Introduction to Biological Databases

1. Introduction

As biology has increasingly turned into a data-rich science, the need for storing and
communicating large datasets has grown tremendously. The obvious examples are the
nucleotide sequences, the protein sequences, and the 3D structural data produced by X-ray
crystallography and macromolecular NMR. A new field of science dealing with issues,
challenges and new possibilities created by these databases has emerged: bioinformatics.

Bioinformatics is the application of Information technology to store, organize and analyze

the vast amount of biological data which is available in the form of sequences and structures
of proteins (the building blocks of organisms) and nucleic acids (the information carrier).
The biological information of nucleic acids is available as sequences while the data of
proteins is available as sequences and structures. Sequences are represented in single
dimension where as the structure contains the three dimensional data of sequences.

Sequences and structures are only among the several different types of data required in the
practice of the modern molecular biology. Other important data types includes metabolic
pathways and molecular interactions, mutations and polymorphism in molecular sequences
and structures as well as organelle structures and tissue types, genetic maps, physiochemical
data, gene expression profiles, two dimensional DNA chip images of mRNA expression, two
dimensional gel electrophoresis images of protein expression, data A biological database is
a collection of data that is organized so that its contents can easily be accessed, managed, and
updated. There are two main functions of biological databases:

 Make biological data available to scientists.

o As much as possible of a particular type of information should be available in
one single place (book, site, and database). Published data may be difficult to
find or access and collecting it from the literature is very time- consuming.
And not all data is actually published explicitly in an article (genome
sequences!).

 To make biological data available in computer-readable form.

o Since analysis of biological data almost always involves computers, having

the data in computer-readable form (rather than printed on paper) is a
necessary first step.
Data Domains

 Types of data generated by molecular biology research:

– Nucleotide sequences (DNA and mRNA)
– Protein sequences
– 3-D protein structures
– Complete genomes and maps
  Also now have:
– Gene expression
– Genetic variation (polymorphisms)

2. Biological Databases

When Sanger first discovered the method to sequence proteins, there was a lot of excitement
in the field of Molecular Biology. Initial interest in Bioinformatics was propelled by the
necessity to create databases of biological sequences.

Biological databases can be broadly classified into sequence and structure databases.
Sequence databases are applicable to both nucleic acid sequences and protein sequences,
whereas structure database is applicable to only Proteins. The first database was created
within a short period after the Insulin protein sequence was made available in 1956.
Incidentally, Insulin is the first protein to be sequenced. The sequence of Insulin consisted of
just 51 residues (analogous to alphabets in a sentence) which characterize the sequence.
Around mid nineteen sixties, the first nucleic acid sequence of Yeast tRNA with 77 bases
(individual units of nucleic acids) was found out. During this period, three dimensional
structures of proteins were studied and the well known Protein Data Bank was developed as
the first protein structure database with only 10 entries in 1972. This has now grown in to a
large database with over 10,000 entries. While the initial databases of protein sequences were
maintained at the individual laboratories, the development of a consolidated formal database
known as SWISS-PROT protein sequence database was initiated in 1986 which now has
about 70,000 protein sequences from more than 5000 model organisms, a small fraction of
all known organisms. These huge varieties of divergent data resources are now available for
study and research by both academic institutions and industries. These are made available as
public domain information in the larger interest of research community through Internet
(www.ncbi.nlm.nih.gov) and CDROMs (on request from www.rcsb.org). These databases
are constantly updated with additional entries.

Databases in general can be classified in to primary, secondary and composite databases.

A primary database contains information of the sequence or structure alone. Examples of
these include Swiss-Prot & PIR for protein sequences, GenBank & DDBJ for Genome
sequences and the Protein Databank for protein structures.
A secondary database contains derived information from the primary database. A secondary
sequence database contains information like the conserved sequence, signature sequence and
active site residues of the protein families arrived by multiple sequence alignment of a set of
related proteins. A secondary structure database contains entries of the PDB in an organized
way. These contain entries that are classified according to their structure like all alpha
proteins, all beta proteins, etc. These also contain information on conserved secondary
structure motifs of a particular protein. Some of the secondary database created and hosted
by various researchers at their individual laboratories includes SCOP, developed at
Cambridge University; CATH developed at University College of London, PROSITE of
Swiss Institute of Bioinformatics, eMOTIF at Stanford.

Composite database amalgamates a variety of different primary database sources, which

obviates the need to search multiple resources. Different composite database use different
primary database and different criteria in their search algorithm. Various options for search
have also been incorporated in the composite database. The National Center for
Biotechnology Information (NCBI) which hosts these nucleotide and protein databases in
their large high available redundant array of computer servers, provides free access to the
various persons involved in research. This also has link to OMIM (Online Mendelian
Inheritance in Man) which contains information about the proteins involved in genetic
diseases.

2.1 Primary Nucleotide Sequence Database – GenBank, EMBL, DDBJ

These are three chief databases that store and make available raw nucleic acid sequences.
GenBank is physically located in the USA and is accessible through NCBI portal over
internet. EMBL (European Molecular Biology Laboratory) is in UK and DDJB (DNA
databank of Japan) is in Japan. They have uniform data formats (but not identical) and
exchange data on daily basis. Here we will describe one of the database formats, GenBank,
in detail. The access to GenBank, as to all databases at NCBI is through the Entrez search
program. This front end search interface allows a great variety of search options.
The word accession number defines a field containing unique identification numbers. The
sequence and the other information may be retrieved from the database simple by searching
for a given accession number. Taking the field names in order, we have first all the word
‘LOCUS’. This is a GenBank title that names the sequence entry. Apart for accession number,
it also specifies the number of bases in the entry, a nucleic acid type, a codeword PRI that
indicates the sequence is from primate, and the date on which the entry was made. PRI is one
of the 17 keyword search that are used to classify the data. The next line of the file contains
the definition of the entry, giving the name of the sequence. The unique accession number
came next, followed by a version number in case the entries have gone through more than
one version.

