GENOMICS Genomics is the study of all genes in an organism, also known as its genome. Genomics includes identifying the specific building blocks of all the genes in a cell, mapping their location in relation to the rest of the DNA, and studying the function of those genes or combination of those genes. Types of Genomics : 1. Structural Genomics 2. Comparative Genomics 3.Functional Genomics 4. Epigenomics 5. Metagenomics 6. Pharmacogenomics 7. Mutation Genomics. PROTEOMICS : (PROTEin in complement to genOME) Proteomics is the study of proteome [Proteome is a protein molecule that interacts to give the cell its individual character]. Proteomics is a subset of functional genomics. The proteome of a cell is all the proteins expressed by its genome. The proteome is of intense interest to investigators because proteins are the major functional components of the cell. Proteomics is the study of proteins in order to revolutionize the understanding of cell behaviour and disease. 1. It studies the translation of process of RNA into proteins as well as the overall process of DNA into proteins. 2. It studies the diseases through proteins because disease process manifest themselves at the level of protein activity. 3. Most drugs act by targeting proteins or protein receptors, so Proteomics is important in new generation of drugs. 4. Proteins are more complex than genes because they can be modified after formation. 5. Proteomics is the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes. 6. Proteomics can use analysis techniques to determine all of the post translational modifications that proteins undergo and therefore determine what makes a diseased or mutant protein different from a normal protein. Proteins are fundamental components of all living cells. Proteins help us digest our food, fight infections, control body chemistry, keep our bodies function smoothly. Identifying a proteins’ shape or structure is key to understanding its biological function and its role in health and disease.

1. OMICS
SMT. P.SANGEETHA
LECTURER IN BIOTECHNOLOGY
KVRGCW(A), KURNOOL

2. OMICS
 Omics refers to a field of study in biological sciences that ends with – omics, such
as genomics, transcriptomics, proteomics and metabolomics.
 The ending –ome is used to address the objects of study of such fields, such as the
genome, proteome, transcriptome, or metabolome.
 Omics refers to the collective technologies used to explore the roles, relationships,
and actions of the various types of molecules that make up the cells of an organism.

3. OMICS
These technologies include:
1. Genomics: The study of genes and their function.
2. Proteomics: The study of proteins.
3. Metabolomics: The study of molecules involved in cellular metabolism.

4. OMICS
4. Transcriptomics: The study of the mRNA.
5. Glycomics: The study of cellular carbohydrates.
6. Lipomics: The study of cellular lipids.

5. GENOMICS
SMT. P.SANGEETHA
LECTURER IN BIOTECHNOLOGY
KVRGCW(A), KURNOOL

6. GENOMICS
 Genomics is the study of all genes in an organism, also known as its
genome.
 Genomics includes identifying the specific building blocks of all the genes
in a cell, mapping their location in relation to the rest of the DNA, and
studying the function of those genes or combination of those genes.

7. TYPES OF GENOMICS
1. Structural Genomics
2. Comparative Genomics
3. Functional Genomics
4. Epigenomics
5. Metagenomics
6. Pharmacogenomics
7. Mutation Genomics.

8. 1. STRUCTURAL GENOMICS
1. It is used to describe three dimensional structure of every protein encoded
by a given Genome rather than focusing on one particular protein .
2. Structural genomics used in drug discovery and in protein on large scale.
3. It includes the genetic mapping, physical mapping and sequencing the
entire genomes.

9. 1. COMPARITIVE GENOMICS
 It includes the differences between different genomes.
 The differences between genomes provides a powerful tool for determining
the relationship between the genotype and phenotype.
Eg: Studying genes in model organisms.

10. Comparative genomics also provides a powerful
tool for
1. Studying Evolutionary changes.
2. Helping to Identify genes that are conversed or common among species.
3. Genes that give each organism its unique characteristics.

11. 3. FUNCTIONAL GENOMICS
Functional genomics involves the gene functioning of the entire genome.
 Mutagenesis or the production of changes in the DNA sequence that affect the
expression or structure of gene products, is one of the best methods for
understanding the gene function.
Genotype is the term applied to specific changes in DNA sequence found in a
mutant, while phenotype refers to all biological consequences from the presence of
mutation.

12. 3. FUNCTIONAL GENOMICS
Phenotype is the subject of genomics.
TECHNIQUES USED IN FUNCTIONAL GENOMICS ARE
1. Gene expression Profiling at transcript level.
2. Proteome analysis.

13. TYPES OF GENOMICS
4. EPIGENOMICS :
It is the study of complete set of epigenetic modifications on the genetic material of
the cell.
5. META GENOMICS :
It is the study of genetic material directly from Environmental samples and this can
be broadly referred as Environmental Genomics, Eco genomics or Community
Genomics.

