eChapters

Biodiversity conservation and sustainable use has, for many people, become associated mainly with issues related to plants and wild animals. Although much less discussed, the loss of farm animal genetic resources may well be much more serious than in crops because the gene pool is smaller and very few wild relatives remain. The fact that 32% of livestock breeds worldwide are at risk of becoming extinct and that the rate of extinction continues to accelerate (FAO, 2000) is thus a serious cause for concern. Animals of different characteristics and hence outputs suit differing local community needs.

The union territory of A & N Islands constitutes the farthest and the remotest part of Indian union. The islands are situated in the Bay of Bengal surrounded by sea. The neighboring countries are Burma in north east and Singapore, Malaysia and Indonesia in south east. The Union territory of A & N Islands is situated between 60 and 140 north latitude and 920 and 940 east longitude forming a broken row of continuous islands from. North to South direction. They can be divided into two groups namely Andaman and Nicobar groups. The dreaded 100 channel which is about 145 Kms wide and 400 fathoms deep, separates the two groups

Bioinformatics can be defined as “the collection, archiving, organization and interpretation of biological data” (Orengo et al., 2003). By extension, structural bioinformatics deals with the collection, archiving, organization and interpretation of 3-D structural data of bio macromolecules. Structural bioinformatics emerged with the first crystal structures of haemoglobin and myoglobin. These structures were analyzed and contributed significantly to our understanding of the principles of life at a molecular level. A repository of all publicly accessible protein crystal structures, the Protein Data Bank (PDB) was established by Walter Hamilton et al., at Brookhaven National Laboratory in 1971. Until the late 1980s, structural biologists often knew all the available structures of bio macromolecules and much of the analysis, such as structure comparison and hydrogen-bonding analysis was done manually without much computer intervention. As the number of available structures increased, so did the need for software tools for structure analysis. Structural bioinformatics encompasses a wide variety of applications, including structure visualization, validation, classification, structure-based function prediction, identification of targets for structural genomics projects and prediction of the structures of individual bio macromolecules and complexes as well the binding modes of small molecules inside proteins of pharmaceutical or biotechnological interestStructural and theoretical analyses of proteins are central to the understanding of complex molecular mechanisms and are fundamental to the drug discovery process.

Bioinformatics can be defined as the application of computer technology for the management and analysis of biological data using computer to gather, store, analyze and merge the biological data. It consists of the organization of many kinds of large-scale biological data, particularly that based on DNA and protein sequence, into web-accessible databases and the methods required analyzing these data. Bioinformatics is a fast growing field within the biological sciences that was developed because of the need to handle large amounts of genetic and biochemical data. The goal of bioinformatics is to uncover the wealth of biological information hidden in the mass of data and to obtain a clearer insight into the fundamental biology of organism. This knowledge can have profound impact on various fields such as human health, agriculture, environment, energy and biotechnology. Bioinformatics involves use of various biological databases, which are archives of consistent data that are stored in a uniform and efficient manner. Biological databases are large collections of data that are relatively different to maintain outside the centers and institutions that produce them. These data are traditionally accessed and analysed using browser-based World Wide Web (www) interfaces. There are two types of databases i.e. Primary database and Secondary database. Primary databases contain information and annotations of DNA and Protein sequences, DNA and Protein structure and DNA and Protein expression profiles catalogued for the end users.

A genome is an organism’s complete genetic signature and the collection of information that an organism can pass on to its offspring. Genomics, the study of the structure, function, and evolution of entire genomes is principally dealing with genetic information which helps us to understand how organisms and ecosystems work, how theymalfunction, or how they might be melded to human needs. The model organisms used in genomics have, in general, small genomes and short generation times. To meaningfully analyze the gene-to-phenotype relationships, a large amount of sequencing information is necessary. Progress in DNA sequencing technologies leads to accumulate Information about structures of genomes (Mohan Kumar, 2007).

HISTORY OF INSECT GENOMICS

Commencing from the publication of the entire nucleotide sequence of the genome of Haemophilus influenzae in 1995, a complete genome sequence of many organisms, including lower and higher eukaryotes, have been reported. The cost-effective way to get sufficient sequence information to address the questions is to sequence a high-quality reference genome and then map sequences from other genomes onto the reference sequence. Insects constitute the vast majority of known species with their importance including biodiversity, agricultural, and human health concerns. Hence, a study of Insect genomics is imperative to elucidate information to other organisms.

ANALYSIS OF CODON USAGE VARIATION

Multivariate analysis methods such as Correspondence Analysis and Principle Component Analysis have often been used to identify major trends of variation in synonymous codon usage among inter or intra specific genes. Genetic codes are degenerate meaning most of amino acids can be encoded by more than one codon (triplet of nucleotides); such codons are synonymous and usually differ by one nucleotide in the third position. The alternative synonymous codons are not used with similar frequency and their usage varies among different genes. Hence there is the presence of Relative Synonymous Codon Usage values. 

SEQUENCE DATA

The gene sequences downloaded from Genbank of National Center for Biotechnology Information that is the nucleotide sequence repository known worldwide, serves as the secondary data used for analysis. Relative synonymous codon usage value of each gene is extracted separately using the Codon Usage software of Sequence Manipulation Suite. These are the raw data which needs to be normalized to be used before application of various multivariate analysis.

