Plant Biology Fall 2006

1. BISC 367 - Plant Physiology Lab Spring 2009 Plant Biology Fall 2006 • Tutorial March 5 2009: • Due date for the 2nd report is March 13 • Please see me to discuss your research project today • Reading material: • Negi et al., (2008) Ethylene regulates lateral root formation and auxin transport in Arabidopsis thaliana. Plant J. 55: 175-187.

2. Maize seedlings growing at low Yw From Spollen et al., Plant Phys. 122:967 (2000) ABA maintains root growth by suppressing ethylene production • FLU (fluridone) is an inhibitor of ABA biosynthesis • AOA, AVG & STS are inhibitors of ethylene action or biosynthesis • Inhibiting ethylene production or action in ABA-deficient seedlings restored growth in water deficit stressed seedlings • ABA suppresses ethylene production and thereby maintains root growth

3. Root system architecture is plastic and influenced by the environment LR formation is suppressed in drought stressed roots because: • Their elongation growth is reduced • Primordia are formed but they don’t grow out or develop into LRs • The repression of LR formation is dependent on ABA • May involve ABA checkpoints that operate during LR development Non-stressed seedlings Salt-stressed seedlings

4. Root Data - observations • etr1 mutant • Avg root length control WT = 36.7 mm • Avg root length salt WT = 27.4 mm • Salt reduced growth by 25% • Avg root length control etr1 = 34.3 mm (1 plate had short roots – deleted) • Avg root length salt etr1 = 25.8 mm • Salt reduced growth by 25% • ein2 mutant • Avg root length control WT = 37.1 mm • Avg root length salt WT = 34.7 mm • Salt reduced growth by 6% • Avg root length control ein2 = 36.5 mm • Avg root length salt ein2 = 32.4 mm • Salt reduced growth by 11% • Looks like WT – don’t include in analyses

5. Root Data • aba1 mutant • Avg root length control WT = 35 mm • Avg root length salt WT = 35 mm • Salt had not effect on growth • Avg root length control aba1 = 14.7 mm • Avg root length salt aba1 = 16 mm • Salt had no effect on growth • abi1 mutant • Avg root length control WT = 33.61 mm • Avg root length salt WT = 33.1 mm • Salt had no effect on root growth • Avg root length control abi1 = 31.2 mm • Avg root length salt abi1 = 21.2 mm • Salt reduced growth by 32%

6. Root Data • Data crunching…….. • Create spreadsheet for all ABA mutants and another for all ET mutants • Combine all WT data and include in both spreadsheets • Calculate average root growth and LRD for all WT seedlings • To calculate LRD, divide # LRs by root length on a seedling basis • Calculate average for root growth and LRD for mutant genotypes • Do this on a per plate (replicate) basis as each plate should give similar values • Then calculate a mean for all seedlings for both replicate plates • On excel spreadsheet delete seedlings with roots that are < 50% of the mean length • When you delete a seedling, delete all data for that seedling (i.e. LR data too) • Normalize root length and LRD data for mutant genotypes by control • Put normalized data in a separate column • Organize excel worksheet so that all data are in separate rows • Save data as .csv • Open data in JMP (JMP can be downloaded for free) http://www.microstore.sfu.ca/downloads.htm

7. Root Data • Analysing data in JMP (statistical analyses package) • On the data sheet everything except the data columns are “nominal” • Data columns are “continuous” • Select menu “Analyse” • Select “Fit Model” • In “Fit Model” window select “Root length” from under “Select Columns” and hit button “Y” • Select “Treatment” and “Genotype” under “Select Columns” and then the “Macros” button under “Construct model Effects” • When the menu drops select “Factorial to Degree”. Ensure that “2” is entered next to degree • Hit “Run Model” • In analyses window “Genotype*Treatment” use “least sq means” and “std error” to construct data graphs • Hit the down arrow to the left of “Genotype*Treatment” and select “student’s t-test” to note the statistical classes