14. TYPES OF GENOMICS
6. PHARMACOGENOMICS :
It is the study of how Variation in the human population correlates with drug
response pattern.
7. MUTATIONAL GENOMICS:
The study of Genome in terms of mutations that occurs in individual DNA or
Genome. The main aim is to determine the function of gene or anonymous
sequence.

15. THRUST AREAS OF GENOMICS
1. Gene Expression
2. Polymorphism Analysis
3. Seqeunce Analysis
4. Genes and Diseases
5. Molecular markers

16. THRUST AREAS OF GENOMICS
6. Genotyping
7. Mapping
8. Genome libraries
9. Phylogenetic Analysis
10. Mutations

17. PROTEOMICS
SMT. P.SANGEETHA
LECTURER IN BIOTECHNOLOGY
KVRGCW(A), KURNOOL

18. PROTEOMICS : (PROTEin in
complement to genOME)
 Proteomics is the study of proteome [Proteome is a protein molecule that
interacts to give the cell its individual character].
 Proteomics is a subset of functional genomics.
 The proteome of a cell is all the proteins expressed by its genome.
 The proteome is of intense interest to investigators because proteins are the
major functional components of the cell.

19. PROTEOMICS : (PROTEin in
complement to genOME)
Proteomics is the study of proteins in order to revolutionize the
understanding of cell behaviour and disease.
1. It studies the translation of process of RNA into proteins as well as the
overall process of DNA into proteins.
2. It studies the diseases through proteins because disease process manifest
themselves at the level of protein activity.

20. PROTEOMICS : (PROTEin in
complement to genOME)
3. Most drugs act by targeting proteins or protein receptors, so Proteomics is
important in new generation of drugs.
4. Proteins are more complex than genes because they can be modified after
formation.
5. Proteomics is the qualitative and quantitative comparison of proteomes
under different conditions to further unravel biological processes.

21. PROTEOMICS : (PROTEin in
complement to genOME)
6. Proteomics can use analysis techniques to determine all of the post
translational modifications that proteins undergo and therefore determine
what makes a diseased or mutant protein different from a normal protein.
Proteins are fundamental components of all living cells. Proteins help us
digest our food, fight infections, control body chemistry, keep our bodies
function smoothly. Identifying a proteins’ shape or structure is key to
understanding its biological function and its role in health and disease.

22. FUNCTIONAL PROTEOMICS
It is an area of Proteomics that is focused on identifying the biological
functions of specific individual proteins, classes of protein(Ex.Kinases) or
whole protein interaction networks.

23. STRUCTURAL PROTEOMICS
Structural Proteomics strives to be able to predict the 3D structure of every
protein.
1. Function is intimately dependent on structure.
2. Not feasible to solve the structure for every protein.
3. Therefore it is necessary to model the structure of unknown proteins or
similar proteins.
4. This requires a large number of known protein structures.

24. GOALS OF STRUCTURAL
PROTEOMICS
1. Assemble a sufficiently large database of protein structures and functions.
2. Construct optimal computer algorithms for modelling structure based on
aminoacid sequence.

25. PROTEIN STRUCTURE DETERMINATION
Structure determination follows the following sequence of steps :
1. Utilisation of genome sequences to find target ORF’s and design PCR
primers for cloning them into vectors.
2. Improved Affinity Chromatography for purifying protein.
3. Improvements in computer based structure solving.

26. PROTEIN STRUCTURE DETERMINATION
Two methods used for structure determination
I. X-Ray Crystallography
II. NMR (Nuclear Magnetic Resonance)

27. I. X-RAY CRYSTALLOGRAPHY
1. Based on the scattering of X-Rays through a protein crystal.
2. The scattered waves recombine in ways dependent on the atomic positions
in the protein, producing a unique pattern.
3. Determination of the amplitudes and phases of the scattered waves allows
the construction of an electron density map, from which the structure can be
determined.

28. I. X-RAY CRYSTALLOGRAPHY
4. Determination of phase usually requires additional X-Ray diffraction images of
same protein with substituted heavy atoms through a new process called Multiple
Anomalous Dispersion (MAD) allows the structural determination using one
crystal
ADVANTAGES :
1. Process is well known. 2. High resolution(2 Å)
DISADVANTAGES :
1. Requires crystallisation

29. II. NMR(NUCLEAR MAGNETIC
RESONANCE)
1.Based on the transition of phosphorous and hydrogen nuclei from a low energy to
high energy spin state under magnetic irradiation.
2. The magnetic field around nuclei in a molecule is influenced by electron flow
around the nucleus which is dependent on nearby atoms. This dependence is called
Chemical Shift.
3. Transfer of magnetic energy from one nucleus to a nearby one, the Nuclear
Overhauser Effect(NOE), shows which nuclei lie than 5 Å apart.

30. II. NMR(NUCLEAR MAGNETIC
RESONANCE)
ADVANTAGES :
1. Allows structural determination in physiological conditions.
2. Does not require crystallisation.
3. Use of lipid micelles allows the determination of structure of integral
membrane domains.