The next item is a list of specially defined keywords that used to index the entries. Next come
a set of SOURCE records which describe the organism from which sequence was extracted.
The complete scientific classification is given. This is followed by publication details.
In the beginning, sequences were extracted from the published literature and painstaking
entered in the database. Each entry was therefore associated with a publication. The features
table includes coding region, exons, introns, promoters, alternate splice patterns, mutation,
variations and a translation into protein sequence, if it code for one. Each feature may be
accompanied by a cross-reference to another database. After the feature table, a single line
gives the base count statistics for the sequence. Finally comes the sequence itself. The
sequence is typed in lower cases, and for ease of reading, each line is divided into six columns
of ten bases each. A single number on the left numbers the bases.
The above description does not cover all the fields used in GenBank, but only the more
important ones.

2.2 Primary Protein Sequence Database

PIR-PSD or protein information resource – protein sequence database, at the NBRF

(National Biomedical Research Foundation, USA), and SWISS-PROT at the SBI (Swiss
Biotechnology Institute), Switzerland are protein sequence databases.

The PIR-PSD is a collaborative endeavour between the PIR, the MIPS (Munich Information
Centre for Protein Sequences, Germany) and the JIPID (Japan International Protein
Information Database, Japan). The PIR-PSD is now a comprehensive, non- redundant,
expertly annotated, object relational DBMS. It is available at
http://pir.georgetown.edu/pirww. A unique characteristic of the PIR-PSD is its classification
of protein sequences based on the super family concept. Sequence in PIR- PSD is also
classified based on homology domain and sequence motifs. Homology domains may
correspond to evolutionary building blocks, while sequence motifs represent functional sites
or conserved regions. The classification approach allows a more complete understanding of
sequence function structure relationship.
The other well known and extensively used protein database is SWISS-
PROT(http://www.expasy.ch/sprot). Like the PIR-PSD, this curated proteins sequence
database also provides a high level of annotation. The data in each entry can considered
separately as core data and annotation. The core data consists of the sequences entered in
common single letter amino acid code, and the related references and bibliography. The
taxonomy of the organism from which the sequence was obtained also forms part of this core
information. The annotation contains information on the function or functions of the protein,
post-translational modification such as phosphorylation, acetylation, etc., functional and
structural domains and sites, such as calcium binding regions, ATP-binding sites, zinc
fingers, etc., known secondary structural features as for examples alpha helix, beta sheet,
etc., the quaternary structure of the protein, similarities to other protein if any, and diseases
that may rise due to different authors publishing different sequences for the same protein, or
due to mutations in different strains of an described as part of the annotation.
Lines of code in SWISS-PROT database:

Code Expansion Remarks

ID Identification Occurs at the beginning of the entry. Contains
a unique name for the entry, plus information
on the status of the entry. If it has been
checked and conforms to SWISS-PROT
standards, it is called STANDARD.
AC Accession numbers This is a stable way of identifying the entry.
The name may change but not the AC. If the
line has more than one number, it means that
the entry was constituted by merging other
entries.
DT Date There are three dates corresponding to the
creation date of the entry and modification
dates of the sequence and the annotation
respectively
DE Description Lines that start with the identifier contain
general description about the sequence.
GN Gene name The name of the gene ( or genes) that codes
for the protein
OS, Organism name, The name and taxonomy of the organism, and
OG,OC Organelle, Organism information regarding the organelle containing
classification the gene e.g. mitochondria or chloroplast, etc.
RN, Reference number, Bibliographic reference to the sequence. This
RP,RX,RA Position, comments, includes information (following the code RP)
RT,RL cross-reference, on the extent of work carried out b the authors.
authors, title and
location.
CC Comments These are free text comments that provide any
relevant information pertaining to the entry.
DR Database cross- This line gives cross-references to other
reference databases where information regarding this
entry is also found. As for example to structural
information for the protein in the
PDB.
 KW Keywords This line gives a list of keywords that can be
used in indexes. Search programs very often
simply go through such indices to identify
required information
FT Features Table These lines describe regions or sites of interest
in the sequence, e.g. post-transitional
modifications, binding sites, enzyme active
sites and local secondary structures
SQ Sequence Header This line indicates the beginning of the
sequence data and gives a brief summary of its
contents.

Both PIR-PSD and SWISS-PROT have software that enables the user to easily search
through the database to obtain only the required information. SWISS-PROT has the SRS or
the sequence retrieval system that searches also through the other relevant databases on the
site, such as TrEMBL.

TrEMBL (for Translated EMBL) is a computer-annotated protein sequence database that is

released as a supplement to SWISS-PROT. It contains the translation of all coding sequences
present in the EMBL Nucleotide database, which have not been fully annotated. Thus it may
contain the sequence of proteins that are never expressed and never actually identified in the
organisms.

2.3 Derived or Secondary databases of nucleotide sequences

Many of the secondary databases are simply sub-collection of sequences culled from one or
the other of the primary databases such as GenBank or EMBL. There is also usually a great
deal of value addition in terms of annotation, software, presentation of the information and
the cross-references. There are other secondary databases that do not present sequences at
all, but only information gathered from sequences databases.

