Drought Phenotyping Protocol for Potato
1
Introduction
Drought has a large influence on plant fitness and productivity. An in-exhaustive scheme
of potential drought impacts and plant reactions is given in figure 1. Drought phenotyping
monitors the drought environment, its impact on plant performance, and water stress
triggered responses of the plant.
Environmental variables such as soil- and climatic factors, the complexity of traits
contributing to crop yield, and the diversity of plant reactions to water stress make
drought phenotyping challenging. Careful choice of drought testing environments and
robustness of phenotyping parameters are essential for successful drought phenotyping.
Soil water content/potential
Drought environment
Decreasing soil water content, high vapor pressure deficit,
irradiation
Air temperature, relative humidity
Plant reactions
PERCEPTION OF WATER STRESS: CELL WATER STATUS – HORMONE BALANCE – OXIDATIVE STRESS
Leaf water content/potential
ABA, Gibberellin
Stomatal closure
Gene expression analysis
GENE EXPRESSION
Plant (organ) size
Morphological adaptation
Reduced photosynthesis
High water use efficiency
Water use/transpiration efficiency
Plant height, internode distance, leaf area
Reduced growth
Osmotic adjustment
Metabolite analysis, leaf water potential
Yield (partition), GM, DSI
Reduced yield
Cell rescue
Plant vigor, gene expression
Porometry
Chlorophyll fluorescence, CO2 uptake
Carbon partitioning traits
Metabolite and gene expression analysis
tolerance
Fig 1.: Environment, plant performance and plant responses to drought. Phenotyping parameters describing strength of drought,
plant performance and plant responses are listened in boxes.
2
Drought Environments
2.1
Hydroponics
Hydroponic culture allows plant cultivation under defined and reproducible osmotic
stress conditions by adding an osmoticum such as polyethylene glycol or sorbitol to the
culture medium. This system supports testing of a large number of plants for adaptation
and/or acclimation of vegetative parts to osmotic stress conditions. However, the artificial
experimental setting imposes different stress conditions to the plant than drought in the
field, consequently the transferability of findings to natural environments is limited.
Further, hydroponics does not allow yield assessment, which is a crucial component in
drought tolerance testing of potato. Therefore, hydroponics might provide a suitable
testing system for specific adaptation or acclimation reactions of plants to water stress,
but cannot replace phenotyping in more natural settings.
1
2.2
Growth Chamber
Growth chambers equipped with temperature and air humidity control are ideal
environments for drought tolerance studies providing reproducible drought conditions.
But due to space limitation this test system is only practical for a small number of
genotypes. Yield assessment is possible in growth chambers, when potato plants are
grown in large containers instead of in pots. However, several physiological parameters
can be only performed on pot plants, such as transpiration efficiency studies.
2.3
Greenhouse
Greenhouse-grown plants provide a suitable experimental setting for many drought
tolerance-related studies. As already stated above, for yield assessment plants have to be
grown in large containers instead of in pots. For pot-grown plants it is important to avoid
position effects by randomly moving the pots. A further concern for greenhouse trials is
the amount of light available for the plants, as glass roofs might absorb a significant
portion of sunlight and thus cause a strong decrease of irradiation, which might influence
drought responses.
2.4
Rain-Out Zone
Rain-our zones provide an ideal environment for drought screenings. They consist of a
roof protecting the plants from rainwater and are equipped with plastic barriers at the
borders and below the test plot to avoid water inflow from the sides or from below
ground. Moderate construction costs allow large dimensioned rain-out zones harboring
thousands of plants. Increased heat or air humidity due to roofing might influence the
drought environment. So either mobile roofs that cover the plants only during a
precipitation event, or good aeration of the rain out zone is required.
The surface of rain-out zones should be completely even to avoid water accumulation in
pits. The soil depth above the plastic barrier should be at least 50 cm to allow deep
rooting. Water should be applied by drip irrigation.