31. II. NMR(NUCLEAR MAGNETIC
RESONANCE)
DISADVANTAGES :
1. Lower resolution
2. Can only determine the structure of approx.. 30KDa protein.

32. THRUST AREAS OF PROTEOMICS
1. Structure prediction and protein modelling.
2. Function prediction.
3. Protein folding.
4. Active site analysis.
5. Target identification and optimisation.
6. Protein targeting.
7. Protein microarrays.

33. TRANSCRIPTOMICS
SMT. P.SANGEETHA
LECTURER IN BIOTECHNOLOGY
KVRGCW(A), KURNOOL

34. TRANSCRIPTOMICS
 Transcriptomics is the study of all RNA molecules in a cell. RNA is copied
from pieces of DNA and contains information to make proteins and perform
other important functions in the cell.
 Transcriptomics is used to learn more about how genes are turned on in
different types of cells and how this may help cause certain diseases, such as
cancer.

35. TRANSCRIPTOMICS
 Transcriptomics technologies are the techniques used to study an
organism’s transcriptome, the sum of all of its RNA transcripts.
 The information content of an organism is recorded in the DNA of
its genome and expressed through transcription.

36. TRANSCRIPTOMICS
 Here, mRNA serves as a transient intermediary molecule in the information
network, whilst noncoding RNAs perform additional diverse functions.
 A transcriptome captures a snapshot in time of the total transcripts present in
a cell.
 The first attempts to study the whole transcriptome began in the early 1990s, and
technological advances since the late 1990s have made transcriptomics a
widespread discipline.

37. TRANSCRIPTOMICS
Transcriptomics has been defined by repeated technological innovations that
transform the field. There are two key contemporary techniques in the
field:
1. Microarrays , which quantify a set of predetermined sequences,
2. RNA sequencing (RNA-Seq), which uses high-throughput sequencing to
capture all sequences.

38. 1.MICROARRAYS
 Microarrays consist of short nucleotide oligomers, known as "probes," which are
arrayed on a solid substrate (e.g., glass).
 Transcript abundance is determined by hybridisation of fluorescently labelled
transcripts to these probes .
 The fluorescence intensity at each probe location on the array indicates the
transcript abundance for that probe sequence.
Contd..

39. 1.MICROARRAYS
 Microarrays require some prior knowledge of the organism of interest, for
example, in the form of an annotated genome sequence or in a library of
ESTs (Expressed Sequence Tags) that can be used to generate the probes for
the array.

40. 2.RNA-Seq
 RNA-Seq refers to the combination of a high-throughput sequencing methodology with
computational methods to capture and quantify transcripts present in an RNA extract.
 The nucleotide sequences generated are typically around 100 bp in length, but can range
from 30 bp to over 10,000 bp, depending on the sequencing method used.
RNA-Seq leverages deep sampling of the transcriptome with many short fragments from a
transcriptome to allow computational reconstruction of the original RNA transcript
by aligning reads to a reference genome or to each other.

41. 2.RNA-Seq
 The typical dynamic range of 5 orders of magnitude for RNA-Seq is a key advantage over
microarray transcriptomes.
 In addition, input RNA amounts are much lower for RNA-Seq (nanogram quantity)
compared to microarrays (microgram quantity), which allowed finer examination of
cellular structures, down to the single-cell level when combined with linear amplification of
cDNA .
 Theoretically, there is no upper limit of quantification in RNA-Seq, and background signal
is very low for 100 bp reads in nonrepetitive regions.

42. 2.RNA-Seq
 RNA-Seq may be used to identify genes within a genome or identify which genes are active
at a particular point in time, and read counts can be used to accurately model the relative
gene expression level.
 RNA-Seq methodology has constantly improved, primarily through the development of
DNA sequencing technologies to increase throughput, accuracy, and read length.
 RNA-Seq has been rapidly adopted and overtook microarrays as the dominant
transcriptomics technique in 2015.

43. 2.RNA-Seq
APPLICATIONS
1 .DIAGNOSTICS AND DISEASE PROFILING :
Transcriptomic strategies have seen broad application across diverse areas
of biomedical research, including disease diagnosis and profiling.
2. GENE FUNCTION ANNOTATION :
All transcriptomic techniques have been particularly useful in identifying
the functions of genes and identifying those responsible for particular
phenotypes.

44. 2.RNA-Seq
APPLICATIONS :
3. NONCODING RNA :
Transcriptomics is most commonly applied to the mRNA content of the cell.
4. RESPONSES TO ENVIRONMENT :
Transcriptomics allows for the identification of genes and pathways that respond to and
counteract biotic and abiotic environmental stresses.
5. TRANSCRIPTOME DATABASES :
Transcriptomics studies generate large amounts of data that has potential applications far
beyond the original aims of an experiment.

45. THANK
YOU