An example of the former type of database is the FlyBase or The Bereley Drosophila Genome
Project ( http://www.fruitfly.org). A consortium sequenced the entire genome of the fruit fly
D. Melanogaster to a high degree of completeness and quality.
Another database that focuses on a single organism is ACeDB. More than a database, this is
a database management system that was originally developed for the C. Elegans ( a nematode
worm) genome project. It is a repository of not only the sequence, but also the genetic map
as well as phenotypic information about the C. Elegans nematode worm.

The comprehensive Microbial Resource maintained by TIGR (The Institute for Genomic
Research) at http://www.tigr.org allows access to a database called Omniome. This contains
all the focus on one organism. Omniome has not only the sequence and annotation of each
of the completed genomes, but also has associated information about the organisms (such as
taxon and gram stain pattern), the structure and composition of their DNA molecules, and
many other attributes of the protein sequences predicted from the DNA sequences. The
presence of all microbial genomes in a single database facilitated meaningful multi-genome
searches and analysis, for instance, alignment of entire genomes, and comparison of the
physical proper of proteins and genes from different genomes etc.

A database of the genomes of mitochondria and other such organelles is available at the
Organelle Genome Database at the University of Montreal, Canada, and is called GOBASE
(http://megasun.bch.umontreal.ca/gobase).

2.4 Derived or Secondary databases of amino acid sequences - Subcollections

Another family of a database focussed on a particular family protein is GPCRGB

(http://rose.man.pozen.pl/aars/). These are transmembrane protein used by cells to
communicate with the outside world. They are involved in vision, smell, hearing, taste and
feeling.GPCRGB is in fact more than a collection of sequences of the protein family. It
includes additional data on multiple sequences alignments. Ligands and ligands binding data,
3D models, mutation data, literature reference, disease patterns, cell lines, protocols, vectors
etc. It is fully integrated information system with data, and browsing and query tools.

MHCPep ( http://wehih.wehi.edu.au/mhcpep/) is a database comprising over 13000 peptide

sequences known to bind the Major Histocompatibilty Complex of the immune system. Each
entry in the database contains not only the peptide sequence, which may be 8 to 10 amino
acid long, but in addition has information on the specific MHC molecules to which it binds,
the experimental method used to assay the peptide, the degree of activity and the binding
affinity observed , the source protein that, when broken down gave rise to this peptide along
with other, the positions along the peptide where it anchors on the MHC molecules and
references and cross links to other information.

The CluSTr (Cluster of SWISS-PROT and TrEMBL proteins at http://ebi.ac.uk.clustr)

database offers an automatic classification of the entries in the SWISS-PROT and TrEMBL
databases into groups of related proteins. The clustering is based on the analysis of all pair
wise comparisons between protein sequences.

Similar to CluSTRr is the COGS or Cluster of Orthologous Groups of database that is

accessible at htp://ncbi.nlm.nih.gov/COG. An orthologous group of proteins is one in which
the members are related to each other by evolutionary descent. Such orthology may not be
just from one protein to another, and then to another and so on down the line. It may involve
one-to-many ad many-to-many evolutionary relationships, and hence the term ‘groups’.
COGS is thus a database of phylogenetic relationships. The approximately 2500
groups have been divided into 17 broad categories. The utility of COGS, as of CluSTr, is
that it helps assign function to new protein sequences without going through tedious
biochemical discovery processes.

2.5 Derived or Secondary databases of amino acid sequences – Patterns and

Signature

A set of databases collects together patterns found in protein sequences rather than the
complete sequences. The patterns are identified with particular functional and/or structural
domains in the protein, such as for example, ATP binding site or the recognition site of a
particular substrate. The patterns are usually obtained by first aligning a multitude of
sequences through multiple alignment techniques. This is followed by further processing by
different methods, depending on the particular database.

PROSITE is one such pattern database, which is accessible at http://www.expasy.ch/prosite.

The protein motif and pattern are encoded as “regular expressions”. The information
corresponding to each entry in PROSITE is of the two forms – the patterns and the related
descriptive text. The regular expression is placed in a format reminiscent of the SWISS-
PROT entries, with a two letter identifier at beginning of the each line specifying the type of
information the line contains. The expression itself is placed on line identified by “PA”. The
entry also contains references and links to all the proteins sequences that contains that pattern.
The related descriptive text is placed in a documentation file with the accession number
making the connection to the expression data.

In the PRINTS database (http://www.bioinfo.man.ac.uk/dbbrowser/PRINTS), the protein

sequence patterns are stored as ‘fingerprints’. A finger print is a set of motifs or patterns
rather than a single one. The information contained in the PRINT entry may be divided into
three sections. In addition to entry name, accession number and number of motifs, the first
section contains cross links to other databases that have more information about the
characterized family. The second section provides a table showing how many of the motifs
that make up the finger print occurs in the how many of the sequences in that family. The last
section of the entry contains the actual finger prints that are stored as multiply aligned set of
sequences, the alignment being made without gaps. There is therefore one set of aligned
sequences for each motif.

The ProDom protein domain database ( http://www.toulouse.inrs.fr/prodom.html) is a

compilation of homologous domains that have been automatically identified sequence
comparison and clustering methods using the program PSI-BLAST. No identification of
patterns is made.. The focus is here to look for complete and self-contained structural
domains and the search methods includes signals for such features. A graphical user interface
allows easy interactive analysis of structural and therefore functional homology relationships
among protein sequences.