In the context of molecular biology, a consensus sequence is the minimum nucleotide sequence that shows the characteristics common to most members of the family among a set of related genetic sequences.It serves in representing the results of a multiple sequence alignment, where related sequences are compared to each other, and similar functional sequence motifs are found. It also shows conserved/variable residues. It is found several times in the genome and is thought to play the same role in its different locations. For example, many transcription factors recognize particular consensus sequences in the promoters of the genes they regulate. In the same way restriction enzymes usually have palindromic consensus sequences, usually corresponding to the site where they cut the DNA. Transposons act in much the same manner in their identification of target sequences for transposition. Splice sites, i.e. those sequences immediately surrounding the exon-intron boundaries, can also be considered as consensus sequences. Defining a consensus DNA binding site by examining consensus sequences is a key work carried out by biologists (Harley et al., 1994). Rareness or anomaly detection followed by in depth analyses in such sequences may reveal significant information regarding the structural, functional and biochemical mechanisms of the genes which are of much importance to biologists.

Two schemes of labeling are in common use today. One variant labels a single sample, either radioactively or fluorescently. Radioactive labeling is used, e.g., in conjunction with hybridization on nylon membranes (Lennon and Lehrach, 1991). The company Affymetrix synthesizes sets of short oligomers on a glass wafer and uses a single fluorescent label (Lipshutz et al., 1999). Alternatively, two samples are labeled with a green and a red fluorescent dye, respectively. The mixture of the two mRNA preparations is then hybridized simultaneously to a common array on a glass slide. This technology is usually referred to as the Stanford technology (David Duggan et al., 1999). Quantification utilizes a laser scanner that determines the intensities of each of the two labels over the entire array. Recently, companies like Agilent have immobilized long oligomers of 60 to 70 base pairs length and used two-color labeling.

Mitochondria are key energy generators in most eukaryotic cells. In recent years a number of mitochondrial genomes have been completely sequenced, contributing to the knowledge of molecular features related to function and evolution of this peculiar genome (Boore, 1999). The pathways of mitochondrial DNA evolution are obscured by their extraordinary size. Gene content, gene rearrangement and mode of expression are the characteristics of mitochondrial genomes. The mitochondrial genomes from eukaryotes reveal large size differences between animal, fungal and plant species. The average size of animal mtDNA is ~ 16 kb (Boore, 1999), whereas plant mtDNAs range from 200 to 2500 kb (Palmer, 1990). The size of fungal mtDNA’s range from 19 kb to 176 kb (Hudspeth, 1995).The mtDNA genome has a limited number of protein coding genes such as NADH ubiquinone oxidoreductase (ND2 to ND5), cytochrome c oxidase (COX), succinate dehydrogenease (SDH), ATP synthase (ATP6), cytochrome (CYTB), etc. Among non-coding genes only rRNA and tRNA genes are found.Ribosomal RNA (rRNA) is a component of the ribosomes, the protein synthetic factories in the cell. rRNA molecules are extremely abundant. They make up at least 80% of the RNA molecules found in a typical eukaryotic cell. Synthesis of the three nucleolar rRNA molecules is unusual as they are made on one primary transcript that is chopped up into three mature rRNA molecules.

The development of bio-informatics started with the working of computers and accumulation of data on genes and proteins. There are 100,000 proteins in the human body or 1 million. In the last decade the number of protein sequences gathered in databases increased tremendously, but the key to understand the function of a protein is not its sequence but its structure. Experimental determination of 3 dimensional native folded structure of a protein usually can be done via crystallography techniques. But such experiments are time consuming. Currently there are hundreds of different fully automated approaches to protein 3D structure prediction.

All proteins are polymers of Amino acids. The polymers also known as polypeptides consist of a sequence of 20 different L-m-amino acids also referred to as residues. For chains under 40 residues the term peptide is frequently used instead of protein. To be able to perform their biological function, proteins fold into one that is driven by a number of non covalent interactions such as hydrogen bonding, ionic interaction, Vander Waal’s forces and hydrophobic packing. In order to understand the functions of proteins at a molecular level, it is often necessary to determine the three dimensional structure of proteins. The modern Information Technology techniques like Artificial Intelligence have opened new pathways to researchers. Once ANN has been trained it is capable of producing accurate output for the unknown inputs. Many researchers have tried to analyze the large sequence sized gene to determine the protein, predict the secondary structure of the protein and model its three dimensional (3D) view [11].

Today, when the collection of biological data has been increasing at explosive rate, the processing of these data is needed. It would be extremely valuable if the specialists who know what the data mean were also able to imagine ways to collect, process and exploit these data. Biological and agricultural scientists should note that concepts from computer science, discrete mathematics and statistics are being used increasingly to study and describe biological systems. The specialists, who know the subjects of mathematics, statistics and computer programming, are needed for solving the computational problems in biology. Statistical data mining approaches seem ideally suited for bioinformatics, since it is data rich, but lacks a comprehensive theory of life organization at molecular level, or in the words of I.E. Alcamo “ Keeping up with the directions and application of DNA is a never ending job.” Starting with possible definitions of statistical data mining and bioinformatics, this chapter will give a general side view of both the fields on the statistical data mining part and its technologies and discuss how statistical data mining may be used in bioinformatics.

