BIOINFORMATICS APPROACHES AND ITS
APPLICATION IN PLANT SCIENCE
DEPARTMENT OF BOTANICAL AND ENVIRONMENTAL SCIENCES
GURU NANAK DEV UNIVERSITY, AMRITSAR
SUPERVISED BY-
DR. HARPREET KAUR
SUBMITTED BY-
JASVIR KUMAR
ROLL NO. 28372355431
M.Sc. Botany 2nd Sem
(Seminar BSS4099)
CONTENT
1. Introduction
2. Definition
3. Genomics
4. Transcriptomics
5. Proteomics
6. Metabolomics
7. The first genomic sequence – Arabidopsis thaliana
8. Application of Plant Genomics in Plant Science
9. Plant Breeding
10. Plant Disease Management
11. In Agriculture
12. Crop Improvement
13. Development of Drought-Resistant varieties
14. Single Gene Analysis
15. Molecular Markers
16. Database used for major crops
17. Disadvantages of Bioinformatics
18. Conclusion
INTRODUCTION
Bioinformatics plays a critical role in data integration, analysis, and
model prediction, as well as in managing the massive amounts of data
resulting from new, high-throughput approaches.
Bioinformatics is a rapidly developing field which is helping in advance
plant biotechnology and breeding technique.
The typical datasets generated by plant researchers with the help of
bioinformatics contain Morphological information, Physiological
information, Molecular information, and Genetic information.
BIOLOGY INFORMATICS
BIOINFORMATICS
Definition
o Bioinformatics refers to the study of biological information using
concepts and methods in computer science, statistics, and engineering.
o It is the analysis, collection, classification, manipulation, recovery,
storage, and visualization of all biological information using
computation technology.
o It is an umbrella term for Genomics, Transcriptomics, Proteomics and
Metabolomics.
GENOMICS
 Genomics is a discipline in genetics concerning the study of the genomes
of organisms.
 This includes studying the structure, function, and interactions between
all of the genes and other components that make up the genome.
 The term Genomics was coined by H. Roderick in
1987.
TRANSCRIPTOMICS
 The Transcriptome is the set of all RNA molecules,
including mRNA, rRNA, tRNA, and other non-
coding RNAs produced in one or a population of
cells.
 Transcriptomics is defined as the study of
transcriptome, also known as Expression profiling,
as it is a study of the expression levels of mRNAs in
a given cell population.
 It helps in the detection of Diagnostic biomarkers,
understanding of Disease pathways, Classification
of diseases and monitoring of Therapeutic response.
Transcriptomics
PROTEOMICS
 The Proteome is the entire set of
proteins expressed by the genome in a
cell, tissue, or organism.
 Proteomics is the study of the
interactions, function, composition,
and structures of proteins and their
cellular activities.
Figure 1: Central Dogma of Molecular Biology
https://www.scienceholic.org/post/the-exception-to-the-central-dogma
METABOLOMICS
 Metabolomics is the large-scale study of small molecules, commonly
known as metabolites, within cells, biofluids, tissues or organisms.
 The Metabolome is the complete set of metabolites within a cell, tissue or
biological sample at any given time point.
 Metabolomics provides a deep look into the metabolites
present in any given sample at any given time.
The First Plant Genome Sequence-
Arabidopsis thaliana
• The Arabidopsis thaliana genome was the first plant genome to be sequenced.
• The initiative to sequence the Arabidopsis genome was proposed in 1989 by the Biological,
Behavioural, and Social Science Directorate (BBS) of the National Science Foundation
(NSF) with considerable input from academic and industrial scientists.
Nuclear protein-coding genes 27,202
Pseudogenes and Transposable Element Genes 4827
Noncoding RNAs 1359
Average Intron Length 165 nt
Average Exon Length 296 nt Figure 2: Plant of
Arabidopsis thaliana
Table 1: Table showing Genomic information of Arabidopsis thaliana. https://herbaria.plants.ox.ac.uk/bol/plant
s400/Profiles/AB/Arabidopsis
Application of
Bioinformatics in
Plant Science
Development of
Drought
Resistance
varieties
Crop
Improvement
Plant Disease
Management
Plant
Breeding
In Agriculture Single Gene
Analysis
PLANT BREEDING
 Bioinformatics aids in identifying ideal genotype combinations
for desired phenotypes and accelerates the development of new
varieties.
 Bioinformatics methods measure the best leaf angle for the
highest photosynthetic rates, to create plants with an optimal
leaf angle, which may increase the accumulation of organic
matter in plants.
 For example, the adaptability, yield, and quality of Rapeseed
(Brassica napus) have been the target of genetic improvement
via breeding.