2.5
Field
Field testing is the cheapest and the most natural way for drought phenotyping, but also
the most affected by environmental impacts. Field testing is relatively straight forward in
zones with negligible precipitation, like in dry seasons or desert zones, as long as
excessive heat does not interfere with the drought trial. Field plots should have
homogenous soil type, should be flat to avoid water accumulation in pits and should be
equipped with an appropriate irrigation system, ideally with drip irrigation.
3
Experimental Design
Generally drought trials are performed using two regimes: a well watered control, which
is irrigated to field capacity, and a drought treatment, where plants are exposed to water
stress. An appropriate number of repetitions, each with a suitable number of plants, has to
be planted for each treatment. In field- and rain-out zone trials, a minimum of 3 blocs of
5 plants per treatment i.e. 3 biological repetitions should be used. When destructive
sampling is required, a higher number of plants per bloc is necessary. When space and
seed is not limiting, at least 4 repeated blocs of 10 plants should be used for each
treatment. The plants at the border of the blocs are not used for evaluations because of
2
influences by neighboring genotypes or field borders. Blocs should be arranged in a
random complete bloc design.
In trials with pot plants, a minimum of 5 individual plants per genotype and treatment
should be used. Each individual plant represents a biological repetition. The position of
the pots has to be completely randomized and border effects should be excluded by
randomly moving the plants every few days.
In all environments listened above, except hydroponics, drought might be applied by
stopping irrigation at an appropriate time point. Generally drought treatments are applied
during a defined developmental stage of the plants, such as tuberization. For rain-out
zones or field settings it is recommended to choose clones with similar phenology in
order to expose the plants to drought at identical developmental stages. Drought trials
using pot-grown plants allow more flexibility, as irrigation can be stopped individually
for each pot. Duration of the drought treatment depends of the aim of the study and might
be chosen either for a fixed period, dependent of the soil type and irradiation, lasting for
30 to 60 days, or drought might be applied until a certain plant- or soil parameter reaches
a defined threshold (table 1). The threshold values given in table 1 were applied in potato
drought tolerance trials at CIP or by collaborators and might vary with experimental
setting, soil type, environment and genotypes.
Parameter
Threshold
value
Evaluation method
Required
measurements
Soil water content
20%*
Gravimetrical soil water determination
Soil water potential
-0.6 to -1 MPa
Sensor
Leaf water content
65-70%
Tourneux et al. (2003)
Leaf water potential
-1 to –2.5 MPa
Tourneux et al. (2003), Callster et al.
(2006)
Schoellander bomb, osmometry
Photosynthesis
efficiency
1 µmCO2/m2/sec
Photosynthesis analyzer
Reading
Soil fresh weight
Soil dry weight
Reading
Weight of fully hydrated leaf
Leaf fresh weight
Leaf dry weight
Tab. 1 Useful parameters to determine duration of drought treatments in phenotyping studies. *)
value might strongly vary between different soil types.
An alternative drought treatment involves irrigation with a limited amount of water
during the whole cropping season, instead of stopping irrigation completely. The amount
of water required to reach stress conditions has to be determined by quantification of
evapotranspiration in the given environment. For stress treatments irrigation should be
lowered to 30 - 50% of the water evapotranspiration of well watered plants. Under low
irradiation condition, providing 200 to 300 mm of water during the whole growing season
distributed over weekly irrigation events is a suitable drought treatment for potato.
4
Drought phenotyping parameters
Phenotyping has to capture three aspects: the strength of drought, the effect of drought on
the plant performance and the plant response. Evaluation parameters for drought trials
have to be chosen appropriately to quantify the impact of a defined drought event on
plant performance and to distinguish between responses leading to drought tolerance and
other stress responses pinpointing susceptibility of the plant to water stress. A list of
parameters useful for drought phenotyping is given in table 2.