Bioinformatics is the application of information technology to the field of molecular biology. The term Bioinformatics was coined by Paulien Hogewag, in 1978 for the study of informatic processes in biotic systems. Bioinformatics nowadays, entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data. Bioinformatics deals with storing and searching of large biological data sets and analysis of these data sets using computers to determine various relationships. 
The rapid developments in genomic and other molecular research technologies and developments in information technologies have been combined to produce tremendous amount of information related to molecular biologists. Now bioinformatics has developed and deals with many other types of biological data like protein structures, sequence alignment, gene finding, genome assembly, gene expression profiles, structure alignment, protein structure prediction, protein–protein interactions and the modelling of evolution. Being an interface between modern biology and informatics, it involves detection, expansion and implementation of computational algorithms and some of the software tools used to provide applications primarily in agriculture and healthcare divisions. In developing countries, bioinformatics play a major role in agricultural area where it can be used for increasing the nutritional content, and increasing the volume of the agricultural products etc.

r DNA Biotechnology
    
Concept of r DNA
    
DNA Preparation from Tissue
    
Reagents
    
Preparation
    
DNA Buffer (Tris-EDTA)
    
RNase A (20 mg/ml)
    
Toe DNA Preparation for Southern Blots
    
Southern Blot
    
PCR
    
Polymerase Chain Reaction
    
The Cycling Reactions
    
Denaturation at 94°C
    
Annealing at 54°C
    
Extension at 72°C
    
DNA Sequencing
    
The Sequencing Reaction
    
Denaturation at 94°C
    
Annealing at 50°C
    
Extension at 60°C
    
Separation of the Molecules
    
Detection on An Automated Sequencer
    
Assembling of The Sequenced Parts of a Gene
    
Freezing of Buffalo Semen (Jindal, 1995)
    
Tissue Culture
    
Preparation of Media
    
Laboratory Procedure for IVF (Kharche et al., 2008)
    
Source of Oocytes
    
Preparation of Estrous Goat Serum
    
Collection of Oocytes
    
Laparoscopic Ovum Pick-up
    
Oocyte Retrieval from Ovaries Collected form Slaughter 
    
House
    
Slicing Technique
    
Follicle Puncture Technique
    
Follicle Aspiration Technique
    
Follicle Isolation Technique
    
Evaluation of Oocytes
    
In vitro Maturation of Oocytes
    
Preparation of Cells for Co-culture
    
Assessment of Nuclear Maturation After in vitro Maturation of Oocytes
    
Analysis of Nuclear Status is Ascribed to One of the Following
    
Sperm Preparation for in vitro Fertilization of Oocytes
    
In vitro Fertilization of Oocytes
    
Assessment of in vitro Fertilization of Oocytes
    
Assessment of Cleavage
    
In vitro embryo culture

Animal Science Biotechnology Research Centres
    
Current Status and Some of the Achievements in Animal Heatlh
    
National Bioresource Development Board
    
Animal Biotechnology
    
Biotechnology Parks and Incubators
    
National Institute of Immunology, New Delhi
    
Bose Institute, Kolkata
    
Jawahar Lal Nehru University, New Delhi
    
National Centre For Cell Science, Pune
    
Centre for Dna Fingerprinting and Diagnostics (Cdfd) Hyderabad
    
National Institute for Plant Genome Research (Nipgr) New Delhi
    
Institute of Bioresources and Sustainable Development,Imphal
    
Institute of Life Sciences, Bhubaneshwar
    
Bharat Immunologicals and Biologicals Corporation Limited
    
International Centre for Genetic Engineering and Biotechnolgoy (Icgeb), New Delhi
    
Animal Biotechnology Research Abroad

Checks and Balances in Biotechnology Applications
    
Biosafety Issues in Animal Biotechnology Application
    
World Organization for Animal Health (OIE)
    
Recombinant DNA Safety Guidelines (1990)
    
Foreign Trade (Development and Regulation) Act, 1992 (2006)(Draft Amendment)
    
Revised Guidelines for Research in Transgenic Plants and Guidelines for Toxicity and Allergenicity Evaluation of Transgenic Seeds, Plants and Plant Parts (1998)
    
Guidelines for Generating Preclinical and Clinical Data for rDNA Vaccines, Diagnostics and other Biologicals (1999)
    
The Food Safety and Standards Act (2006)
    
Transgenic Animals Bioreactors
    
First Patent in Biotechnology
    
Biotechnology - Ethical Concerns
    
Some Priority Areas in the Field of Biotechnology
    
Suggestions for Future Development of Biotechnology Activities in the Field of Animal Health and Production in India
    
Epilogue

Information Sources for Biotechnology
    
Books
    
General Biotechnology Books
    
Animal Biotechnology Books
    
Review Articles
    
Journals
    
Animal Biotechnology Journals
    
Biotechnology Job Listings
    
The Scientist
    
Patents
    
Requirements for Setting up a Biotechnology Laboratory
    
Essential
    
Beneficial
    
Useful
    
PCR
    
Specifications of a Good PCR Macine
    
Gel Documentation System Electrophoresis
    
Laboratory Safety and Hazards

Environmental Biotechnology
    
Global Warming and Animal Health and Production
    
Genome Mapping
    
Human Genome
    
Livestock Genomics
    
Cattle Genome
    
Pig Genome
    
Bioinformatics
    
Major Branches of Bioinformatics Include
    
List of Bioinformatics Software Commonly Used in Animal Genomics Research
    
Sequence Analysis Software
    
Genetics Analysis Software
    
Functional Genomics Software
    
Biofuels
    
Advantages of Bioethanol
    
Ecological
    
Economical
    
Looking to the Future: The Potential of Second-Generation Biofuels
    
Future Role of Biofuels Depends on Profitability and New Technologies

Vaccines
    
Veterinary v/s Human Vaccines
    
Modern Veterinary Vaccines
    
rDNA Technology to Prepare Vaccines
    
Veterinary Viral Vaccines
    
Live Vaccines
    
Killed Vaccines
    
Genetically Engineered Viral Vaccines
    
Veterinary Bacterial Diseases Vaccines
    
Veterinary Parasitic Vaccines
    
Vaccines against cancer
    
Swine Flu
    
Foot and Mouth Disease
    
Adenovirus Vector Vaccine
    
Johne’s Disease
    
Diseases of Poultry
    
Newcastle Disease in Poultry
    
Avian Influenza (Bird Flu)
    