Figure 3. Best Leaf Angle
for the highest
photosynthesis rate
Breeding aims to
integrate various
indicators such
as:-
Yield Quality
Fertility
Disease
Resistance
Insect
Resistance
Adaptability to
adverse
environments
Figure 4: Improved qualities of Crops
With the help of breeding
https://www.mdpi.com/2223-7747/11/22/3118
PLANT DISEASE MANAGEMENT
• The first systematic attempt to produce an insect-resistant plant in Europe
occurred in the 18th century with the grafting of Grapevine stems onto
resistant American rootstocks to defeat the Aphid.
Figure 5: Aphids attacking Grapevine stem
https://influentialpoints.com/Gallery/Aphis_illinoisensis_grapevine_aphid.htm
• In 1973, researchers developed techniques to move genes from one organism to
another organism.
In Agriculture
1. Genetically Modified Food
• The first genetically modified food, the
Flavor Savr Tomato (delayed ripening for
longer freshness) was approved in the US in
1994. The FLAVR SAVR™ tomato was
developed through the use of antisense RNA
to regulate the expression of the enzyme
polygalacturonase (PG) in ripening tomato
fruit.
Figure 6. Development of FLAVR SAVR tomato.
https://homescience10.ac.in/storage/pages/ecurricul
um/Bsc_Hsc_Sem_2/flavrsavr%20tomato.pdf
2. Improvement of Rice
• Genomics has played a significant role in enhancing the yield and nutritional value of
rice. As a result, rice production has increased.
• β-carotene genes are transferred into Rice to increase Vitamin A, Iron, and other
micronutrients.
Figure 7: Production of improved Rice crop
https://www.linkedin.com/pulse/organic-rice-production-market-demand-comprehensive-overview-sharma
CROP IMPROVEMENT
• Crop improvement is entering a new era of omics and
bioinformatics.
• The goal of the omics technique is to collect the latest advances
in understanding the molecular mechanism.
• These include molecular mechanisms of agronomically
important traits in crops, such as yield, quality, and resistance
to abiotic and biotic disease.
The figure depicts the use of genomic resources for
the identification of marker /candidate genes.
Subsequently, the markers/genes identified may be
used to detect gene trait associations thus
enhancing the molecular breeding program by
deploying different approaches like MABC,
MARS, and GS. Ultimately integrating genomic
resources through translational genomics would
result in improved lines or developed cultivars.
Figure 8: Integrative genomics for accelerated
crop improvement.
https://www.researchgate.net/figure/Integrative-genomics-for-accelerated-
crop-improvement-The-figure-depicts-the-use-of_fig2_267397050
DEVELOPMENT OF DROUGHT
RESISTANT VARIETIES
• Research is in progress to produce crop
varieties capable of tolerating reduced water
conditions.
• Crops like Corn, Wheat, and Rice, have
become increasingly tolerant to drought with
new varieties created via genetic engineering.
• These varieties allow agriculture to succeed in
poorer soil areas, thus adding more land to the
global production base.
Figure 9: Drought resistant crops
https://www.technologynetworks.com/applied
-sciences/news/breakthrough-in-development-
of-drought-resistant-crops-355322
Single Gene Analysis
• Single gene sequencing may be appropriate for conditions
caused by variants in a single gene, where the degree of
diagnostic confidence is high. All the exons in the
particular gene are sequenced.
Que - When is single-gene sequencing done?
Ans - Single-gene sequencing may be undertaken when an
organism’s features are strongly indicative of a genetic
condition caused by variants in a single Gene.
Figure 10:. Single Gene Analysis
https://www.tessresearch.org/genetic-
sequencing/
Advantages of Single gene
Analysis
• Can provide rapid genetic confirmation of a
diagnosis if the plant’s features are sufficiently
specific.
• There is no possibility of incidental findings.
• Focusing on a single gene means that there are
fewer variants requiring clinical interpretation,
and less chance of identifying Variants of
Unknown Significance (VUS).
Disadvantages of Single Gene
Analysis
• Not suitable for genetically heterogeneous
conditions.
• Will not identify any novel genetic causes of
disease.
Tables comparing the Advantages and Disadvantages of the different
approaches to Gene Sequencing
Molecular Markers
• Molecular marker is a fragment of DNA that is associated with a certain
location within the Genome.
• Molecular markers are used in molecular biology and biotechnology to
identify a particular sequence of DNA in a pool of unknown DNA.
