Tools and Applications of bioinformatics
in fisheries science
Introduction to Bioinformatics in fisheries
By the term Bioinformatics, we mean the application of statistics
and computer science to the field of molecular biology. The term bioinformatics
was coined by Paulien Hogeweg in 1979 for the study of informatics processes in
biotic systems. Bioinformatics can also be defined as a “science of solving
biological problem using a mathematical and computational approach”. Its primary use since the late 1980s has been
in genomics and genetics, particularly in those areas of genomics involving
large-scale DNA sequencing. Extending its application in the field of Fisheries
sciences, bioinformatics can have following applications: Bioinformatics can be
used in mapping and analyzing DNA and protein sequences of various fish
species. Further it can be put into use
for aligning DNA and protein sequences of different fish species to compare
them. Its applications extend into creating and viewing 3-D models of protein
structures. By virtue of sequencing the genome of different fish species, we
can search for specific genes and their functions. Fish populations can be made
healthier, more disease-resistant and much more productive. Bioinformatics can
help in drug development and discovery and thereby changing the state of fish
populations.
Applications of Bioinformatics in Fisheries:
Bioinformatics
is the application of computer technology to the management of biological information.
Computers are used to gather, store, analyze and integrate biological and
genetic information which can then be applied to gene-based drug discovery and
development. The need for Bioinformatics capabilities has been precipitated by
the explosion of publicly available genomic information resulting from the
Human Genome Project. The goal of this project - determination of the sequence
of the entire human genome (approximately three billion base pairs) - will be
reached by the year 2002.
The science of Bioinformatics, which is the
melding of molecular biology with computer science, is essential to the use of
genomic information in understanding human diseases and in the identification
of new molecular targets for drug discovery. In recognition of this, many
universities, government institutions and pharmaceutical firms have formed
bioinformatics groups, consisting of computational biologists and
bioinformatics computer scientists. Such groups will be key to unraveling the
mass of information generated by large scale sequencing efforts underway in
laboratories around the world.
Molecular
medicine requires the integration and analysis of genomic, molecular, cellular,
as well as clinical data and it thus offers a remarkable set of challenges to
bioinformatics. Bioinformatics nowadays has an essential role both, in
deciphering genomic, transcriptomic, and proteomic data generated by
high-throughput experimental technologies, and in organizing information
gathered from traditional biology and medicine.
The
evolution of bioinformatics, which started with sequence analysis and has led
to high-throughput whole genome or transcriptome annotation today, is now going
to be directed towards recently emerging areas of integrative and translational
genomics, and ultimately personalized medicine. Therefore considerable efforts
are required to provide the necessary infrastructure for high-performance
computing, sophisticated algorithms, advanced data management capabilities,
and-most importantly-well trained and educated personnel to design, maintain
and use these environments. This review outlines the most promising trends in
bioinformatics, which may play a major role in the pursuit of future biological
discoveries and medical applications. Bioinformatics is a comparatively younger
discipline that bridges the life sciences and computer sciences.
The explosive growth of biological sequence
information has made it imperative to integrate these two disciplines.
Organization and analysis of biological data are the main activities of
bioinformatics. Algorithms to create, maintain and access the sequence
databases are among the most important contributions that bioinformatics has
made for the life sciences. In the flow of genetic information from sequence to
function, the stored information is translated twice: first from DNA to mRNA in
the process of transcription, then from mRNA to protein in the process of
translation. DNA and protein sequence comparisons have become routine steps in
biochemical characterization, from newly cloned proteins to entire genomes.
Genomics attempts to make a complete inventory of genes and nucleic acid
sequences. In contrast to genomics approach, proteomics attempts to study the
expressed proteins. Protein manifest physiological as well as pathophysiological
processes in a cell or an organism and proteomics describe the complete
inventory of proteins in dependence on in vivo parameters. Proteomics is
complementing genomics as a tool to study life sciences.
The two key technologies in
experimental proteomics are:
1) 2-D PAGE with image analysis and
2)
Biological mass spectrometry (MS) with database searching.
2-D
PAGE technique is finding application in fisheries for identification of
serum/plasma proteins that might be involved in the constitutive resistance to
infections, muscle protein characterization, and biochemical analysis of
cross-reactive antigens, understanding the molecular pathogenesis and genetics
of disease resistance. We are developing 2D-refernce maps of commercially
important fish and shellfish and plan to construct an index of the piscine
proteins, by the construction of 2D-database that may be useful in
identification of quantitative trait loci (QTL).
Bioinformatics tools
Bioinformatics
Tools Bioinformatics Tools the Bioinformatics tools are the software programs
for the saving, retrieving and analysis of Biological data and extracting the
information from them. Factors that must be taken into consideration when
designing these tools are: The end user (the biologist) may not be a frequent
user of computer technology and thus it should be very user friendly. These
software tools must be made available over the internet given the global
distribution of the scientific research community
Types of bioinformatics tools
1. Homology and Similarity Tools
The
term homology implies a common evolutionary relationship between two traits -
whether they are DNA sequences or bristle patterns on a fly's nose. Homologous
sequences are sequences that are related by divergence from a common ancestor.
Thus the degree of similarity between two sequences can be measured while their
homology is a case of being either true of false. This set of tools can be used
to identify similarities between novel query sequences of unknown structure and
function and database sequences whose structure and function have been
elucidated.