A database called Pfam contains the profiles used using Hidden markov models
(http://www.sanger.ac.uk/Software/Pfam). HMMs build the model of the pattern as a series
of match, substitute, insert or delete states, with scores assigned for alignment to go from one
state to another. Each family or pattern defined in the Pfam consists of the four elements. The
first is the annotation, which has the information on the source to make the entry, the method
used and some numbers that serve as figures of merit. The second is the seed alignment that
is used to bootstrap the rest of the sequences into the multiple
 alignments and then the family. The third is the HMM profile. The fourth element is complete
alignment of all the sequences identified in that family.

2.6 Structure Databases

Structure databases like sequence databases comes in two varieties, primary and secondary.
Strictly speaking there is only one database that stores primary structural data of biological
molecules, namely the PDB. In the context of this database, term macromolecule stretches to
cover three orders of magnitude of molecular weight from 1000 Daltons to 1000 kilo Daltons
Small biological and organic molecules have their structures stored in another primary structure
database the CSD, which is also widely used in biological studies. This contains the three
dimensional structure of drugs, inhibitors and fragments or monomers of the macromolecule.

2.6.1 The primary structure database - PDB and CSD

PDB stands for Protein Databank. In spite of the name, PDB archive the three-dimensional
structures of not only proteins but also all biologically important molecules, such as nucleic
acid fragments, RNA molecules, large peptides such as antibiotic gramicidin and complexes of
protein and nucleic acids. The database holds data derived from mainly three sources. Structure
determined by X-ray crystallography form the large majority of the entries. This is followed by
structures arrived at by NMR experiments. There are also structures obtained by molecular
modelling. The data in the PDB is organized as flat files, one to a structure, which usually means
that each file contain one molecule, or one molecular complex.

The Cambridge Structural Database (CSD) was originally a project of the University of
Cambridge, which is set up to collect together the published three-dimensional structure of
small organic molecules. This excludes proteins and medium sized nucleic acid fragments, but
small peptides such as neuropeptides, and monomer and dimmers of nucleic acid finds a place
in the CSD. Currently CSD holds crystal structures information for about 2.5 lakhs organic and
metal organic compounds. All these crystal structures have been obtained using X-ray or
neuron diffraction technique. For each entry in the CSD there are three distinct types of
information stored. These are categorized as bibliographic information, chemical connectivity
information and the three- dimensional coordinates. The annotation data field incorporates all
of the bibliographic material for the particular entry and summarized the structural and
experimental information for the crystal structure.

2.6.1.1 Derived or Secondary databases of bimolecular structures

NDB stands for Nucleic acid data bases. It is a relational database of three-dimensional
structures containing nucleic acid. This encompasses DNA and RNA fragments, including
those with unusual chemistry such as NDB, and collections of patterns and motifs such as
SCOP, PALI etc. The structures are the same as those found in the PDB and therefore the NDB
qualifies to be called a specialized sub collection. However a substantial amount, and, unlike
the PDB, the NDB is much more than just a collection of files. The structure of DNA has been
classified into A, B and Z polymorphic forms, based on the information specified by authors.
Other classes include RNA structures, unusual structures and protein-nucleic acid complexes.
These classes of structures are arranged in the form of an ATLAS of Nucleic Acid Containing
Structures, which can be browse and searched to obtain the structure or structures required.
Each entry in the atlas has information on the

sequence, crystallisation condition, references and details of the parameters and the figures
of the merit used in structure solution. The entry has links not only to the coordinated but also
to automatically generated graphical views of the molecule. NDB also has also have archives
of structural geometries calculated for all the structures or for a subset of them. And finally,
the database stores average geometrical parameters for nucleic acids, obtained by statistical
analysis of the structures. These parameters are widely used in computer simulations of
nucleic acids and their interactions. The NDB may be accessed at
http://ndbserve.rutgers.edu/NDB/.

The SCOP database (Structural Classification of Proteins: http://scop.mrc-

lmb.cam.ac.uk/scop/ ) is a manual classification of protein structures in a hierarchical scheme
with many levels. The principal classes are the family, the super family and the fold. SCOP
is a searchable and browsable database. In other words, one may either enter SCOP at the
top of the hierarchy or examine different folds and families as one pleases, or one may supply
a keyword or a phrase to be search the database and retrieve corresponding entries. Once a
structure, or a set of structures, has been selected, they may be obtained or viewed wither as
graphical images. Each entry also has other annotation regarding function, etc., and links to
other databases, including other structural classification such as CATH.

CATH stands for Class, Architecture, Topology and Homologous super family. The name
reflects the classification hierarchy used in the database. The structures chosen for
classification are a subset of PDB, consisting of those that have been determined to a high
degree of accuracy.
 File formats

In the field of bioinformatics there exists many different file formats that store DNA and
protein sequence information. There is no one sequence format that is ideal: many are used
in different contexts, and can often be converted from one to another for easier access or
sharing. Below is a list of file formats and a link to their respective file format specs and
descriptions for anyone wishing to get to know the file formats a little better. While there
are many different formats out there used by commercial software, this list focuses mainly
on open, non-propietary file formats.

What is a file format?

A file format is a way for computers (and humans) to standardize how data is organized. For
example, this page was written on an .html extension. HTML files contain special tags that
tell the browser what each block of text is, and how to display it on the page.
Additionally, computers are able to check file formats and immediately determine whether
it should be opened in a text editor (for editing), a modern browser (for viewing) or some
other software.
File types can also indicate which algorithm to use to view (or open) that file. For example,
.gif, .jpg and .png all display images, but the level of compression, size and resolution differ.