List of Markers Acronym
Restriction Fragment Length Polymorphism RFLP
Random Amplified Polymorphic DNA RAPD
Amplified Fragment Length Polymorphism AFLP
Variable Number Tandem Repeat VNTR
Oligonucleotide Polymorphism OP
Single Nucleotide Polymorphism SNP
Table showing the list of markers and their acronym
Applications of Markers in Plant Science.
• Assessing variability of genetic differences and characteristics
within a species.
• Identification and fingerprinting of genotypes.
• Estimating genetic distances between species and offspring.
• Identifying the location of Quantitative Trait Loci (QTL).
• Identification of DNA sequence from useful candidate genes.
Selection of plant
with Desired
Morphological traits.
Development of
breeding populations.
(F1 and F2
generation)
Marker assisted
selection of Plants
with Desired traits
Marker Validation
in improved Plants
Field traits of
improved lines
Expressing
Desired
Morphological
traits
Enhanced Plant Growth
Yield and Stress tolerance
Marker-Assisted Breeding for Abiotic Stress Tolerance in Crop Plants
NOTE URL
1. National Rice Data Centre http://www.ricedata.cn/index.htm
2. Maize genome database http://maize.jcvi.org/
3. Tomato functional genome
database
http://ted.bti.cornell.edu/
4. Wheat genome information
database http://www.wheatgenome.org/
5. Rice genetics and genomics
database
https://shigen.nig.ac.jp/rice/oryzaba
se/
Databases used for Major crops
DISADVANTAGES OF BIOINFORMATICS
Searching databases can sometimes become time-consuming.
Costly to hold databases.
Reliability of data stored is questioned.
Error in sequence alignment can affect the outcome of structural analysis.
Completely relying on the information is dangerous if the information is
inaccurate.
CONCLUSION
• Applying bioinformatics to the study and characterize biological
phenomena represents a fundamental shift in how scientists study living
organisms.
• Databases provide access to Gene information, gene expression data, and
metabolite profiles, as well as the experimental conditions used to
generate them.
• Many genomic, Transcriptomic, Proteomic, and Metabolite databases
available have the potential to accelerate the rate of functional discoveries
in plant biology.
ACKNOWLEDGMENT
I would like to express my special thanks to the Head of my Department Dr Rajinder
Kaur as well as my Supervisor Dr Harpreet Kaur and all the teachers who gave me
this golden opportunity to make this wonderful project on the topic of Bioinformatics
Approaches and its Application in Plant Science which helped me in doing a lot of
research and I came to know about a lot of new things. Secondly, I would like to thank
my friends who helped me a lot in finalizing this project.
431 Bioinformatics approaches and its application in plant science.pptx

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431 Bioinformatics approaches and its application in plant science.pptx

  • 1. BIOINFORMATICS APPROACHES AND ITS APPLICATION IN PLANT SCIENCE DEPARTMENT OF BOTANICAL AND ENVIRONMENTAL SCIENCES GURU NANAK DEV UNIVERSITY, AMRITSAR SUPERVISED BY- DR. HARPREET KAUR SUBMITTED BY- JASVIR KUMAR ROLL NO. 28372355431 M.Sc. Botany 2nd Sem (Seminar BSS4099)
  • 2. CONTENT 1. Introduction 2. Definition 3. Genomics 4. Transcriptomics 5. Proteomics 6. Metabolomics 7. The first genomic sequence – Arabidopsis thaliana 8. Application of Plant Genomics in Plant Science 9. Plant Breeding 10. Plant Disease Management 11. In Agriculture 12. Crop Improvement 13. Development of Drought-Resistant varieties 14. Single Gene Analysis 15. Molecular Markers 16. Database used for major crops 17. Disadvantages of Bioinformatics 18. Conclusion
  • 3. INTRODUCTION Bioinformatics plays a critical role in data integration, analysis, and model prediction, as well as in managing the massive amounts of data resulting from new, high-throughput approaches. Bioinformatics is a rapidly developing field which is helping in advance plant biotechnology and breeding technique. The typical datasets generated by plant researchers with the help of bioinformatics contain Morphological information, Physiological information, Molecular information, and Genetic information.
  • 5. Definition o Bioinformatics refers to the study of biological information using concepts and methods in computer science, statistics, and engineering. o It is the analysis, collection, classification, manipulation, recovery, storage, and visualization of all biological information using computation technology. o It is an umbrella term for Genomics, Transcriptomics, Proteomics and Metabolomics.
  • 6. GENOMICS  Genomics is a discipline in genetics concerning the study of the genomes of organisms.  This includes studying the structure, function, and interactions between all of the genes and other components that make up the genome.  The term Genomics was coined by H. Roderick in 1987.