2. Protein Function Analysis
Function
Analysis is Identification and mapping of all functional elements (both coding
and non-coding) in a genome. This group of programs allows you to compare your
protein sequence to the secondary (or derived) protein databases that contain
information on motifs, signatures and protein domains. Highly significant hits
against these different pattern databases allow you to approximate the biochemical
function of your query protein.
3. Structural Analysis
This
set of tools allows you to compare structures with the known structure
databases. The function of a protein is more directly a consequence of its
structure rather than its sequence with structural homologs tending to share
functions. The determination of a protein's 2D/3D structure is crucial in the
study of its function
4. Sequence Analysis
This
set of tools allows you to carry out further, more detailed analysis on your
query sequence including evolutionary analysis, identification of mutations,
hydropath regions and compositional biases. The identification of these and
other biological properties are all clues that aid the search to elucidate the
specific function of your sequence.
Important bioinformatics tools used infisheries and
aquaculture
BLAST:
The
Basic Local Alignment Search Tool (BLAST) for comparing gene and protein
sequences against others in public databases, now comes in several types
including PSI-BLAST, PHI-BLAST, and BLAST 2 sequences. Specialized BLASTs are
also available for human, microbial, malaria, and other genomes, as well as for
vector contamination, immunoglobulins, and tentative human consensus sequences.
Blast is an algorithm and programme for comparing primary biological sequence
information such as amino acid sequence of proteins or nucleotides of DNA or
RNA. BLAST can be used in the field of fisheries in several purposes, these
include
1. Identifying different fish
species:-
With
the use of BLAST we can possibly correctly identify a species or find the
homologous species. This can be useful for example when we are working with a
DNA sequence from the unknown species.
2. DNA mapping of fishes:-
When
working with known species and looking to sequence a gene at an unknown
location, BLAST can compare the chromosomal position of sequence of interest to
relevant sequence in data base.
3. Establishing phylogeny:-
Using
the results received through the BLAST, we can create a phylogenetic tree using
the BLAST web page.
4. Comparison of different fish
species:-
When
working with Gene’s, Blast can locate common genes in two related species and
can be used to map annotations from one organism to another.
FASTA
A
database search tool used to compare a nucleotide or peptide sequence to a
sequence database. The program is based on the rapid sequence algorithm
described by Lipmann and Pearson. It was the first widely used algorithm for
database similarity searching. The program looks for optimal local alignments
by scanning the sequence for small matches called "words". Initially,
the scores of segments in which there are multiple word hits are calculated
("init1"). Later the scores of several segments may be summed to
generate an "in" score. An optimized alignment that includes gaps is
shown in the output as "opt". The sensitivity and speed of the search
are inversely related and controlled by the "k-top" variable which
specifies the size of a "word".
EMBOSS
EMBOSS
(The European Molecular Biology Open Software Suite) is a new, free open source
software analysis package specially developed for the needs of the molecular
biology user community. Within EMBOSS you will find around 100 programs
(applications) for sequence alignment, database searching with sequence
patterns, protein motif identification and domain analysis, nucleotide sequence
pattern analysis, codon usage analysis for small genomes, and much more It
stands for European Molecular Biology open software suite. It is a free open
source software analysis package developed for the needs of molecular Biology
and bioinformatics user community. It is used in the field of fisheries for
following purposes:-
1. Sequence alignment.
2. Rapid data base searching with
sequence patterns.
3. Protein identification including
domain analysis.
4. Nucleotide sequence pattern
analysis.
5. Codon usage analysis for small
genomes.
Clustalw
ClustalW
is a general purpose multiple sequence alignment program for DNA or proteins.
It produces biologically meaningful multiple sequence alignments of divergent
sequences, calculates the best match for the selected sequences, and lines them
up so that the identities, similarities and differences can be seen.
RasMol
It
is a powerful research tool to display the structure of DNA, proteins, and
smaller molecules. Protein Explorer, a derivative of RasMol, is an easier to
use program.
Bioinformatics
needs in the field of fisheries:-
As
we know the Organization and analysis of biological data are the main
activities of bioinformatics. In the flow of genetic information from sequence
to function, the stored information is translated twice: first from DNA to mRNA
in the process of transcription, then from mRNA to protein in the process of
translation. DNA and protein sequence
comparisons have become routine steps in biochemical characterization, from
newly cloned proteins to entire genomes. Genomics attempts to make a complete
inventory of genes and nucleic acid sequences. In contrast to genomics
approach, proteomics attempts to study the expressed proteins. Protein manifest
physiological as well as pathophysiological processes in a cell or an organism
and proteomics describe the complete inventory of proteins in dependence on in
vivo parameters. Proteomics is complementing genomics as a tool to study life
sciences.
Branches
of applied bioinformatics
1.
Sequence analysis
2.
Genome annotation
3.
Computational evolutionary biology
4.
Literature analysis
5.
Analysis of gene expression
6.
Analysis of regulation
7.
Analysis of protein expression
8.
Modeling biological systems
9.
High-throughput image analysis
10.
Molecular Interaction
11.
Prediction of protein structure
Note: Our Next topic
will be
Applied bioinformatics statistics and
economics in fisheries research
Credit of Writing: Last year students of the Faculty
of Fisheries- Kashmir: (Sabreena, Taranum, Sabiya, Asra, Ishrat, Arsh, Ambreen, Samreena, Mufassil,
Midhat,
Falak,
Shahida,
Uzma,
Gowher,
Sajad,
Shahid,
Ubaid
and Wasim
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