 Genbank - quite possibly the standard in sequence file formats, the Genbank format is
widely used by public databases such as NCBI. The Genbank file format is quite flexible
and allows annotations, comments, and references to be included within the file. The file is
plain text and thus can be read with a text editor. Genbank files often have the file extension
'.gb' or '.genbank'.

 EMBL - similar in form to the Genbank file, the EMBL format is used by public databases
such as European Molecular Biology Laboratory. The Genbank file format is quite flexible
 and allows annotations, comments, and references to be included within the file. The file is
plain text and thus can be read with a text editor. Genbank files often have the file extension
'.gb' or '.genbank'.

 PDB - the PDB file format is used to store both sequence information, but more importantly
stores 3-dimensional structure information. This information can be used to visualize the
crystal structure of a given molecule (typically a protein). PDB files are simply text files,
thus can be viewed with a text editor, and often have the file extension '.pdb'.

 MDL - While not technically containing sequence data, the MDL file format is worth
including in this list. The MDL mol file contains information regarding small molecules, the
spec being quite similar to that of the PDB file format. The MDL mol file contains
information regarding 2d (and possibly 3d) molecule structure, such as atom type and atom
connectivity.

 FASTA format
File format : FASTA
File extensions : file.fa, file.fasta,
file.fsa Example :

>XR_002086427.1 Candida albicans SC5314 uncharacterized ncRNA (SCR1), ncRNA

TGGCTGTGATGGCTTTTAGCGGAAGCGCGCTGTTCGCGTACCTGCTGTTTGTTGAA
AATTTAAGAGCAAAGTGTCCGGCTCGATCCCTGCGAATTGAATTCTGAACGCTAG
AGTAATCAGTGTCTTTCAAGTTCTGGTAATGTTTAGCATAACCACTGGAGGGAAG
CAATTCAGCACAGTAATGCTAATCGTGGTGGAGGCGAATCCGGATGGCACCTTGT
TTGTTGATAAATAGTGCGGTATCTAGTGTTGCAACTCTATTTTT

Fasta format is a simple way of representing nucleotide or amino acid sequences of nucleic
acids and proteins. This is a very basic format with two minimum lines. First line referred as
comment line starts with ‘>’ and gives basic information about sequence. There is no set
format for comment line. Any other line that starts with ‘;’ will be ignored. Lines with ‘;’ are
not a common feature of fasta files. After comment line, sequence of nucleic acid or protein
is included in standard one letter code. Any tabulators, spaces, asterisks etc in
 sequence will be ignored.

Plain sequence format

A sequence in plain format may contain only IUPAC characters and spaces (no numbers!).

Note: A file in plain sequence format may only contain one sequence, while most other
formats accept several sequences in one file.

An example sequence in plain format is:

ACAAGATGCCATTGTCCCCCGGCCTCCTGCTGCTGCTGCTCTCCGGGGCCACGGCCACCGCTGCCCTGCC
CCTGGAGGGTGGCCCCACCGGCCGAGACAGCGAGCATATGCAGGAAGCGGCAGGAATAAGGAAAAGCAGC
CTCCTGACTTTCCTCGCTTGGTGGTTTGAGTGGACCTCCCAGGCCAGTGCCGGGCCCCTCATAGGAGAGG
AAGCTCGGGAGGTGGCCAGGCGGCAGGAAGGCGCACCCCCCCAGCAATCCGCGCGCCGGGACAGAATGCC
CTGCAGGAACTTCTTCTGGAAGACCTTCTCCTCCTGCAAATAAAACCTCACCCATGAATGCTCACGCAAG
TTTAATTACAGACCTGAA

FASTQ format

A sequence file in FASTQ format can contain several sequences.

FASTQ is a text-based format for storing both a biological sequence (usually nucleotide
sequence) and its corresponding quality scores. It is mainly used for storing the output of
high-throughput sequencing instruments.
A FASTQ file usually uses four lines per sequence.

1. a '@' character, followed by a sequence identifier and an optional description

2. the raw sequence letters.
3. a '+' character, optionally followed by the same sequence identifier (and any description)
4. quality values for the sequence in Line 2

An example sequence in FASTQ format is:

@SEQUENCE_ID
GTGGAAGTTCTTAGGGCATGGC
AAAGAGTCAGAATTTGAC
+
FAFFADEDGDBGEGGB
CGGHE>EEBA@@=

EMBL format

A sequence file in EMBL format can contain several sequences.

One sequence entry starts with an identifier line ("ID"), followed by further annotation lines.
The start of the sequence is marked by a line starting with "SQ" and the end of the sequence is
marked by two slashes ("//").

FASTA format

A sequence file in FASTA format can contain several sequences.

Each sequence in FASTA format begins with a single-line description, followed by lines of
sequence data. The description line must begin with a greater-than (">") symbol in the first
column.
An example sequence in FASTA format is:
>AB000263 |acc=AB000263|descr=Homo sapiens mRNA for prepro cortistatin
like peptide, complete cds.|len=368
ACAAGATGCCATTGTCCCCCGGCCTCCTGCTGCTGCTGCTCTCCGGGGCCACGGCCACCGCTGCCCTGCC
CCTGGAGGGTGGCCCCACCGGCCGAGACAGCGAGCATATGCAGGAAGCGGCAGGAATAAGGAAAAGCAGC
CTCCTGACTTTCCTCGCTTGGTGGTTTGAGTGGACCTCCCAGGCCAGTGCCGGGCCCCTCATAGGAGAGG
AAGCTCGGGAGGTGGCCAGGCGGCAGGAAGGCGCACCCCCCCAGCAATCCGCGCGCCGGGACAGAATGCC
CTGCAGGAACTTCTTCTGGAAGACCTTCTCCTCCTGCAAATAAAACCTCACCCATGAATGCTCACGCAAG
TTTAATTACAGACCTGAA

GCG format

A sequence file in GCG format contains exactly one sequence, begins with annotation lines
and the start of the sequence is marked by a line ending with two dot ("..") characters. This
line also contains the sequence identifier, the sequence length and a checksum. This format
should only be used if the file was created with the GCG package.