3
Environmental data are recorded over the whole duration of the phenotyping experiment
and comprise climate data (temperature, irradiation, for field trials also precipitation) and
soil water content or potential. Monitoring plant performance involves visual scoring as
well as quantitative measurements. Quantitative measurements are taken from at least 3
biological repetitions. Additionally technical repeats of measurements have to be taken to
allow determination of means and standard deviations and to assess significance of
differences between clones and treatments by T-test. Analysis of genomics data,
particularly microarray data, need specific significance analysis beyond T-tests.
PARAMETER
ENVIRONMENT
ACQUIRED
DATA
TIME POINT
Irradiation values
over time, taken
during porometry
and
photosynthesis
analysis
Constantly during
drought
treatment,
recorded by a
data logger
METHOD
COMMENT
Environmental parameters
Irradiation
Gc, G, RoZ, F
Sensor
Gc, G, RoZ, F
% soil water
content, mean,
STD
Weekly over
drought
treatments.
Gravimetrically
Soil water potential
Gc, G, Roz, F
Soil water energy
state
Weekly over
drought treatment
Tensiometry,
thermocouple
psychrometry,
electrical conduction
Vapor pressure deficit
Gc, G, RoZ, F
% relative air
humidity over time
Continuously,
recorded via data
logger
Hygrometer and
thermometer
Precipitation
F
Mm precipitation
/m2
Continuously
Weather station
Continuously
Weather station,
thermometer
Weekly from 28
days after
planting on
Careful visual
analysis of above
ground plant parts ,
and on plants
especially reserved
for this purpose, also
of stolons.
Weekly after
drought onset
Visual evaluation
Weekly
Leaf area meter,
Tetracam, or
scanning and
determination of
surface of all leafs of
sampled plants
Soil water content
Temperature
Gc, G, RoZ, F
Temperature
Required control for
porometry and to determine
oxidative stress levels
Measurement of drought
stress independent of plant
parameters. Number of
samples required depends
of the design of the
experimental plot. Minimum
for rain-out zone or field
trials: one sample for every
second row and 4 blocs.
Adsorption of water onto soil
particles and solutes
dissolved in the soil water
affect the potential energy of
the soil water and each of
these factors must be
characterized in the soil
water reference state.
Vapor pressure deficit is
beside soil water content the
most important measure to
quantify the drought stress
imposed on the plants.
Additional heat stress
impost on water-stressed
plants is influencing plant
reactions.
Plant development, morphology
Phenology
Gc, G, RoZ, F
Tuberization time
point
Earlyness
Senescence
Rating from 0 – 10
Plant vigor
Gc, G, RoZ, F
Plant health and
vigor rating from 0
to 10
Leaf area and ground
cover
Gc, G, RoZ, F
Leaf area per plant
Leaf area per
ground area
Important parameter for
normalizing photosynthesis
and porometryparameters
4
Specific leaf area
Gc, G, RoZ, F
Plant height
Gc, G, RoZ, F
Internode distance
Gc, G, RoZ, F
Root size
Gc, RoZ, F
Leaf area per g
leaf mass
Mean for each
accession and
treatment
Mean for each
accession and
treatment
3 time points
under drought
Leaf area data / leaf
weight
Used to normalize
transpiration efficiency data
Every two weeks
Measurement
Measurement for plant
productivity
Every two weeks
Measurement
Measurement for plant
productivity
Root length and
weight
Terminal harvest,
ideally also at 2
time points during
drought stress
Measurement
Biomass
distribution, tuber
number, yield,
fresh and dry
weight, means,
STD
Shoot material:
14 days after final
harvest
Tubers and roots:
final harvest
Weighing, counting
Mass of above-ground
tissue is determined 2
weeks before harvest.
Wilted leaves due to
drought-related senescence
might cause biases for this
measurement.
