAA ATTTAGACTT TTACTCAACA AAAGTGATTG ATTGATTGAT
TCAACAAAAG TGATTGATTG ATTGATTGAT TGATTGATGG TTTACAGTAG
TGATTGATTG ATGGTTTACA GTAGGACTTC ATTCTAGTCA TTATAGCTGC
• The first line of the input file contains the number of sequences and
their length (all should have the same length) separated by blanks.
• The next line contains a sequence name, next lines are the
sequence itself in blocks of 10 characters. Then follow rest of
sequences.
Other formats
MEGA
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#mega
Title: infile.fasta
#G019uabh
ATACATCATAACACTACTTCCTACCCATAAGCTCCTTTTAACTTGTTAAAGTCTTGCTTG
AATTAAAGACTTGTTTAAACACAAAAATTTAGAGTTTTACTCAACAAAAGTGATTGATTG
ATTGATTGATTGATTGATGGTTTACAGTAGGACTTCATTCTAGTCATTATAGCTGCTGGC
AGTATAACTGGCCAGCCTTTAATACATTGCTGCTTAGAGTCAAAGCATGTACTTAGAGTT
GGTATGATTTATCTTTTTGGTCTTCTATAGCCTCCTTCCCCATCCCCATCAGTCTTAATC
AGTCTTGTTACGTTATGACTAATCTTTGGGGATTGTGCAGAATGTTATTTTAGATAAGCA
AAACGAGCAAAATGGGGAGTTACTTATATTTCTTTAAAGC
#G028uaah
CATAAGCTCCTTTTAACTTGTTAAAGTCTTGCTTGAATTAAAGACTTGTTTAAACACAAA
ATTTAGACTTTTACTCAACAAAAGTGATTGATTGATTGATTGATTGATTGATGGTTTACA
GTAGGACTTCATTCTAGTCATTATAGCTGCTGGCAGTATAACTGGCCAGCCTTTAATACA
TTGCTGCTTAGAGTCAAAGCATGTACTTAGAGTTGGTATGATTTATCTTTTTGGTCTTCT
ATAGCCTCCTTCCCCATCCCATCAGTCT
ReadSeq
Don Gilbert
software@bio.indiana.edu, May 2001
Indiana University, Bloomington, Indiana
WWW
http://www.ebi.ac.uk/cgi-bin/readseq.cgi
http://bioportal.bic.nus.edu.sg/readseq/readseq.html
http://www-bimas.cit.nih.gov/molbio/readseq/
Seqret
A program in EMBOSS suite
The Readseq package can read most common formats: examples of all
these formats are included in the readseq directory. The formats include:
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IG/Stanford, used by Intelligenetics and others
GenBank/GB, genbank flatfile format
NBRF format (SAM modifications cause this to break when sequences do not have a
terminating asterix)
EMBL, EMBL flatfile format
GCG, single sequence format of GCG software
DNAStrider, for common Mac program
Fitch format, limited use
Pearson/Fasta, a common format used by Fasta programs and others
Zuker format, limited use. Input only.
Olsen, format printed by Olsen VMS sequence editor. Input only.
Phylip3.2, sequential format for Phylip programs
Plain/Raw, sequence data only (no name, document, numbering)
MSF multi sequence format used by GCG software
PAUP's multiple sequence (NEXUS) format
PIR/CODATA format used by PIR
Databases in Biology
Need for databases in Biology?
• Need for storing and communicating large datasets
has grown.
• Need to disseminate biological information.
• Provide Organized data for analysis friendly
retrieval.
• Need to make biological data available in computerreadable form.
Different classifications of
databases
• Type of data
– nucleotide sequences
– protein sequences
– proteins sequence patterns or motifs
– macromolecular 3D structure
– gene expression data
– metabolic pathways
– proteomics data
Different classifications of databases….
• Primary or derived databases
– Primary databases: experimental results
directly into database
– Secondary databases: results of analysis of
primary databases
– Aggregate of many databases
• Links to other data items
• Combination of data
• Consolidation of data
Different classifications of databases….
• Technical design
– Flat-files
– Relational database (SQL)
– Exchange/publication technologies (HTML,
CORBA, XML,...)
• Each one of the above are inter
convertible
Different classifications of databases….
• Availability
– Publicly available, no restrictions
– Available, but with copyright
– Accessible, but not downloadable
– Academic, but not freely available
– Proprietary, commercial; possibly free for
academics
Different classifications of databases….
• Content
– Protein/DNA/RNA/miRNA etc.
– Family: kinases
– Common physical properties: membrane bound,
mitochondrial proteins
– Common chemical properties: Proteases, reductases
etc.
– Sequences of a particular genome/species: e.g.
Influenza sequences, plasmodium sequences etc.
– Motifs/domains
Where to look for databases?
• Search Engines
• Journals related to Bioinformatics
• Websites like:
– http://www.biophys.uni-duesseldorf.de/BioNet/Pedro/rt_all.html
– www.expasy.ch
– Several others websites
NAR DB issue 2010
• 58 new dbs since last year!
• Total >1230!
• (http://www.oxfordjournals.org/nar/databas
e/a/
• Complete list
– Searchable
– http://nar.oxfordjournals.org/cgi/content/full/gk
m1037/DC1/1 (html format), also as
downloadable word file)
http://www3.oup.co.uk/nar/database/c/
Database searching tips
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Look for links to Help or Examples
Always check update dates
Level of curation
Try Boolean searches
Be careful with UK/US spelling differences
– leukaemia vs leukemia
– haemoglobin vs hemoglobin
– colour vs color
Exercise
• Retrieve sequences from sequence
databases
• Convert sequence formats
• Study different formats and flow of
information