R Gene expression and transcription profiling in plants. Incorporating gene resistance and its transcription database.

1. R Gene Expression and Transcription Profiling
Presented By
Shraddha Karcho
Assistant Professor
Department of Plant Pathology
College of Agriculture, Tikamgarh
JNKVV, Jabalpur

2. OR gene
Resistance genes are genes in plant genomes
that convey plant disease resistance against pathogens
by producing R proteins.
The main class of R-genes consist of
OA nucleotide binding domain (NBS)
OA leucine rich repeats (LRR)
OA Serine /threonine protein kinase

3. Functions of Resistance Genes
OSignalling of plant stress hormones
OGeneration of reactive oxygen species (ROS)
OEthylene biosynthesis
ODefence gene activation leading to phytoalexin
biosynthesis,
OCell wall strengthening by the deposition of callose and
hypersensitive response
(Dixon et al.

4. Plant pathogen interaction and development of disease resistance

5. How do R gene/protein functions
Nucleus
Activatio
n of
defense
Elicitors recognized by R protein
Pathogen
Alters the gene expression
Elicitors / effectors
Membrane bound
Receptors – Effector interaction

6. Fungal pathogens and interacting R-genes

7. Bacterial pathogens and interacting R-genes

8. Nematode pathogens and interacting R-genes

9. Viral pathogens and interacting R-genes

10. Insects and interacting R-genes

11. Advantages of R gene
O When induced in timely manner, the concerted response
efficiently halts pathogen growth with minimal collateral
damage to the plant.
O No input is required from the farmer and no adverse
environmental effects.
O Efficient reduction of pathogen growth.
O Minimal damage to the host plant.
O Zero input pesticide from the farmer.
O Most importantly the environment friendly nature of such crops.

12. Disadvantages of R gene
OR genes are quickly defeated by co-evolving pathogens.
OMany R gene recognise only a limited number of pathogen
strain.
OR genes do not provide broad spectrum resistance.
OIntrogression of R genes into a elite cultivars by convention
breeding is a lengthy process.

13. Transcription profiling
O The study of the complete set of RNA transcript that are made from
an plants DNA.
O Also known as “Expression Profiling”
O It involves the quantification of gene expression of many genes in
cell or tissue sample at the transcription level

14. Features . .
O In the field of molecular biology gene expression profiling is the
measurement of the activity of thousands of genes at once
O Use to create a global picture of cellular function
O These profiles can distinguish between cells that are actively dividing
or show how the cells react to a resistance.
O In profiling, we can measure an entire genome simultaneously, that
is, every gene present in a particular cell.

15. Gene Network Diagram which
dynamically assembles genes
with known relationships. Green
indicates reduced expression,
red indicates increased
expression. The algorithm has
included unregulated genes,
white, to improve connectivity.

16. Heat maps of gene expression values show how experimental conditions
influenced production (expression) of mRNA for a set of genes. Green indicates
reduced expression. Cluster analysis has placed a group of down regulated
genes in the upper left corner.

17. Technologies for Measuring Gene Expression
O RNA gel blot (northern), in which a labelled probe is hybridized to an RNA
target and the resulting band size and signal intensity is used to confirm and
quantify expression
O Sequencing-based methods, these methods started with the use of
expressed sequence tags (ESTs), and now include methods based on short
tags, such as serial analysis of gene expression (SAGE) and massively
parallel signature sequencing (MPSS)

18. Single gene measurement
O In recent years, quantitative real-time PCR (QRT-PCR) has been
demonstrated to generate robust, quantitative expression data for a
single gene
O This method also offers rapid and reproducible results and a large
dynamic range.
O One of the major advantages of QRT-PCR is a broad dynamic range
that can precisely quantify transcript concentrations over more than
eight orders of magnitude.
O Modifications of this technology may go beyond expression analysis to
monitor RNA splicing or other applications

19. DNA Microarrays
O The DNA microarray has produced a revolution in expression analysis
O These chips simultaneously determine expression levels for thousands
of genes.
O Data are then analysed for patterns of expression that change over
various treatments or time points.
O This approach, though still widely used, requires the maintenance and
handling of microtiter dishes, validation of clones, and large-scale PCR
reactions.

20. Tag-Based Methods
O Exhaustive sequencing of ESTs (expressed sequence tags) is a common method for
gene expression profiling
O The abundance of an EST is an exact digital representation of the number of copies
of a transcript in the tissue.
O Large numbers of ESTs derived from diverse tissues produce quantitative estimates
of gene expression
O But ESTs are relatively slow and costly to generate, making it difficult to achieve
saturation of a library.
O A recent advance is MPSS, which is based on methods to clone individual cDNA
molecules on microbeads and sequence, in parallel, short tags or signatures from
these cDNAs.

21. APPLICATIONS OF TRANSCRIPTIONAL PROFILING
O These methods include the numerous clustering techniques designed
to construct groups of genes with related patterns within the dataset.
O This simplifies and structures the data based on inherent patterns
O The extraction of meaningful data requires analytical strategies and
the interpretation depends on close interactions among biologists,
computer scientists, and statisticians.