Harvest
Calculation based on
yield data
Predictor of plant
performance under stress
and non-stress conditions
Harvest
Calculation based on
yield data
Agronomical analysis
Yield partition
Gc, RoZ, F
Geometric Mean
Gc, RoZ, F
Drought Susceptibility
Index
Gc, RoZ, F
Square root of
yield under control
conditions (Yc) x
yield under stress
conditions (Ys)
DSI: (1-Ys/Yc)/(1Ms/Mc) (Ys= yield
under stress, Yc =
yield control, Ms
mean of all
genotypes under
stress, Mc = mean
of all genotypes
control
Plant water status
Relative leaf water
content (RWC)
Gc, G, RoZ, F
% leaf water
content
Weekly after
drought onset
Osmotic potential in
leaves (LWP)
Gc, G, RoZ, F
MPa
Weekly after
drought onset
Gc, G, RoZ, F
cm/s
mean of 4
repetitions per
plant
Weekly after
drought onset
either at specific
day time or over
time course from
8am to 4 pm
every 2 hours
Gc, G
g water per g
biomass
Daily after
drought onset
Stomatal conductance
Transpiration efficiency
Water use efficiency
a) Gc, G, RoZ,
F
b)Only potgrown plants
a) 12C/13C ratio
b) g water/g
biomass
a) after harvest
b) weekly after
drought onset
Weighing fresh, rehydrated and dried
leaves. On 3
individual plants per
clone and treatment
Osmometer, on 3
individual plants per
clone and treatment
Porometer
Weighing pot grown
plants irrigated with
defined amount of
water
a) C isotope
discrimination
b) Weighing pot
grown plants irrigated
with defined amount
of water
Tourneux et al. Agronomie
23 (2003) 181–190
Tourneux et al. Agronomie
23 (2003) 181–190
Measurement on apical
leaflet of 3rd fully developed
leaf of main stem, on 4
individual plants per clone.
Ekanayake and DeJong
1992, Annals of Botany
70:53-60
Ray et al. Plant and Soil
239: 113–121, 2002
a) Rebetzke et al. Crop Sci.
42:739–745 (2002).
Plant health
Reflectance/absorbance,
transmittance
Gc, G, RoZ, F
Absorbance and
reflectance spectra
Every two weeks
Spectroradiometer
Gutierrez-Rodriguez et al,
Austr. J. Agr. Research,
55:1139-1147, 2004
5
Photosynthesis
Chlorophyll content
Gc, G, RoZ, F
Mean and STD
Chlorophyll fluorescence
Gc, G, RoZ, F
Maximum quantum
yield
Photosynthesis
efficiency
Gc, G, RoZ, F
M CO2/min
Weekly after
drought onset
Weekly from day
30 after planting
on at defined day
time. 2-weekly in
two h intervals
over whole day
on an appropriate
number of clones.
Weekly from day
30 after planting
on at defined day
time. 2-weekly in
two h intervals
over whole day
on an appropriate
number of clones.
SPAD,
Spectroradiometer
Chlorophyll
fluorescence analyzer
Chlorophyll content
measurements using SPAD
have to be standardized for
each clone by chemical
analysis in order to allow for
comparison between clones.
Azia and Stewart, J. Plant
Nutrition (2001) 24:961966
State of photosystem II,
Measurement on apical
leaflet of 3rd fully developed
leaf of main stem, on 4
individual plants per clone.
Maxwell and Johnson
(2000), J. Exp. Bot. 51:359368
CO2 probe
Nitrogen uptake
Nitrate reductase and
glutamine synthetase
activity
Gc, G, RoZ, F
Mol NO2/h
Minimum 3 time
points during
drought
treatment.
Stressed and
control plants.
Enzyme activity
measurement
Monitors N-assimilation and
C-N balance
HPLC
Monitors concentration of a
key stress hormone in
tissues
Hormone status
Abscissic acid (ABA)
Gc, G, RoZ, F
mol/g dry matter
Gibberellin
Gc, G, RoZ, F
mol/g dry matter
Minimum 3 time
points during
drought
treatment.
Stressed and
control plants.
Minimum 3 time
points during
drought
treatment.
Stressed and
control plants.