Rabies
    
Disease Diagnostics
    
The Nucleic Acid-hybridization Technique
    
Diagnostics Based on pcr
    
Diagnosis by Restriction Fragment Length Polymorphisms and Related DNA-based Approaches
    
Diagnosis by DNA Probes and DNA Microarray Technology
    
Antigen-Capture Enzyme-Linked Immunosorbent Assay (ELISA) Proteomics
    
Disease Diagnosis Kits Developed
    
Brucelosis
    
Rabies
    
Canine Distemper and Canine Parvo Virus
    
Canine Hepatitis Virus
    
Foot and Mouth Disease
    
New Castle Disease
    
Egg Drop Syndrome Virus-76 (EDS-76)
    
Proteomics for Disease Diagnostics
    
Nanotechnologies in Diagnosis and Vaccine Development
    
Monoclonal Antibodies
    
Immunotherapy
    
Problems
    
Animal Genomics for Disease Resistance
    
Gene Knockout Technology
    
Gene Pharming
    
Gene Therapy
    
Types of Gene Therapy
    
Germ Line Gene Therapy
    
Somatic Gene Therapy

Reproductive Biotechnology
    
Artificial Insemination (AI)
    
History and Future Perspectives of Artificial Insemination
    
Semen Cryopreservation
    
Buffalo
    
Goat
    
Cryoprotection and Anti Oxidants
    
Cryopreservation and Genetic Stability of Livestock Spermatozoa
    
Insemination Technique
    
Cattle and Buffalo
    
Sheep and Goat
    
Conception Rate with Artificial Insemination
    
Multiple Ovulation and Embryo Transfer (MOET)
    
Advantages of Embryo Transfer
    
MOET Includes the Following Steps
    
Superovulatory Treatments
    
Insemination
    
Recovery of Embryos
    
Synchronization of Recipients
    
Cattle
    
Buffaloes
    
Goats
    
Horses
    
In vitro Maturation, fertilization and culture of Oocytes
    
Historical Development
    
In Vitro Maturation of Oocytes
    
In vitro Sperm Capacitation
    
Scope
    
Limitations
    
Embryo Cryopreservation
    
Ultrasonography in Reproductive Management
    
Ultrasound-guided Transvaginal Oocyte Pick-up (OPU)
    
Embryo Cloning or Nuclear Transfer
    
Blastomere Separation
    
Embryo Splitting
    
Nuclear Transfer Cloning (NT)
    
Embryonic Stem Cell Complementations
    
Limitations and Future Prospects of Cloning
    
Sexing of Embryos and Separation of X and Y Chromosomes Bearing Sperms
    
PCR  in Sex Determination
    
Transgenic Animal Production
    
Gene Transfer Through Direct DNA Microinjection
    
Gene Transfer with Retroviral-Vector Assistance
    
Gene Transfer through Production of Germ-line Chimeras
    
Parthenogenetic Embryos: An Emerging Tool in Reproductive Biotechnology for Multiplication of Superior Germ Plasm
    
Applications of Parthenogenesis
    
Livestock Genomics and Marker Assisted Selection (Use of DNA Level Markers)
    
Stem Cells
    
Vaccine for Fertility Control and Increase Prolificacy
    
Auto-immunization to Increase Prolificacy
    
Biotechnology of Conservation of Livestock Breed Biodiversity
    
Gene for Prolificity: Booroola Merino
    
Role of Biotechnology in Enhancing Production
    
Milk
    
Biotechnology of Rumen Manipulation
    
Genetically Modified Ruminal Microorganisms

Biotechnology of Animal Feeding
    
Probiotics
    
Biotechnology Crops as Animal Feed
    
Biotechnology of Animal Products
    
Some New Products made Possible by Biotechnology Include

Biotechnology Products and Technologies
    
Bottlenecks in Fast Progress of Animal Biotechnology
    
Why Biotechnology should be Used in Animal Husbandry and Dairy Production
    
Contribution of Livestock Sector to Food Basket
    
Biotechnology and Environment
    
Biotechnology of Nutrient Partitioning
    
Genetic Programming for Better Animals
    
Biotechnology of Reproduction
    
Biotechnology of Animal Health

This statement signifies that the casualty of people is not due to the earthquake but due to the damage of buildings by earthquake forces. In developed countries, the casualty and loss of property is very minimal in comparison to the death toll and losses in India in the event of earthquakes of same magnitude. It has been experienced in the past that on the event of earthquakes of Richter magnitude scale of 6 or more, the death toll in India is in terms of thousands where as in Western Countries, it is multiple of tens. The less casualty is due to less damage of buildings and other infrastructures which in turn is due to the design and construction of Buildings and other structures as per the earthquake resistant theory. This paper discusses the issues related to the earthquake hazards in India and the concept of earthquake resistant structures.