An example sequence in GCG format is:

An example sequence in GCG format is:
 GCG-RSF (rich sequence format)
The new GCG-RSF can contain several sequences in one file. This format
should only beused if the file was created with the GCG package.

GenBank format
A sequence file in GenBank format can contain several sequences.
One sequence in GenBank format starts with a line containing the word LOCUS
and a numberof annotation lines. The start of the sequence is marked by a line
containing "ORIGIN" and theend of the sequence is marked by two slashes ("//").

IG format
A sequence file in IG format can contain several sequences, each consisting of a
number of comment lines that must begin with a semicolon (";"), a line with the
sequence name (it may not contain spaces!) and the sequence itself terminated with
the termination character '1' for linear or '2' for circular sequences.

SAM (Sequence Alignment Map)

File format : SAM
File extensions : file.sam
SAM (file format) is a text-based format for storing biological sequences aligned to a reference sequence
developed by Heng Li. The acronym SAM stands for Sequence Alignment/Map. It is widely used for storing
data, such as nucleotide sequences, generated by Next generation sequencing technologies and usually mapped
to a reference. SAM stands for Sequence Alignment/Map format. It is a TAB-delimited text format consisting
of a header section, which is optional, and an alignment section. If present, the header must be prior to the
alignments. Header lines start with ‘@’, while alignment lines do not. Each alignment line has 11 mandatory
fields for essential alignment information such as mapping position, and variable number of optional fields for
flexible or aligner specific information.
BAM
File format : BAM
File extensions : file.bam
A BAM (Binary Alignment/Map) file is the compressed binary version of the Sequence Alignment/Map
(SAM), a compact and indexable representation of nucleotide sequence alignments. The data between SAM
and BAM is exactly same. Being Binary BAM files are small in size and ideal to store alignment files. Require
samtools to view the file.
VCF (Variant Calling Format/File)
File format : VCF
File extensions : file.vcf
The Variant Call Format (VCF) specifies the format of a text file used in bioinformatics for storing gene
sequence variations. The format has been developed with the advent of large-scale genotyping and DNA
sequencing projects, such as the 1000 Genomes Project.
GFF (General Feature Format or Gene Finding Format)
File format : GFF
File extensions : file.gff2, file. gff3, file.gff
In bioinformatics, the general feature format (gene-finding format, generic feature format, GFF) is a file format
used for describing genes and other features of DNA, RNA and protein sequences
GTF (Gene Transfer format)
File format : GTF
File extensions : file.gtf
The Gene transfer format (GTF) is a file format used to hold information about gene structure. It is a tab-
delimited text format based on the general feature format (GFF), but contains some additional conventions
specific to gene information. A significant feature of the GTF that can be validated: given a sequence and a
GTF file, one can check that the format is correct. This significantly reduces problems with the interchange of
data between groups.

The central dogma of molecular biology

A gene expresses itself by protein synthesis. Protein synthesis is under direct control
of DNA in most cases or else under the control of genetic RNA where DNA is absent.
Information for structure of a polypeptide is stored in a polynucleotide chain of DNA or
RNA.

In 1958 F.Crick proposed that the concept of central dogma, which states that when a
particular gene is expressed (control a function or a reactions) its information is copied into
another nucleic acid (mRNA) which in turn directs the synthesis of specific proteins. So the
central dogma was proposed as unidirectional flow of molecular information from DNA to
mRNA and finally to polypeptide.

Fig. 11.1 Linear flow of Central Dogma

Information in biological systems flows from DNA to RNA to proteins. The process by which
information stored in the DNA is turned into RNA is called transcription. This is similar to
DNA replication, but uses a different enzyme called RNA polymerase. Further only one strand
is used and it does not produce a new DNA but rather RNA. The same template is used over
and over again to get multiple copies of the gene. Only one strand has the sequence for the
protein, that is specifies what sequence of bases specifies the protein sequence. This is called
the coding strand. The template is the other strand and is called the anti- sense strand or the
non-coding strand. RNA polymerase always reads from 3’ to 5’ to make a “meaningful” protein
sequence that goes from 5’ to 3’. How the DNA specifies the protein sequence is through the
genetic code.