HPLC
Genomics, Metabolites
Metabolites (sugars,
amino acids, acids,
polyamines)
Gene expression I
Gene expression II
Gc, G, RoZ, F
Gc, G, RoZ, F
Gc, G, RoZ, F
mol/g dry matter
Minimum 3 time
points during
drought
treatment.
Stressed and
control plants.)
Expression relative
to control plants
2- 3 time points
during drought
treatment.
Stressed and
control plants.
Real Time PCR
Gene list (approx 30 genes),
including transcription
factors, signaling genes,
genes of carbon and
hormone metabolism, stress
response genes (Table 3)
Expression relative
to control plants
2- 3 time points
during drought
treatment.
Stressed and
control plants.
Microarrays
Data on several thousands
of genes simultaneously
GC-MS
6
Table 2: Parameter for drought tolerance pheotyping of potato
5
Measuring and Sampling
An experimental bloc consists of at least 5 plants of a clone. For measuring and sampling,
the 3 central plants of a bloc are used to avoid neighbor effects. Porometry,
spectroradiometry, SPAD and photosynthesis efficiency measurements are performed on
the apical leaflet of the third fully expanded leaf of the main stem. Ideally, when only a
moderate number of accessions is analyzed, 3 plants of a bloc and 3 blocs per treatment
are measured. When a large genotype set is under investigation, one plant per bloc is
chosen, labeled and used for measurements at each time point.
For relative leaf water content analysis whole 3rd leaves of the main stem are sampled,
covered with saran wrap and processed for RWC measurement. For leave water potential,
leave discs are taken from the apical leaflet of the 3rd fully expanded leaf using a cork
borer and processed in an osmometer.
The amount of destructive sampling for biochemical and genomic analysis depends of the
measurements to be taken. Ideally, samples from the three central plants of a bloc are
pooled. For leaf samples, the third leaf or an appropriate number of leaflets of the third
leave is taken. For stolons, all stolons of a plant are pooled and from roots distal parts
with about 2 mm diameter are sampled, rapidly cleaned from soil and rapidly rinsed with
distilled water. For tuber sampling, slices of about 0.5 cm are cut from the middle of
washed and unpeeled tuber in longitudinal and transversal direction. The plant material is
dripped in liquid nitrogen immediately after harvest in order to “freeze” the condition of
the plant, transported to the laboratory under liquid nitrogen and kept at -80ºC for
genomics analysis or -20º for metabolome analysis. Samples for metabolite analysis are
lyophilized and ground before extraction.
6
Data Evaluation
A phenotyping flow scheme of a typical droughty trial on potato is given in fig. 2.
Clone selection
Selection of testing environment
Field experiment
Collection of environmental data:
Description of drought environment
Monitoring plant performance
(measurements, sampling)
Yield assessment
(GM, DSI)
susceptible
Fig.2: Phenotyping scheme for potato
tolerant
Trait analysis:
PS traits
Stomatal traits
C-partition related traits
Osmotic adjustment
Detoxification-related traits
7
6.1
Environmental Parameters
Soil water content and vapor pressure deficit are key drought stress descriptors and are
used to normalize quantitative plant parameters. Irradiation values serve to normalize
porometry and photosynthesis measurements and temperature and humidity
measurements result in vapor pressure deficit values that also serve to normalize
phenotyping data.
6.2
Plant Development and Morphology
Drought influences plant development. Dependent of the genotype, timing and strength
of drought, water stress might accelerate or delay flowering and tuberization, or slow
down canopy growth and tuber bulking. It is important to measure differences in earliness
between clones in order not to confound drought tolerance and drought escape.
Recording morphological and phenological parameters assists in measuring the impact of
drought on plant development. Leaf area is an important parameter for the normalization
of photosynthesis or transpiration-related measurements. Determination of root size is
reveals differences in access to soil water between clones.