Influenza a Pandemics

Drug designing is the approach of finding drugs by design based on their biological targets. The substance used for medical purpose, either alone or in mixture that changes the state or function of cells, organs or organism as a whole is known as a drug. So typically a drug target is a key molecule involved in particular metabolic or signaling pathway that is specific to disease condition or pathology, or to the infectivity or survival of a microbial pathogen. Drugs may be designed that bind to the active region and inhibit the key molecule that causes disease. However these drugs would also have to be designed in such a way that they should not affect any other important molecules similar to the key molecule. These can also be used to enhance the normal pathway of metabolism by promoting specific molecules that may have been suppressed in disease state.

In recent years, we have witnessed an explosion of biological information and the bioinformatics data arising from the rapid research and unprecedented progress in molecular biology. The novel genomic technologies have revolutionized the drug designing, discovery and development processes in government as well as private pharmaceutical industries through the use of these technologies. Various databases are doubling in size every year and fortunately we have the complete genome sequences of more than 100 organisms. At present, the pharmaceutical industries have clasped genomics as a source of drug targets. They also distinguish that the field of bioinformatics is crucial for validating these potential drug targets and for determining the ones that are most suitable for entering the drug development pipeline. Due to our increased understanding of molecular biology, there has been a change in the way that medicines are being developed. Once upon a time, new synthetic organic molecules were tested in animals or in whole organ preparations. Now this approach has been replaced with a molecular target in which in-vitro screening of compounds against purified, recombinant proteins or genetically modified cell lines is carried out with a high throughput as a consequence of better and ever improving knowledge of the molecular basis of disease.

The genetic code uses 64 codons to represent the 20 standard amino acids and the translation termination signal. Each codon is recognised by a subset of a cell’s transfer ribonucleotide acid molecules (tRNAs) and with the exception of a few codons that have been reassigned in some lineages (Osawa and Jukes 1989; Osawa et al., 1990) the genetic code is remarkably conserved, although it is still in a state of evolution (Osawa et al.,1992). The genetic code uses 64 codons to represent the 20 standard amino acids and the translation termination signal. Each codon is recognised by a subset of a cell’s transfer ribonucleotide acid molecules (tRNAs) and with the exception of a few codons that have been reassigned in some lineages (Osawa and Jukes 1989; Osawa et al., 1990) the genetic code is remarkably conserved, although it is still in a state of evolution (Osawa et al., 1992).

Insights into the three-dimensional (3D) structure of a protein are of great assistance when we plan experiments to understand protein function and in assistance of the drug design process.

Homology modeling
    
·    Homology modeling consists of the extrapolation of the structure for a new (target) sequence from the known 3D-structure (X-ray crystallographic or NMR) of related family members (templates).
    
·    Homology modeling is for those targets that have homologous proteins with known structure (>30% identity)
    
·    Homology modeling is for easy targets.
    
·    Homology modeling treats the template in an alignment as a sequence and only sequence homology is used for prediction.
    
·    When the sequence identity between the target and template sequence is low (<25%), homology modeling may not produce a significance result.

ANN is a Mathematical model or Computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. Neural Networks are non-linear statistical data modeling tools. That can be used to model complex relationships between inputs and outputs or to find patterns in data.

Objectives
    
·    Creation and use of large databases of Biological information to augment traditional laboratory based biology.
    
·    Analysis and interpretation of genomic and structural data using computational techniques from Mathematics, Statistics and Computer Science.
    
·    Explain the process and mechanism of evolution by comparing the Genomes of different species.
    
·    Development of new methods and technologies for understanding and diagnosis of genetic diseases and design of drugs for their treatment.

Motif

1.    A nucleotide/amino acid sequence pattern having biological significance.

2.    Occurs repeatedly, either in same molecule or in many molecules. Found in upstream intergenic region.

3.    Functionally important regions of genome (gene) can be recognized by searching such patterns.

4.    Used for locating binding sites, regulatory signals, to control gene expression.

5.    Identifying potential drug target sites.

Sequence Alignment

Sequence Alignment is the procedure of comparing two (Pair-wise Alignment) or more (Multiple Sequence Alignment) sequences by searching for a series of individual characters or character patterns that are in the same order in the sequences.

Significance: Discovering functional, structural and evolutionary information in biological sequences.

Biological sequences like the nucleotide and amino acid sequences can be analyzed by means of the sequence alignment. The objective behind this is to obtain knowledge regarding the similarity between the query and the target sequence to decipher the structure, function, homology of the query sequence.

Introduction

After the advent of Post Genomic era, Biological data is accumulating at an electrifying pace every day. Storage and analysis of these data serve as a major source for scientific research to understand the phenomena of origin, evolution and existence of various forms of life. The management of these data requires different statistical techniques used for retrieval, storage, analysis and extraction of precise information from small as well as large biological datasets. Application of statistical tools in Bioinformatics especially in fisheries data has been reported (Roy and Martha, 2008).

The advances in science and technology are deeply intertwined. Researchers can use the semiconductor manufacturing techniques that underlie miniaturization to build radios and exceptionally small mechanical structures that sense fields and forces in the physical world. These inexpensive, low-power communication devices can be deployed throughout a physical space, providing dense sensing close to physical phenomena, processing and communicating this information, and coordinating actions with other nodes. These multifunction devices are battery operated and are connected wirelessly with sensing, processing and communicating capabilities and are known as the wireless sensors. If we use these sensors with biological issues or Biotechnology, then we can find the new concepts biosensors. If we really implement these concepts in real life we can get rid of many diseases like heart attack, blood sugar level, gene reaction and other changes that happens in our body much before its shows to outside.