8. Root Data Lateral root density (# LR/ mm root length) A B B C • Complete data analyses for your normalized data too • Select “normalized by control” as “Y” (step 3 on previous slide) • Complete data analyses for root length and for LRD

9. Root Data • Data for paper: • Plot 1: absolute root length data for ET mutants vs WT • Plot 2: normalized root length data for ET mutants vs WT • Plot 3: absolute root length data for ABA mutants vs WT • Plot 4: normalized root length data for ABA mutants vs WT • Plot 5: absolute LRD for ET mutants vs WT • Plot 6: normalized LRD for ET mutants vs WT • Plot 7: absolute LRD for ABA mutants vs WT • Plot 8: normalized LRD for ABA mutants vs WT

10. Root Data A B B C Root length (mm) Graphs (ABA mutants) • Root length • Relative root length • Root length for each genotype in presence of salt was normalized by growth under control conditions • Allows comparison between genotypes for the ability of salt to reduce growth • Comparison usually made to WT • Graphs show that: • Salt reduced root growth for all genotypes except aba1 • Control and non-stressed roots of aba1 and abi1 were shorter than WT • abi1 was more sensitive to the ability of salt to reduce growth than WT and aba1 was less sensitive D D A B B B C Relative root length D

11. Root Data A B LRD (# LR / mm root length C CD C Graphs (ABA mutants) • LRD data • Relative LRD • LRD of salt-stressed roots of each genotype was normalized by the LRD of non-stressed roots • Allows comparison of effect of salt on LRD relative to WT • Graphs show that: • Salt reduced LRD • Non-stressed roots of aba1 and abi1 had a lower LRD than WT • Salt-stressed aba1, but not abi1, had a lower LRD than WT • abi1 and aba1 were more resistant to the ability of salt to reduce LRD D A A A B Relative LRD B C

12. Root Data AB A B C Root length (mm) Graphs (ET mutant) • Root length • Relative root length • Graphs show that: • Under control conditions the root length of etr1 was similar to WT • etr1 mutant was more sensitive to salt stress than WT AB A B C Relative root length

13. Root Data A B B LRD (# LR / mm root length Graphs (ET mutant) • LRD data • Relative LRD • Graphs show that: • etr1 roots had a higher LRD than WT under both control and salt-stressed conditions • etr1 was less sensitive to the ability of salt to reduce LRD than WT C A A Relative LRD B C

14. Hormonal regulation of root growth • Writing your report • Introduction should contain: • Introduction to root system architecture • What is it? Why is it important? It is dynamic. What processes influence it (root elongation, root branching) • Root elongation • Regulation by hormones • Lateral root formation • Regulation by hormones • Influence of abiotic stresses such as drought and salinity on root system architecture • Stress and root elongation • Stress and lateral root formation • Role of hormones • Introduce this study

15. Hormonal regulation of root growth • Writing your report • Results • Organization (use section headings) • Section on root elongation (with data) • Section on lateral root formation (with data) OR • Describe effect of ET on root elongation and lateral roots (show ET data) • Describe effect of ABA on root elongation and lateral roots (show ABA data) OR ???

16. Hormonal regulation of root growth • Writing your report • Discussion • Organization • Always start with a good opening sentence(s) • For example, overall summary statement from what is known already about root systems and what has been learnt from the current study • Use section headings to organize ideas e.g. • Mutations in ET signaling pathways increase root twirling • ABA promotes root growth • Salt stress reduces lateral root formation • Ideas for sections • Root system architecture (absence of stress) • Hormonal regulation • Root growth • LR formation • What new information has your data added and does it agree with the literature?

17. Hormonal regulation of root growth • Writing your report • Discussion • Ideas for sections • Root system architecture of salt or drought-stressed plants • Hormonal regulation • Root growth • LR formation • What deductions can you make regarding the hormonal regulation of these processes based on your data, does it agree with the literature?