6.3
Agronomical Analysis
Yield maintenance under water stress conditions is the principal measurement of drought
tolerance. Yield data under drought and control conditions are used to determine the
geometric mean (GM) of yield, which is a good predictor of genotype performance in
stress and non-stress environments. GM is calculated as √(Yield under stress x Yield control).
Further, yield data are used to calculate the drought susceptibility index, which is a
measurement for the relative drought resistance of a genotype compared to the mean of
the investigated accessions and is calculated as (1-Yieldunder stress/Yieldcontrol)/(1-mean under
stress/meancontrol).
Yield partition analysis reveals differences in carbon allocation to different plant tissues.
6.4
Plant water status
Relative leaf water content measures differences in hydratation status of leaf tissue and is
an indicator for the capacity of the plant to maintain its water status. Leaf water potential
reveals the water up-take capacity of the plant from a drying soil and also estimates
osmotic adjustment of the plant tissue during drought stress.
Stomata control transpiration and have the tendency to be closed under water stress in
order to avoid water loss. However, closed stomata also inhibit CO2 uptake and thus limit
photosynthesis. Measuring stomatal conductance in connection with leaf area, relative
leaf water content, and photosynthesis efficiency allows to identify stomatal and nonstomatal effects on photosynthesis efficiency under drought.
Transpiration efficiency is an indicator for water relations in the plant during soil drying.
The sooner the amount of transpiration drops in a plant grown on a successively drying
substrate, the lower is the capacity of the plant to extract soil water and thus the higher is
its drought sensitivity.
8
Water use efficiency describes how much water a plant needs per unit of produced
biomass or yield. Plants with high water use efficiency are desirable for drought tolerance
breeding, however, there is a multitude of traits determining water use efficiency, such as
gas exchange efficiency, carbon allocation, growth regulation and transpiration
efficiency, which themselves are determined by many different traits.
6.5
Plant Health
Sensing spectral reflectance data of crop plants allows to detect crop stress in very early
stages. Spectra of solar radiation reflected and absorbed by the crop canopy are measured
to uncover information about a crop's health. Spectroradiometers monitor the continuous
spectrum from 350nm to 1050nm. Recording data over treatments and genotypes and
correlating these data to physiological and agronomical parameters allows to translate
spectral information into of the crop's water or nitrogen status.
6.6
Photosynthesis
Plant productivity depends on the efficiency of photosynthesis. Drought lowers
photosynthetic efficiency through increased photorespiration through lack of CO2 due to
stomatal closure. Determination of the status of photosystem II by measuring chlorophyll
fluorescence and determination of CO2 uptake by the plant are basic parameters to
identify genotype-dependent differences in photosynthetic efficiency under drought.
6.7
Nitrogen uptake
Nitrate reductase is a central enzyme of the nitrogen metabolism in the plant. Nitrate
uptake and carbon assimilation are coordinated in the plant, but might be impaired under
drought. A decrease in nitrate reductase activity in stressed plants indicates increased
stress susceptibility of the plant. Nitrate reductase also catalyzes the formation of nitric
oxide, an important messenger for abscissic acid biosynthesis and stomatal closure.
6.8
Hormone Status
Abscissic acid is a central hormone for drought stress signaling. It regulates drought
responses such as stomatal closure, drought induced root growth and gene expression
changes. Quantification of ABA over time is a good indicator for drought stress and can
be related to plant drought responses.
Giberellins are hormones regulating plant development and are involved with
tuberization in potato. Drought changes the gibberell composition in plant tissues,
causing alterations in plant development, such as canopy size reduction or changes in
tuberization timing and efficiency.
6.9
Genomics and Metabolomics
Determination of changes in metabolite content and gene expression provides a bulk of
data giving insight into plant stress responses. Measurements are expensive and time
consuming and thus are only practical for the investigation of a small genotype set,
mostly for drought tolerance trait capture.
Metabolite analysis yields data on sugar and sugar alcohol accumulation and reveals
changes of amino acid patterns in plants, which can be interpreted as osmotic adjustment
under drought. Genotypic variation in metabolite concentrations yields important
information on clone-specific differences in drought adaptation.