Nanotechnology is a field of applied science focused on the design, synthesis, characterization and application of materials and devices on the nanoscale. It is a sub classification of technology in colloidal science, biology, physics, chemistry and other scientific fields and involves the study of phenomena and manipulation of material at the nanoscale. This is involved in the creation of useful materials, devices, and systems used to manipulate matter at an incredibly small scale; between 1 and 100 nanometers. With nanotechnology, a large set of materials with distinct properties (optical, electrical, or magnetic) can be fabricated. Nanotechnologically improved products rely on a change in the physical properties when the feature sizes are shrunk.

The advancements in the field of informatics, biology and allied fields of technology led to the emergence of an inter-disciplinary field known as ‘Bioinformatics’. This field is an expanding and challenging tool for the collection, storage, organization, integration, analysis and simulation of biological data for utilization in biotechnology.

Collection of Data for Bioinformatics

An epoch making revolution in Genomics in recent years in deciphering plant, animal and microbial genome sequences, Proteomics, Statistics, Instrumental techniques, Structural and Computational Biology have given input to fragmented pieces-and-bits of information on biological materials. Each data is a discrete piece of important but defragmented information regarding a molecule (protein, RNA, DNA, sugars or lipids etc) or a reaction or at best a pathway, supposed to be occurring in a living system independently at a given time and space. However, as in a living system each molecule or a process exists in unison with other entities of its kind, these fragmented data are to be stored, organized, and then integrated and analysed to form an integrated part of a whole chain of events – now called a ‘SYSTEM’. Storage and organisation of data Explosion of knowledge in the field of biology and generation of new informations (data) needs well storage, organization and a faster distribution among the scientific workers. The advent of super computers, high speed computing and development of algorithms for data formatting, assists in the storage of data at the site of origin and distributed through the hyperlinks in world wide web (www).

Bioinformatics is a discipline that deals with computation of biological information. Bioinformatics is a newly emerging interdisciplinary research area spanning a range of specialties that include biology, biophysics, computer science, mathematics & statistics. It makes use of scientific and technological advances in the area of computer science, information technology and communication technology to solve complex problems in life sciences particularly problem in Biotechnology.

Explosive growth in biological data from large sequencing projects that are producing nucleotide sequences continuously at a faster rate and the content of the nucleotide database is doubling in every 14 months. The latest release of Gene bank (v.102) exceeded one billion base pairs. To cope with this huge volume of data, a new scientific discipline has emerged comprising bioinformatics, biocomputing & computational biology.

The focus of world’s trade and economic activities is increasingly being shifted from resource-based economics to knowledge-based economics. This paradigm shift has been triggered due to the implementation of Convention on Biodiversity (CBD) and other related international treaties and policy frameworks. CBD for the first time states that bio-resources are the sovereign property of the countries in which they are found. It further stipulates that access to bio-resources by outside parties can be made only after prior approved consent of the concerned stakeholders and also with mutually agreed terms and conditions for equitable sharing of benefits accrued from the commercialization of biodiversity. To realize such proclaimed rights given in CBD and to fulfill obligations of various other relevant treaties, particularly in the context WTO regulation, it is imperative that the bio-resources-rich nations like India have comprehensive knowledgebase of the biodiversity and associated information systems in accessible form.

The importance of Plant Pathology has been realized over the years owing to number of crop failures in different parts of the world. Plant disease control is indispensable for qualitative production and to compete in global agricultural trade. There is great need of sensitization of our research in various aspects which shall guide the generation to come for managing plant diseases not only for enhancing crop production but also in facilitating trade by conserving the biodiversity and environment.

Research Trend in Plant Pathology

Like in other sciences, there has been a change in the trend of research in Plant Pathology with passage of time. Up to the late 1960s most of the interest in plant pathology was concentrated in crop diseases mostly caused by fungi. Physiology of microorganisms and physiology of parasitism became increasingly popular fields of interest in 1960s.

The success of any crop improvement programme springs mainly from sound and genetically investigations carried out in the fields. However, the moment such biological populations are subjected to field evaluation, some external and non-heritable agencies come into active role. As a result, these agencies or factors mask real differences among the tested populations which stem purely from heritable or genetic factors. Their influence gets confounded with the latter. Consequently authentic data related to genetic differences are not available due to controllable and non-controllable errors. Further, physical data that are assembled in an experiment are often so voluminous and so vast that is perhaps humanly not possible to arrive at meaningful conclusions. Hence, an adequate knowledge of statistical principles and their appropriate use warrant perfection to a point where all possible sources of error can be well accounted for.

Biotechnology provides significant opportunities and greater effects in horticulture, where even minor changes such as quality, colour, aroma, flavour, structure, disease-pest resistance and postharvest behaviour bring tremendous achievements commercially. Tissue culture, genetic engineering, molecular breeding, biofertilizers, biopesticides and postharvest biotechnology are important aspects of biotechnology in horticulture such as fruit, vegetable, ornamental, spice, medicinal, aromatic and plantation crops.

Tissue Culture

Tissue culture is the true reality of the plant biotechnology. The annual demand of tissue cultured production constitutes nearly 10 per cent of the total world biotech business, amounting to 15 billion US dollars. The global production of tissue culture industry is expanding @ 15% per annum (Chadha, 2000). In India, more than 130 tissue culture units are presently producing > 300 million plantlets per annum (Choudhury and Tejaswini, 2000).