Minimum necessary Materials:-

i. Amino acids- there are some 20 amino acids and amides which constitute building
blocks or monomers of proteins. They are found in the cellular pool or cytoplasm.
ii. Ribosome- ribosome comprises two sub units which exists as separate subunits prior
to the translation of mRNA and contain following sites:
 P site (peptidyl site or D site- donor site) - P site is jointly contributed by the
two ribosomal subunits, most frequently occupied by peptidyl-tRNA or the
tRNA carrying growing peptide chain. . The P-site is also referred to as the
puromycin sensitive site. Puromycin is an antibiotic which shows similarities
with a part of amino acyl-tRNA
 A site (amino acyl site) - A site is situated on the larger subunit of ribosome.
It faces the tunnel between the two subunits, frequently occupied by amino acyl-
tRNA, functions as acceptor for growing protein during peptide bond formation.
 E-site – the exit site, the ribosomal site harboring decylated tRNA on transit out
from the ribosome.
iii. mRNA- carrying genetic information of DNA into cytoplasm for its translation
iv. tRNA- to transport the respective amino acids as per their anticodons against the
codons of mRNA
 v. Enzymes- amino acid activating system (aminoacyl- tRNA synthetase), Peptide
polymerase system
vi. ATP- as energy source
vii. GTP- for synthesis of peptide bonds
viii. Soluble protein initiation and transfer factors
ix. Various inorganic cations (K+, NH4+, Mg++ or Mn++)

Transcription:-
The transfer of genetic information from DNA to mRNA in general is known as
transcription. The segment of DNA that takes part in transcription is called
transcription unit. It has three components-
a) A promoter
b) The structural gene
c) A terminator
a) A promoter- promoter sequences are present upstream (5’end) of the structural
genes of a transcription unit. The binding sites for RNA polymerase lies within the
promoter sequence. In prokaryotes 10bp upstream from the start point lies a
conserved sequence described as 10 nucleotide sequencesTATAAT or “pribnow
box” and 35 nucleotide sequencesTTGACA as “recognitionsequence”.
b) The structural gene- structure gene is part of that DNA strand which has 3’5’
polarity as transcription occur in 5’3’ direction. The strand of DNA that directs
the synthesis of mRNA is called template or non-coding strand. The
complementary strand is called non-template or coding strand, it is identical in
base sequence to RNA transcribed from the gene, only with U in place of T.
c) A terminator- terminator is present at 3’ end of coding strand and defines the end
of the process of transcription.
 The base sequence of the mRNA molecule is complementary to that of
the antisense strand which served as it template.
 Like DNA synthesis RNA synthesis also proceeds from 5’ to 3’ direction
(5’3’).

Translation :-

Components of Translation:-

 mRNA– the mRNA serves at the template that will determine the sequence of amino
acids in the new polypeptide.It has following components:
 5’ un translated region or 5’UTR
 Initiation codon
 Coding region
 Stop codon
 3’ un translated region or 3’UTR
 t-RNA- tRNA, a clover leaf shaped molecule, delivers the correct amino acid to the
 ribosome as directed by the codon on the mRNA for incorporation into the polypeptide.
It has following arms, each with specified function:
 3’amino acid carrier arm or acceptor arm with –CCA sequence
 Ribosome recognizing arm-to recognize A or P or E-site
 Anticodon arm- with 3 nucleotides to bind to complementary codon
 Enzyme recognizing arm- to recognize specific animoacyl synthetase
 5énd with G
 Ribosome- protein synthesizing machinery, help in holding mRNA and tRNA for
specific codon translation, has following components:
 Smaller subunit ( 30S or 40S)
 Larger subunit ( 50S or 60S)
 Groove or tunnel between two subunits to hold mRNA
 Three sites- P, A and E-site
 Enzyme, peptidyl transferase , helps in peptide bond formation

General steps of Translation:-

The translation step involves the translation of the language of nucleic acids into the
language of protein. Translation is the process by which a polypeptide chain is
synthesized by ribosomes using the sequence of codons in an mRNA to direct the
sequence of amino acids.

a) Activation of amino acids or Charging of amino acids-Lipmann and co-working

showed during 1950s that amino acids attachment to the tRNA moleculesis an active
process and requires a lot of energy. In the presence of ATP, an amino acid combines
with its specific amino acyl-tRNA synthetase; Mg2+ is also required in this reaction.
It produces amino acyl-adenylate enzyme complex.

AA* + ATP + E** AA-AMP**-E +PPi***

[ *AA-amino acid, **E- aminoacyl tRNA synthetase, ***PPi- pyrophosphate]
b) Aminoacylation of tRNA or Charging of tRNA-It is the loading of tRNA with the
activated amino acid. Amino acid molecule is transferred to a specific tRNA molecule and
the AMP (adenosine monophosphate) molecule is released.
AA-AMP-E* + tRNA  AA-tRNA + AMP + E
[*AA-AMP-E – aminoacyladenylate enzyme]

Fig. 11.7 Charging or animoacylation of tRNA

c) Initiation of translation- In the first step there is binding of mRNA with smaller sub
unit of ribosome. Translation of Initiation codon (AUG) by a charged tRNA with
Methionine (n-formyl methionine, f-Met, in prokaryote) amino acids takes place. It is
followed by the translation of second codon by 2nd charged tRNA. After the translation
of first two codons, the association of bigger subunit of ribosome takes place to form a
complete translational complex. When two such charged tRNA comesclose, the peptide
bond between two amino acids, they carry, will take place with the help of a ribozyme
called- Peptidyltransferase (23SrRNA molecule) enzyme. Formation of peptide bond
between 1st& 2nd amino acid takes place. UTR- (Un- Translated-Regions) is the flanks
of mRNA before Initiation and after the stop codon, which are not to be translated, but
they play role in efficient translation .There are three initiation factors in prokaryotes-
IF3, IF2, IF1. Eukaryotes have 9 initiation factors – eIF2, eIF3, eIF1, eIF4A, eIF4B,
eIF4C, eIF4D, eIF5, eIF6.

