“OMICS” In Crop Breeding “OMICS” In Crop Breeding

Poornima KN Roll No: 9869

ContentsContents Introduction Omics Space

◦ Genomics◦ Transcriptomics ◦ Proteomics ◦ Metabolomics ◦ Phenomics

Case StudiesSummary Conclusion

Approaches and applications

INTRODUCTION

Molecular networks of cell controlling traits and phenotypes

• That one gene encodes one protein, which catalyzes one reaction and determines one phenotype is no longer the case.

How to capture all molecules and their interactions, dynamics, regulations and turnover … ?

How to determine the rate-limiting molecule and step ? How to predict ?

Manipulating one gene can cause pleiotropic effects ?

Large-scale biology – “OMICS” – Revolution in screening traits and develop novel improved organisms

Concepts to be investigated and understood

Crop BreedingDevelopmental biology

“Omics in plants”

Identify genes, promoters, mi RNAs, pathway components

Omics Platforms

GenomicsGenomicsGenomics – the comprehensive study of whole sets of genes &

their interactions (DNA microarrays)

Genome sequencing projectsGenome sequencing projects

Applications of Plant Genomics

Gene identification and cloning Gene prediction/ discovery Genetic mapping and locating genes Genome manipulation QTLs analysis Molecular markers and MAS Comparative genomics Gene banks and chromosome stocks Understanding expression profiles, responses and interactions

Potato is the first sequenced genome of an asterid, a clade within eudicots that encompasses nearly 70,000 species characterized by unique morphological, developmental and compositional features.

Autotetraploid- used a doubled monoploid line – Phureja DM 1-3 516 R44 (DM)

Heterozygous diploid breeding line RH89-039-16 (RH)

WGS- Illumina and Roche- 727 Mb which is 117Mb less than estimated genome size.

Repetitive sequences account for 62.2% of 452.5MB assembled genome with 29.4% occupied by LTR retrotransposons.

RNA seq data- 39,031 protein coding genes annotated and 9875 genes showed alternative splicing indicating more functional variation.

Comparative analysis and Genome Comparative analysis and Genome evolution studyevolution study

Orthologous and paralogous gene families Genome duplication

Analysis of syntenic blocks

Haplotype diversity and inbreeding Haplotype diversity and inbreeding depressiondepression

Vigor Modality representing zygosity

Inbreeding depression analysis

Euchromatic and heterochromatic region analysis

• Sequenced and assembled 1,644RH BAC clones generating 178 Mb of non-redundant sequence from both haplotypes• 3,018 SNPs induce PS in RH and 940 in DM 80 loci with FS in RH. • 246 genes specific to RH and 29 were DM specific.

Study of tuber biologyStudy of tuber biology

KTI gene organisation across potato genome

Phylogenetic tree and KTI gene expression heat map

Starch synthesis enzymes and genes involved in carbohydrate metabolism

Sources for genomicsSources for genomics

De novo sequencingRe sequencingMetagenomicsEpigenetics RNA sequencing - Transcriptomics

TranscriptomicsTranscriptomics The study of the transcriptome, the complete set of RNA

transcripts produced by the genome at any one time.

Transcript profiling methodsTranscript profiling methods

Whole genome transcriptome analysis- Microarray- SAGE- MPSS

Target genome transcriptome analysis- Northern blot- Dot blot- RT-PCR- RT-PCR

Application of transcriptomicsApplication of transcriptomicsDifferential expression of genesCo expression of genesGene interactionAlternative splicing of genes

Hiremath et al, 2011. Plant Biotechnology Journal

Studied biosynthesis of glucosinolates (GSLs) from amino acids found in the family Brassicaceae.

Discovery of two TFs- Myb28 and Myb29 involved in aliphatic GSL production by integrated omics approach.

Combined transcriptome coexpression analysis, mutant transcriptome analysis and GSL analysis.

Expression analysis GSL biosynthesis Expression analysis GSL biosynthesis genesgenes

Mutant analysis Over expression analysis

Sources of transcriptomicsSources of transcriptomicsExpression arraysTilling arraysMicroRNA arraysProtein arrays - Proteomics

ProteomicsProteomicsThe study of proteome, the structure and function of

complete set of protein in a cell at a given time.

Applications of proteomicsApplications of proteomics

Protein Mining – catalog all the proteins present in a tissue, cell, organelle, etc.

Differential Expression Profiling – Identification of proteins in a sample as a function of a particular state: differentiation, stage of development, disease state, response to stimulus or environments.

Network Mapping – Identification of proteins in functional networks: biosynthetic pathways, signal transduction pathways, multiprotein complexes.

Mapping Protein Modifications – Characterization of posttranslational modifications: phosphorylation, glycosylation, oxidation, etc.

Three Australian wheat cultivars (Triticum aestivum L. cv Kukri, Excalibur, and RAC875)

Shotgun proteomics study using iTRAQ (Isobaric tags for relative and absolute quantitation) approach.