  • 7. TRANSCRIPTOMICS  The Transcriptome is the set of all RNA molecules, including mRNA, rRNA, tRNA, and other non- coding RNAs produced in one or a population of cells.  Transcriptomics is defined as the study of transcriptome, also known as Expression profiling, as it is a study of the expression levels of mRNAs in a given cell population.  It helps in the detection of Diagnostic biomarkers, understanding of Disease pathways, Classification of diseases and monitoring of Therapeutic response. Transcriptomics
  • 8. PROTEOMICS  The Proteome is the entire set of proteins expressed by the genome in a cell, tissue, or organism.  Proteomics is the study of the interactions, function, composition, and structures of proteins and their cellular activities. Figure 1: Central Dogma of Molecular Biology https://www.scienceholic.org/post/the-exception-to-the-central-dogma
  • 9. METABOLOMICS  Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms.  The Metabolome is the complete set of metabolites within a cell, tissue or biological sample at any given time point.  Metabolomics provides a deep look into the metabolites present in any given sample at any given time.
  • 10. The First Plant Genome Sequence- Arabidopsis thaliana • The Arabidopsis thaliana genome was the first plant genome to be sequenced. • The initiative to sequence the Arabidopsis genome was proposed in 1989 by the Biological, Behavioural, and Social Science Directorate (BBS) of the National Science Foundation (NSF) with considerable input from academic and industrial scientists. Nuclear protein-coding genes 27,202 Pseudogenes and Transposable Element Genes 4827 Noncoding RNAs 1359 Average Intron Length 165 nt Average Exon Length 296 nt Figure 2: Plant of Arabidopsis thaliana Table 1: Table showing Genomic information of Arabidopsis thaliana. https://herbaria.plants.ox.ac.uk/bol/plant s400/Profiles/AB/Arabidopsis
  • 11. Application of Bioinformatics in Plant Science Development of Drought Resistance varieties Crop Improvement Plant Disease Management Plant Breeding In Agriculture Single Gene Analysis
  • 12. PLANT BREEDING  Bioinformatics aids in identifying ideal genotype combinations for desired phenotypes and accelerates the development of new varieties.  Bioinformatics methods measure the best leaf angle for the highest photosynthetic rates, to create plants with an optimal leaf angle, which may increase the accumulation of organic matter in plants.  For example, the adaptability, yield, and quality of Rapeseed (Brassica napus) have been the target of genetic improvement via breeding. Figure 3. Best Leaf Angle for the highest photosynthesis rate
  • 13. Breeding aims to integrate various indicators such as:- Yield Quality Fertility Disease Resistance Insect Resistance Adaptability to adverse environments Figure 4: Improved qualities of Crops With the help of breeding https://www.mdpi.com/2223-7747/11/22/3118
  • 14. PLANT DISEASE MANAGEMENT • The first systematic attempt to produce an insect-resistant plant in Europe occurred in the 18th century with the grafting of Grapevine stems onto resistant American rootstocks to defeat the Aphid. Figure 5: Aphids attacking Grapevine stem https://influentialpoints.com/Gallery/Aphis_illinoisensis_grapevine_aphid.htm • In 1973, researchers developed techniques to move genes from one organism to another organism.
  • 15. In Agriculture 1. Genetically Modified Food • The first genetically modified food, the Flavor Savr Tomato (delayed ripening for longer freshness) was approved in the US in 1994. The FLAVR SAVR™ tomato was developed through the use of antisense RNA to regulate the expression of the enzyme polygalacturonase (PG) in ripening tomato fruit. Figure 6. Development of FLAVR SAVR tomato. https://homescience10.ac.in/storage/pages/ecurricul um/Bsc_Hsc_Sem_2/flavrsavr%20tomato.pdf
  • 16. 2. Improvement of Rice • Genomics has played a significant role in enhancing the yield and nutritional value of rice. As a result, rice production has increased. • β-carotene genes are transferred into Rice to increase Vitamin A, Iron, and other micronutrients. Figure 7: Production of improved Rice crop https://www.linkedin.com/pulse/organic-rice-production-market-demand-comprehensive-overview-sharma
  • 17. CROP IMPROVEMENT • Crop improvement is entering a new era of omics and bioinformatics. • The goal of the omics technique is to collect the latest advances in understanding the molecular mechanism. • These include molecular mechanisms of agronomically important traits in crops, such as yield, quality, and resistance to abiotic and biotic disease.