Fig. 11.8 Steps in translation in eukaryotic cell

d) Elongation- The translated part of mRNA translocates out and ribosome moves
fromone to next codon. Regular addition of new amino acids takes place at A-site.
Polypeptide chain (PPC) keeps elongating at the expense of energy provided by GTP.
PPC hangs in the groove of bigger sub unit of ribosome on the P-site.

e)
Fig. 11.9 Polypeptide-Chain Growth [Proteins are synthesized by the successive addition of
amino acids to the carboxyl terminus]

Fig. 11.10 Mechanism of Protein Synthesis

[The cycle begins with peptidyl-tRNA in the P site. An aminoacyltRNA binds in the A site.
With both sites occupied, a new peptide bond is formed. The t-RNAs and the mRNA are
translocated through the action of elongation factor G, which moves the deacylated tRNA to
the E site. Once there, it is free to dissociate to complete the cycle.]
 e) Termination- Binding of releasing factors to the stop codon helps in the release of
polypeptide and terminates translation. Synthesis of polypeptide terminates when a
nonsense codon of mRNA reaches the A-site. There are three nonsense codons- UAA,
UAG & UGA. These codons are not recognized by any of the tRNAs. There is no tRNA
having anticodon complementary to stop codon i.e., none of the tRNA has AUU, AUC
or ACU anticodon. Finally the ribosome encounters a stop codon. The polypeptide,
tRNA and mRNA are released. The small and large subunits dissociate from one
another.

DNA

DNA stands for de-oxyribonucleic acid. It is the blue-print of life and it stores the information
that defines everything about an organism and is present in all individual living cells. In order
for an organism to thrive, DNA must be able to replicate itself with high fidelity. The structure
of DNA is a double helix. This is inherently tied to its ability to replicate information. Every
organism has a fixed number of DNA molecules.

DNA is very long and large molecule and it must be stored in special form where it is
supercoiled into a form that is known as Chromosomes. The DNA molecule is a special type
of molecule called a polymer which is made up smaller repeating units. These units are called
nucleotides.The strand of DNA is built from these nucleotides, that is, the basic coding
mechanism of life in quaternary sequence. Think of it as if the life programs itself in four
different signals A, T ,C ,and G nucleotides where as computer consists of 0 and 1. These
nucleotides have the same structure, and differ in one substructure called the “base”. The
structure is made up of a 5 carbon sugar molecule, and on the 1’ carbon is the nitrogen
containing base and the 5’ position a phosphate group. The sugar in DNA is de-oxyribose and
that’s why the name de-oxyribonucleotide. DNA’s nucleotides are of two types: purines (A and
G) and pyrimidines (C and T). They differ in the base. Nucleotides are connected using the
phosphate group of one nucleotide with the hydroxy group of the following. A sequence of
DNA nucleotides has a free 5’ end and a free 3’ end. The sequence is defined by reading from
5’ to 3’.

DNA is a double-stranded molecule and each strand of DNA is a string of these nucleotides.
The sugar- phosphate groups are on the outside and the bases of each strand are on the inside.
The way these two strands are connected is through a double helix where the two strands are
wound around each other and held together by hydrogen bonds between the bases on each
strand. The bases have a unique pair. A pairs with T and C pairs with G. Each strand is therefore
a complement of the other strand. The strands run anti-parallel to each other. So if the sequence
on one strand is AAG, then the sequence on the other strand is CTT and not TTC. Thus the two
strands of DNA are anti-parallel copies of each other. Directionality is important. DNA is read
always from 5’ to 3’. The structure and the complementary base pairing of DNA sequences is
one of the most profound discoveries in biology.

RNA
All RNA comes from copying of DNA and is another form of nucleic acid in cells that are
directly trans- ported and used for the function of information delivery and cellular signaling.
RNA is similar to DNA in the sense that it is also a polymer made up of repeated nucleotides.
However, it is single stranded. It is made up of also a different sugar. Its nucleotides are A, U,
G, and C, where U is the analog of T in DNA. While most of the RNA gets translated into
proteins there are some other types of RNA that do other important biological functions. These
include

 tRNA: transfer RNAs, responsible for transferring specific amino acids into the
ribosome. In fact for every codon there is a corresponding transfer RNA called the anti-
codon.
 ribosomal RNA: They constitute major components of the ribosome, where the
translation of mRNA to protein occurs.
 messenger RNA: mRNA these get turned into proteins

For all intents and purposes of our class, we will focus on the mRNA as the mRNA molecules
deliver the copied version of the DNA message to be translated into a protein.

Proteins

Proteins the main workhorses in cells and are coded for in the DNA. Like DNA proteins are
polymers too, meaning that they are made up of repeating units. These units are called amino
acids. There are 20 amino acids. Specific segments of the DNA code for proteins. Such DNA
segments are called genes. (To be precise, these are protein-coding genes because there are
RNA genes that make RNA that does not get translated to proteins). Proteins have structure
too. However this is much more complicated than DNA sequence. Specifically, proteins have
the “primary sequence” which is the amino acid string, “secondary structure”, which is
composed “alpha” and “beta” helices, “tertiary structure”, which is composed of mul- tiple
secondary structure units getting packaged and organized together, and finally, “quaternary
structure” which is composed of multiple repeated units of tertiary structure components. The
structure of the protein is very important for its function. The primary sequence specifies the
structure of the protein.

The Genetic code

The genetic code dictates how the protein can be read out from a DNA sequence. Proteins are
made up of 20 amino acids. So the key question is how many bases do you need to specify
these 20 amino acids. You need only three. But there are 64 and the remaining are all redundant.
The three bases are called codons. Translation is the process of going from the DNA sequence
to protein sequence. DNA sequence is read non-overlapping sets of three. So the frame matters.
Depending upon which position you started you might end with a different sequence. There are
three frames on each strand.