431 Bioinformatics approaches and its application in plant science.pptx

Bioinformatics approaches and its applications in plant science

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 2 nd Sem (Seminar BSS4099)

2. CONTENT Introduction Definition Genomics Transcriptomics Proteomics Metabolomics The first genomic sequence – Arabidopsis thaliana Application of Plant Genomics in Plant Science Plant Breeding Plant Disease Management In Agriculture Crop Improvement Development of Drought-Resistant varieties Single Gene Analysis Molecular Markers Database used for major crops Disadvantages of Bioinformatics 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 .

4. BIOLOGY INFORMATICS BIOINFORMATICS

5. Definition Bioinformatics refers to the study of biological information using concepts and methods in computer science , statistics , and engineering . It is the analysis , collection , classification , manipulation , recovery , storage , and visualization of all biological information using computation technology. 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/plants400/Profiles/AB/Arabidopsis

11. 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

12. 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

13. 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.

14. In Agriculture 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/ecurriculum/Bsc_Hsc_Sem_2/flavrsavr%20tomato.pdf

15. 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

16. 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.

17. 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

18. 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

19. 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/

20. 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

21. Molecular Markers Molecular marker is a fragment of  DNA  that is associated with a certain location within the  G enome . 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

22. 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.

23. 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

24. 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/oryzabase / Databases used for Major crops

25. 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.

26. 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.

27. 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.