  • 18. The figure depicts the use of genomic resources for the identification of marker /candidate genes. Subsequently, the markers/genes identified may be used to detect gene trait associations thus enhancing the molecular breeding program by deploying different approaches like MABC, MARS, and GS. Ultimately integrating genomic resources through translational genomics would result in improved lines or developed cultivars. Figure 8: Integrative genomics for accelerated crop improvement. https://www.researchgate.net/figure/Integrative-genomics-for-accelerated- crop-improvement-The-figure-depicts-the-use-of_fig2_267397050
  • 19. DEVELOPMENT OF DROUGHT RESISTANT VARIETIES • Research is in progress to produce crop varieties capable of tolerating reduced water conditions. • Crops like Corn, Wheat, and Rice, have become increasingly tolerant to drought with new varieties created via genetic engineering. • These varieties allow agriculture to succeed in poorer soil areas, thus adding more land to the global production base. Figure 9: Drought resistant crops https://www.technologynetworks.com/applied -sciences/news/breakthrough-in-development- of-drought-resistant-crops-355322
  • 20. Single Gene Analysis • Single gene sequencing may be appropriate for conditions caused by variants in a single gene, where the degree of diagnostic confidence is high. All the exons in the particular gene are sequenced. Que - When is single-gene sequencing done? Ans - Single-gene sequencing may be undertaken when an organism’s features are strongly indicative of a genetic condition caused by variants in a single Gene. Figure 10:. Single Gene Analysis https://www.tessresearch.org/genetic- sequencing/
  • 21. Advantages of Single gene Analysis • Can provide rapid genetic confirmation of a diagnosis if the plant’s features are sufficiently specific. • There is no possibility of incidental findings. • Focusing on a single gene means that there are fewer variants requiring clinical interpretation, and less chance of identifying Variants of Unknown Significance (VUS). Disadvantages of Single Gene Analysis • Not suitable for genetically heterogeneous conditions. • Will not identify any novel genetic causes of disease. Tables comparing the Advantages and Disadvantages of the different approaches to Gene Sequencing
  • 22. Molecular Markers • Molecular marker is a fragment of DNA that is associated with a certain location within the Genome. • Molecular markers are used in molecular biology and biotechnology to identify a particular sequence of DNA in a pool of unknown DNA. List of Markers Acronym Restriction Fragment Length Polymorphism RFLP Random Amplified Polymorphic DNA RAPD Amplified Fragment Length Polymorphism AFLP Variable Number Tandem Repeat VNTR Oligonucleotide Polymorphism OP Single Nucleotide Polymorphism SNP Table showing the list of markers and their acronym
  • 23. Applications of Markers in Plant Science. • Assessing variability of genetic differences and characteristics within a species. • Identification and fingerprinting of genotypes. • Estimating genetic distances between species and offspring. • Identifying the location of Quantitative Trait Loci (QTL). • Identification of DNA sequence from useful candidate genes.
  • 24. Selection of plant with Desired Morphological traits. Development of breeding populations. (F1 and F2 generation) Marker assisted selection of Plants with Desired traits Marker Validation in improved Plants Field traits of improved lines Expressing Desired Morphological traits Enhanced Plant Growth Yield and Stress tolerance Marker-Assisted Breeding for Abiotic Stress Tolerance in Crop Plants
  • 25. NOTE URL 1. National Rice Data Centre http://www.ricedata.cn/index.htm 2. Maize genome database http://maize.jcvi.org/ 3. Tomato functional genome database http://ted.bti.cornell.edu/ 4. Wheat genome information database http://www.wheatgenome.org/ 5. Rice genetics and genomics database https://shigen.nig.ac.jp/rice/oryzaba se/ Databases used for Major crops
  • 26. DISADVANTAGES OF BIOINFORMATICS Searching databases can sometimes become time-consuming. Costly to hold databases. Reliability of data stored is questioned. Error in sequence alignment can affect the outcome of structural analysis. Completely relying on the information is dangerous if the information is inaccurate.
  • 27. CONCLUSION • Applying bioinformatics to the study and characterize biological phenomena represents a fundamental shift in how scientists study living organisms. • Databases provide access to Gene information, gene expression data, and metabolite profiles, as well as the experimental conditions used to generate them. • Many genomic, Transcriptomic, Proteomic, and Metabolite databases available have the potential to accelerate the rate of functional discoveries in plant biology.
  • 28. ACKNOWLEDGMENT I would like to express my special thanks to the Head of my Department Dr Rajinder Kaur as well as my Supervisor Dr Harpreet Kaur and all the teachers who gave me this golden opportunity to make this wonderful project on the topic of Bioinformatics Approaches and its Application in Plant Science which helped me in doing a lot of research and I came to know about a lot of new things. Secondly, I would like to thank my friends who helped me a lot in finalizing this project.