This document provides an overview of bioinformatics and highlights several key points: - Bioinformatics has emerged as a field to help analyze the vast amounts of biological data being generated through high-throughput technologies. It integrates biology, computer science, and information technology. - The size of the human genome and rate of data generation has grown exponentially, necessitating computational approaches. International efforts like the Human Genome Project helped sequence the entire human genome. - Bioinformatics tools and databases are used to study genomics, transcriptomics, proteomics and more to better understand living systems at the molecular level and enable applications in medicine, agriculture, forensics and more. This work also raises ethical, legal and social considerations.

1. Dr N A Ganai
Professor
Centre of Animal Biotechnology
SKUAST-Kashmir

2. Contents
 Introduction to Bioinformatics
 Complexity of life
 Size of genome
 Exponential growth in information
generation
 Why and how to handle this
information
 Definition of Bioinformatics?
 Data bases
 Tools
 Scope of Bioinformatics
 Anticipated benefits
 Ethical, Legal, and Social
Issues

3. Variation : Basis of evolution

4. What is Marker?
Marker is a piece ofMarker is a piece of
DNA molecule that isDNA molecule that is
associated with aassociated with a
certain trait of acertain trait of a
organismorganism
MorphologicalMorphological
BiochemicalBiochemical
ChromosomalChromosomal
GeneticGeneticTypes ofTypes of
MarkersMarkers

6. Animals are selected based onAnimals are selected based on
appearanceappearance
Eg. PIGMENTATIONEg. PIGMENTATION
Disadvantage: lack of polymorphismDisadvantage: lack of polymorphism

7. Animals are selected based on biochemicalAnimals are selected based on biochemical
propertiesproperties
Eg. Hb, AMYLASE, BLOOD GROUPS ETC.Eg. Hb, AMYLASE, BLOOD GROUPS ETC.
Disadvantage:Disadvantage:
Sex limitedSex limited
Age dependentAge dependent
Influenced by environmentInfluenced by environment
It covers less than 10% of genomeIt covers less than 10% of genome

8. Animals are selected based onAnimals are selected based on
structural & numerical variationsstructural & numerical variations
Eg. Structural and Numerical VariationsEg. Structural and Numerical Variations
Structural-Structural- Deletions, Insertions etc.Deletions, Insertions etc.
Numerical-Numerical- Trisomy, Monosomy, NullysomyTrisomy, Monosomy, Nullysomy
Disadvantage: low polymorphismDisadvantage: low polymorphism

9. Molecular Marker
Revealing variation at a
DNA level
Characteristics:
Co-dominant expression
Nondestructive assay
Complete penetrance
Early onset of phenotypic
expression
High polymorphism
Random distribution
throughout the genome
Assay can be automated

10. DNA isolated from any tissue eg. Blood, hair etc.
DNA isolated at any stage even during foetal life
DNA has longer shelf-life readily exchangeable b/w
labs
Analysis of DNA carried out at early age/ even at the
embryonic
Stage irrespective of sex.

11. Molecular Markers
Single locus markerSingle locus marker
Multi-locus markerMulti-locus marker
RFLP
Microsatellite
STS
DNA Fingerprinting
AFLP
RAPD
SNPs

13. DNA is not merely a molecule with a
pattern; it is a code, a language, and an
information storage mechanism

14. Size of Human Genome
 Each cell carries: 3.2 billion base pairs
 A code you need to write in 500 books, each book
of 500 pages
 Length of DNA in adult man:
The total length of DNA present in one adult human is
calculated as:
 (length of 1 bp)(number of bp per cell)(number of cells in the body)
(0.34 × 10-9
m)(6 × 109
)(1013
)
2.0 × 1013
meters
That is the equivalent of nearly 70 trips from the earth
to the sun and back.

15. Human Genome Project
• HGP: International research effort
• Began 1990, completed 2003
• Biggest ever project in life
sciences
• 20 labs participated world
around
• Next steps for ~30,000 genes
– Function and regulation of all genes
– Significance of variations between
people
– Cures, therapies, “genomic
healthcare”

16. Genomics
Transcriptomic
s
Proteomics
Metabolomics

17. Year Base Pairs Sequences
1982 680,338 606
1983 2,274,029 2,427
1984 3,368,765 4,175
1985 5,204,420 5,700
1986 9,615,371 9,978
1987 15,514,776 14,584
1988 23,800,000 20,579
1989 34,762,585 28,791
1990 49,179,285 39,533
1991 71,947,426 55,627
1992 101,008,486 78,608
1993 157,152,442 143,492
1994 217,102,462 215,273
1995 384,939,485 555,694
1996 651,972,984 1,021,211
1997 1,160,300,687 1,765,847
1998 2,008,761,784 2,837,897
1999 3,841,163,011 4,864,570
2000 11,101,066,288 10,106,023
2001 15,849,921,438 14,976,310
2002 28,507,990,166 22,318,883
2003 36,553,368,485 30,968,418
2004 44,575,745,176 40,604,319
2005 56,037,734,462 52,016,762
2006 69,019,290,705 64,893,747
2007 83,874,179,730 80,388,382
2008 99,116,431,942 98,868,465
Av. Growth in data generation :
5400 times per year