Gene silencing is the suppression of gene expression through nucleotide sequence-specific interactions that are mediated by RNA. Many manifestations of RNA silencing-RNA interference (RNAi) in animals, quelling in fungi and post-transcriptional gene silencing (PTGS) in plants, appear to be related. RNA silencing is experimentally activated by double-stranded RNA (ds RNA) and is used as a powerful technique for specific inhibition of gene expression in a variety of organisms. In a natural context, ds RNA may be produced from rearranged loci by transcription from converging promoters or by host-or viral-encoded RNA-dependent RNA polymerases (RdRP). A key component of RNA silencing is 21-23 nt RNA known as short interfering RNA (Si RNA). In Drosophila, the siRNA is derived from ds RNA by the action of an RNase-III like enzyme named DICER. The siRNA guides a multi-subunit endnuclease, referred to as the RNA-induced silencing complex (RISC) and it specifically degrades RNA that share sequence similarly with the ds RNA.

If the 1990s were the decade of genomics, the first ten years of the new century are set to become the decade of proteomics. For the first time, the technologies of proteomics make it possible to generate quantitative protein expression data on a scale and sensitivity comparable to that achieved at the genetic level. This advance has major implications for our understanding of cellular organisation in health and disease and for pharmaceutical and agricultural biotechnology. Indeed, proteomics is already yielding important findings, across a wide range of applications. Most proteomics research, however, is directed towards the more proximal goal of investigating protein expression and function under specified physiological conditions.

The rapid evolution of proteomics has continued during the past years with a series of innovations in the core technologies of two-dimensional electrophoresis and mass spectrometry, and a diversity of productive research programmes. Well annotated proteomics databases are now emerging in a number of fields to provide a platform for systematic research, with particularly promising progress in clinical applications such as cardiology and oncology. Large-scale quantitative research, comparable in power and sensitivity to that achieved for gene expression, is thus becoming a reality at the protein level.

Advancement of both biological sciences and computer technology gave birth today’s one of the hottest area known as bioinformatics. Gradually bioinformatics analysis has become an essential component to the continued improvement and development of any kind of biological research work. It has various applications in medicine, biotechnology, agriculture etc. Some of the applications of bioinformatics related to biological information analysis are as follows [1]
    
·    Information related to bio-molecules can be mapped (e.g.), the sequences can be parsed to find sites where so-called “restriction enzymes” will cut them.
    
·    Sequences can be compared, usually by aligning corresponding segments and looking for matching and mismatching letters in their sequences. Genes or proteins that are sufficiently similar are likely to be related and are therefore said to be “homologous” to each other.
    
·    If a homologous exists then a newly discovered protein may be modeled - that is 3D structure of the gene product can be predicted without doing laboratory experiments.
    
·    Bioinformatics is used to attempt to predict the function of actual gene products.

Soil is formed by disintegration and decomposition of rocks, minerals and organic matter, Soil is a habitant for plant growth and serves as a storehouse of water and food nutrients for plants, Soil is not same everywhere and varies morphologically, physically, chemically and mineralogically from one point to another both in horizontal and vertical directions. Development of soil informatics is necessary to classify the soils, to assess the productivity of soils for various crop productions and to use the soil for various purposes such as land capability classification, soil irrigability classification, soil rating and soil mapping.

Morphologically soil may appear red, yellow, black, brown or ashy in colour. Soil may vary from sandy to clayey in texture. Depending upon the nutrient reserve capacity, the soil may be fertile or infertile. On the basis of climate, a soil may be classified as laterite soil. Red earth and red loam soil, podzol soil or desert soil.

Different kinds of soil contain minerals of various types and amounts and so exhibit distinct physio co-chemical properties. Although various methods have been used in the past to classify the soils, the most modern and scientific methods is based on dominants pedogenic processes acting on a place to from a soil. The new method of soil classification has two important characteristics-Firstly soil classification is based on certain diagnostic parameters which could be estimated quantatively, and secondly depending on diagnostic parameters, a scientific method is being followed to classify a soil from higher to lower levels such as order, suborder, great group, subgroup, family and series.

Bioinformatics is a multidisciplinary approach that combines computational and biological expertise to analyze biological data to advance research and development and it drew public attention with the announcement of the draft sequence of human genome by the then US President, Bill Clinton along with Craig Venter and Francis Collins in 2000. Bioinformatics and life sciences research are gaining attention in the government, industries and academic sectors. India was the first country in the world to establish a biotechnology information system (BTIS) network in 1987 through the Dept. of Biotechnology and created an infrastructure that enables it to harness biotechnology through the application of bioinformatics. Through this branch of science, biological data are acquired, stored and then analyzed. Bioinformatics can be used to store huge bioscience data for their future uses. By exploring computational tools, databases and new strategies for pests and diseases, resistant genes can be identified and plants with desired traits can be engineered to enhance agricultural productivity. Bioinformatics can be utilized in two ways for agriculture, viz., (i) at molecular level for application in breeding strategies and (ii) agri-informatics for land use planning, farmers window, early warning system, impact assessment and environmental applications.

Bioinformatics is a recently emerged frontier discipline, which helps in analyzing biological data with the help of information technology and statistical software packages. In a broader sense, bioinformatics is the application of computer technology in management of biological information. This interdisciplinary scientific tool having no barriers between different branches of science like biology, biotechnology, mathematics, computer science and information technology, has great influence on advanced bio-science research, particularly dealing with genes, proteins and cell biology.