Frontiers in plant science, 12 september 2011

Proteome analysisProteome analysis

Frontiers in plant science, 12 september 2011

Completion of the drought regime RAC 875 (tolerant) had the most number of protein changes (206) with Excalibur (tolerant) intermediate (177) and Kukri (intolerant; 168) the least.RAC875 has the highest capacity of the three cultivars for a cellular protein response to drought.Down regulation of proteins involved in photosynthesis and the Calvin cycle, consistent with avoidance of ROS generation in all three cultivars was observed. Known drought responsive proteins, including dehydrins, were also significantly up-regulated.The findings from this proteomic study support the physiological and yield data (Izanloo et al., 2008) previously reported between the three wheat cultivars (Kukri, Excalibur, RAC875) in response to cyclic drought stress. This highlights the importance of proteomics as a complementary tool for identifying candidate genes in abiotic stress tolerance in cereals.

Protein changes during drought stress

Sources of proteomicsSources of proteomics

Protein mixturesPost-translational modificationsBiomarker studiesExamination of metabolites - Metabolomics

MetabolomicsMetabolomics

Study of metabolome, collection of all metabolites in a cell, tissue, organ or organism.

Applications of metabolomicsApplications of metabolomics

Characterization of metabolismIdentification of regulated key sites in

network.Biofortification and genetic modificationInvestigation of gene function under stress

conditions

•Evaluation of metabolite concentrations of fruit pericarp alongside whole-plant parameters in an IL population in which marker-defined regions of the wild species S. pennellii are replaced with homologous regions of the cultivated variety M82 (S. lycopersicum).

•Harvest index, the measure of efficiency in partitioning of assimilated photosynthate to harvestable product, as the chief pleiotropic hub in the combined network of metabolic and whole-plant phenotypic traits.

•The combination of marker-assisted selection and metabolite profiling therefore represents a viable alternative to genetic modification strategies for metabolic engineering.

Sources of metabolomicsSources of metabolomicsToxicity assessmentNutrigenomics Forensic analysisPetrochemical analysisPhenotype analysis- (phenomics)

PhenomicsPhenomics Phenomics, the study of the phenome, where phenotypes are

characterized in a rigorous and formal way, and link these traits to the associated genes and gene variants (alleles).

Why Phenomics ?Why Phenomics ?

The genotype−phenotype map

Essential for assessing pleiotropic effects of genetic variation .Study the fitness to understand evolution – Pleiotropic effects on phenotype and their interaction with environment .Ideally identify relationships between genotype and phenotype as well as reveal correlations between seemingly unrelated phenotypes.

Traits measured on HTP phenotyping Traits measured on HTP phenotyping platformsplatforms

Leaf area Chlorophyll content Stem diameter Plant height / width Growth rate Transpiration rate Canopy temperature Biomass Root mass/growth Rate of soil drying Internode length Pigmentation Leaf rolling Leaf angle Leaf senescence/necrosis Photosynthetic efficiency Forage quality/digestability Tissue water content Ear/panicle size/number Salinity/drought/heat /frost tolerance

Criteria for traits amenable to high Criteria for traits amenable to high throughput analysisthroughput analysis

Measurements must be made rapidly, cheaplyHigh genetic correlation with key target

• Yield• Quality• Resource use efficiency• Abiotic/biotic stress resistance

High heritability• Minimise error variation• Minimise unwanted environmental variation

“High throughput” field phenotyping systems

• Infra red cameras to scan temperature profiles• Spectroscopes for measuring photosynthetic rates• Lidar to guage growth rates• MRI for study of root physiology

Maize leaf, laser confocal microscopy reveals a clear distinction between high activity of photosystem II in mesophyll cells (pink fluorescence) and low activity in bundle sheath cells (purple)—a distinction typical of C4 plants.

Phenomics provide snapshots of cellular structure – Required to understand the contrasting cellular features among C3 and C4 plants.IRRI- screening rice varieties with a cellular architecture best suited to house C4 enzyme assembly and those with muted photosystem II in bundle sheath cells.

Chlorophyll fluorescence, a measure of photosynthesis, in Arabidopsis seedlings and a wheat ear ( inset ) using a car engine dynamometer

The emerging discipline of phenomics will help foment the next green revolution. We now have the tools “to make quantum leaps in crop breeding,” says plant physiologist Robert Furbank, director of HRPPC.

IonomicsIonomics

Ionomics is the study of the ionome, involving quantitative and simultaneous measurement of the elemental composition of living organisms and changes in this composition in response to physiological stimuli, developmental state, and genetic modifications.

Inductively coupled plasma mass spectrometry

ApplicationsApplicationsIdentification of genes and gene networks

that regulate the ionome.Precise large-scale mutant screens for

study of genetic variation.Ionomic biomarkers in assessment of

particular physiological or biochemical state of plants.

Ionome analysis of arabidopsis trichomes using ICP-MS

Laser ablated inductively coupled plasma- mass spectroscopy

Summary Summary

Integrated data set for quick and precise breeding

The power of ‘omics’ approachesThe power of ‘omics’ approaches

Ionomics

Phenomics

Metabolomics

Proteomics Transcriptomics

Genomics

Conclusion

OMICS

“These are the tools we need to feed and

fuel the world.” – E.Finkel

Future concernsFuture concernsReduction in cost of technology usage.Development of bioinformatic tools for

data analysis and storage of databases.Human resource development for an

overall purview of technology to apply in crop breeding.