18. Exponential Growth in Biological Databases:
High throughput Technologies
PCR : by Kary Mullis 1983 - an employee of Cetus Corporation, a
biotechnology firm in California
Awarded the Nobel Prize for the discovery of PCR in 1993

19. Microarray
Technology
Real-Time PCR
DNA Chips

20. Sequencing
Sanger method : 1975
Chain Termination Method
Maxam Gilbert : 1977
Chemical Modification Method
Next Generation: 1994
High Throughput
Parallel sequencing
Entire genome can be sequenced
in a matter of weeks

21. History of DNA SequencingHistory of DNA Sequencing
Avery: Proposes DNA as ‘Genetic Material’
Watson & Crick: Double Helix Structure of DNA
Holley: Sequences Yeast tRNAAla
1870
1953
1940
1965
1970
1977
1980
1990
2002
Miescher: Discovers DNA
Wu: Sequences λ Cohesive End DNA
Sanger: Dideoxy Chain Termination
Gilbert: Chemical Degradation
Messing: M13 Cloning
Hood et al.: Partial Automation
• Cycle Sequencing
• Improved Sequencing Enzymes
• Improved Fluorescent Detection Schemes
1986
• Next Generation Sequencing
•Improved enzymes and chemistry
•Improved image processing
Adapted from Eric Green, NIH; Adapted from Messing & Llaca, PNAS (1998)Adapted from Eric Green, NIH; Adapted from Messing & Llaca, PNAS (1998)
1
15
150
50,000
25,000
1,500
200,000
50,000,000
Efficiency
(bp/person/year)
15,000
100,000,000,000 2008

22. The Genome Sequence
is at hand…so?
“The good news is that we have the human genome.
The bad news is it’s just a parts list”

23. What Next???
We need to know every
part, its function and
application

24. What is Bioinformatics?
The newest, fastest growing
specialty in the life sciences that
integrates biotechnology and
computer science.
Computers aid to collect, analyze,
and interpret biological information
at the molecular level.

25. Understand a living cell and how it functions at
molecular level
Develop data basses and computational tools
Databases to:
Store all the data (information) related to Genomics,
Transcriptomics, preoteomics, Metabolomics
Tools to
 To mine (analyze) databases to generate knowledge to better
understand the living systems
Goal of Bioinformatics

26. Anticipated Benefits of
Genome Research & Bioinformatics
Molecular Medicine : Gene Testing ,
Pharmacogenomics
Gene Therapy
improve diagnosis of disease
detect genetic predispositions to disease
create drugs based on molecular information
use gene therapy and control systems as drugs
design “custom drugs” (pharmacogenomics) based on
individual genetic profiles

27. Huntigton disease (an inherited neurodegenerative
disorder)
 Symptoms:uncontrollable dance-like (choreatic)
movements,mental disturbance,personality changes and
intellectual impairment
 repeats of the trinucleotide CAG,corresponding to
polyglutamine blocks in the corresponding protein,
huntingin
11-28 CAG repeats -->normal
29-34 CAG repeats---->likely to develop disease
35-41 CAG repeats develop mild symptoms
morethan 41 CAG repeats suffer full huntington
disease
Diagnosis of disease and disease risk

28. Microbial Genomics
 rapidly detect and treat pathogens in clinical
practice
 develop new energy sources (biofuels)
 monitor environments to detect pollutants
 protect citizenry from biological and chemical
warfare
 clean up toxic waste safely and efficiently

29. DNA Identification (Forensics)
identify potential suspects whose DNA may
match evidence left at crime scenes
exonerate persons wrongly accused of
crimes
establish paternity and other family
relationships
identify endangered and protected species
as an aid to wildlife officials (could be
detect bacteria and other organisms that may
pollute air, water, soil, and food
match organ donors with recipients in
transplant programs
determine pedigree for seed or livestock
breeds
Benefits: …contined

30. Agriculture, Livestock Breeding, and
Bioprocessing
grow disease-, insect-, and drought-resistant crops
breed healthier, more productive, disease-resistant
farm animals
grow more nutritious produce
develop biopesticides
incorporate edible vaccines incorporated into food
products
develop new environmental cleanup uses for plants
like tobacco
Benefits …cont
.

31. ELSI: Ethical, Legal,
and Social Issues
• Privacy and confidentiality of genetic information.
• Fairness in the use of genetic information by insurers, employers,
courts, schools, adoption agencies, and the military, among others.
• Psychological impact, stigmatization, and discrimination due to an
individual’s genetic differences.
• Reproductive issues including adequate and informed consent and use
of genetic information in reproductive decision making.
• Clinical issues including the education of doctors and other health-
service providers, people identified with genetic conditions, and the
general public about capabilities, limitations, and social risks; and
implementation of standards and quality control measures.‑
Health and environmental issues concerning genetically modified foods
(GM) and microbes.
Commercialization of products including property rights (patents,
copyrights, and trade secrets) and accessibility of data and materials.