Bioinformatics is the branch of study that deals with the use of information technology (IT) for managing data of biological science. Bioinformatics drew public attention with the announcement of the draft sequence of human genome by the then US President Bill Clinton along with Craig Venter and Francis Collins in 2000 (Uma and Sathyanathan, 2004).

1.    ———— is a synthetic antimicrobial drug against M. tuberculosis.
    A.    Penicillin    B.    Tetracycline
    C.    Erythromycin    D.    Isoniazid
Ans.    D.
2.    Which of the antibiotic is not used as a food preservative ?
    A.    Pimaricin    B.    Nisin
    C.    Tylosin    D.    b-lactam antibiotic
Ans.    D.
3.    Which of the following bacteria is susceptible to thiophen-2-carboxylic acid hydrazide?
    A.    M. bovis    B.    M. tuberculosis
    C.    M. chelonei    D.    M. fortuitum
Ans.    A.

INTRODUCTION

Persimmon is a subtropical fruit, originated in China and popular in Western countries. It is the national fruit of Japan. However, only four species are cultivated viz., Diospyros kaki L., Diospyros lotus L., Diospyros virginiana L. and Diospyros oleifera Cheng. Persimmon resembles ripened tomatoes, thus it attract the consumers. The ripe fruit is sweet and has admirable flavor.

NUTRITIVE AND CULTURAL SIGNIFICANCE

Persimmon fruits contain 79 per cent water, 0.7 per cent pectin, 0.4 per cent each of protein and crude fibre per 100 g. They are also rich in vitamin A (2710 IU) and vitamin C (11 mg of ascorbic acid). There are two types viz., astringent and non- astringent cultivars, astringency is due to water soluble tannins (kaki- tannin) present in the flesh of fruit and the level falls down at maturity stage and in non astringent types it completely disappear at maturity.
Fresh persimmon fruits are used in certain dishes, in jelly, jam and fruit peel/ skin is added to pickles for imparting orange colour. Dried kaki is a traditional dessert in New Year festivals especially in Japan. Tannin is used as a mordant for protecting wood, as an antidote against snake venoms and as a control agent for viral infections in plants.

INTRODUCTION

The modern cultivated strawberry (Fragaria × ananassa Duch.) is one of the most widely distributed soft fruits of the world due to its genotypic diversity, highly heterozygous nature and broad range of environmental adaptations. It is one of the most delicious and refreshing soft fruit. Its plant is cherished in gardens as well as in commercial fields for its beautiful red fruit that has tantalizing aroma. Being nutritionally rich, strawberry has now become an important table fruit of millions of people around the globe. Its fruit is different from other fruits as their seeds are produced on outside of the fruit. Strawberry is unique fruit crop, which gives quicker and very high return per unit area on the capital investment, as the crop is ready for harvesting within six months of planting.

The strawberry fruits are highly perishable in nature and need quick disposal after harvest thus it has remarkable scope for its cultivation near the towns, cities and processing units where the fruits can be utilized or processed immediately after harvest. Over the last few years, continuous progress has been made in strawberry cultivation due to the use of micropropagation technique for plant propagation, day neutral cultivar, protected cultivation for multiple crops in a year and low tunnels in open field, which are useful for exploiting the tremendous potential of this small fruit crop.

INTRODUCTION

Prunus avium, commonly called wild cherry, sweet cherry is a species of cherry, a flowering plant in the rose family Rosaceae. Cherry is the fruit of many plants of the genus Prunus, and is a fleshy drupe (stone fruit) and packed with healthy nutrients and excellent antioxidants. Cherries are mostly eaten as dessert fruit or more conveniently in the brined, frozen or canned state. The cherry fruits of commerce usually are obtained from a limited number of species such as cultivars of the sweet cherry, Prunus avium. The name 'cherry' also refers to the cherry tree, and is sometimes applied to almonds and visually similar flowering trees in the genus Prunus, as in "ornamental cherry", "cherry blossom", etc. Wild cherry may refer to any of the cherry species growing outside of cultivation, although Prunus avium is often referred to specifically by the name "wild cherry" in the British Isles. Basically, cherries are native to Europe and Asia regions. De Candole reported that the cherry first grew wild in northern Persia and the Russian provinces south of the Caucasus. From there, it spread rapidly because they are attractive to birds; hence the name Prunus avium L. or bird cherry.

INTRODUCTION

Kiwifruit (Actinidia deliciosa Chev.) also known as Chinese gooseberry, China’s Miracle Fruit and The Horticultural Wonder of New Zealand, belongs to family Actinidiaceae. It is native to Yangtze valley in north-west Hupeh and Szechuan provinces of China. The kiwifruit of international commerce are large – fruited selections of Actinidia deliciosa Planch and Actinidia deliciosa (A. Chev.) 
C F Liang and A. R. Ferguson. The name kiwifruit was derived from the kiwi, a flightless bird and New Zealand’s national symbol. Although this fruit vine originated in China, yet its full economic potential was exploited by the New Zealanders, which accounts for over 70 per cent of world trade. In other countries of the world, its cultivation gained momentum after 1960’s and now is cultivated on a commercial scale in USA, Italy, China, Japan, France, Germany, Chile and Australia

Kiwifruit is a perennial climbing or scrambling vine. Fruits are rusty brown with hairy surface and looks like a sapota fruit. Flesh is light green in colour with decorative pattern of lighter colored rays radiating from the center and embedded in between are many small, soft and dark seed. It is mostly eaten as fresh fruit or combined with other fruits in salad and desserts.