9
Gene expression changes monitored at different time points during drought pinpoint
drought-induced functions over time. Microarray-based gene expression assessment is
most informative, but also most expensive. It allows the monitoring of the expression of
several thousands of genes, which can be attributed to functions and/or biochemical
pathways. These data can be used to define candidate gene lists for drought tolerance.
A drought tolerance candidate gene list has been established for potato (GCP, SP2,
Cluster 3). This list contains a set of drought-inducible transcription factors driving
expression of many drought response genes. An early and efficient up-regulation of these
genes contributes to efficient drought adaptation of the plant. Similar conclusions can be
drawn from the activation of specific signaling genes such as kinases or phosphatases.
Virtually all kinds of stresses cause accumulation of active oxygen species in the plant.
Oxidation status is a crucial regulator of cellular functions, while excessive oxidative
stress causes cell death. A bulk of genes involved in mitigating effects of oxidative stress
is activated under drought. High expression of these genes is considered as a marker for
stress tolerance.
Groups of genes comprising e.g. “late embryogenesis abundant-” (LEA-) genes is known
to protect cells from adverse effects caused by drought. High expression of these genes
also is a marker for drought tolerance.
Candidate genes used for Real Time PCR gene expression analysis are listed in table 3.
Gene
Myb
CAAT binding factor
HLZ AtHB-7
DREB1A
HLZ protein AtHB-12
Protein phosphatase 2C
SNF-1-related protein Kinase
Protein phosphatase 2C
Glutathion-S-transferase
Thioredoxin
Superoxyd dismutase
Peroxyredoxin
Rab-18
Dehydrin
LEA5
RD22
WCOR 413
Fatty acid elongase
Lipid Transfer Protein 1
Sucrose Synthase
Enolase
Invertase
amylase
Trehalose phosphate phosphatase
delta-1-pyrroline-carboxylate-synthase
Proline dehydrogenase
Cystein protease
TIGR Gene Index No.
BQ508846
TC127518
TC113966
TC116037
TC113966
TC112267
TC132860
TC119843
TC117080
TC160759
TC139039
TC141787
TC109380
TC134741
TC103181
TC112053
TC140461
TC105983
TC 145196
TC135042
TC133954
TC124949
TC126648
TC120885
TC128842
TC127497
TC112050
Function
Transcription regulation
Transcription regulation
Transcription regulation
Transcription regulation
Transcription regulation
Signaling
Signaling
Signaling
Redox regulation
Redox regulation
Redox regulation
Redox regulation
Water stress response
Water stress response
Water stress response
Water stress response
Cold acclimation
Cuticula strengthening
Membrane stabilization
Sugar metabolism
Sugar metabolism
Sugar metabolism
Sugar metabolism
Sugar metabolism
Proline metabolism
Proline metabolism
Protein degradation
Table 3: Drought
tolerance candidate
genes used for Real
Time PCR gene
expression analysis
for
phenotyping
potato
drought
responses.
TIGR
Gene
Index:
http://compbio.dfci.ha
rvard.edu/tgi/cgibin/tgi/gimain.pl?gud
b=potato
10
7
Data Storage and Analysis
Drought phenotyping monitors the complex plant drought responses and environmental
variables. Capturing all these variables implicates collection of large data sets and make
them available for analysis. Data formatation best is done immediately during recording
in MS-Excel sheets appropriate for analysis in SAS or R. Data deposition in databases for
analysis over years is recommended. Statistical analysis of data depends on the kind of
data collected. Morphological, agronomical and physiological data can be analyzed as
described in Gomez and Gomez (1984). Genomics data, such as Real Time PCR data
should be processed according to Pfaffl et al (2002). For microarray analysis, a range of
analysis methods has been proposed. Methods according to Wolfinger et al. (2001) and
Tusher et al. (2001) are widely used and were found appropriate.
8
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