Phenotyping sugarcane plants for drought tolerance

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3+ years

Soil Structure Soil Fertility Seed Bank

1 year

Diseases Nitrogen Water Weeds

0.5 years Weed Control Struggle Grazing

Sowing Date Density No Tillage Disease/Insect Control Irrigation


Whole Plant Level Defenses

Tissue Level Defenses

Cellular Level Defenses


Avoidance: Plant maintain adequate plant water status Drought Avoidance under soil water deficit

Tolerance: Ability of remain viable Drought Tolerance and grown after dehydration

High Relative Water Content High Harvest Index High Transpiration Leaf Pubescence Deep rooting

ABA, ROS scavenging Reduced Leaf Area High Sugar Content Deeper tap root early in the season Partial closure of stomata Reduced Growth Duration Low Flower Abortion Leaf Osmotic Adjustment


Gene Bank Acceccions Introgression Lines Near Isogenic Lines Recombinant Inbred Lines

Transgenics Intragenics Cisgenics

The combination of specific arrangements of genotypes and biotechnology traits that include Tolerance and Avoidance mechanisms might be more useful to improve the efficiency of the many mechanisms impacting quantitative traits.


ABA Dependent x ABA Independent

ABA H3C

CH3

Drought, Salinity and Cold

CH3

OH O

CH3

Plant Cell

COOH

Drought Cold

Signal Perception

ABA

ABA independent

Signal Transduction

Gene Expression

Salinity

Response to Stress and Tolerance


Water Waterchannel channel protein protein Transcription factors (DREB, AREB, etc.)

Detoxification enzymes

Regulatory Proteins Protection Protectionfactors factors of ofmacromolecules macromolecules (LEA protein)etc.) (LEA proteins

drought Drought

Key enzymes for osmolyte biosynthesis (proline, sugar, etc.)

Protein Proteinkinases kinases

Proteinases Chaperons

Functional Proteins


Drought, high salt and cold stresses

Cold stress

Signal perception

Signal perception

Transcription Factor

Gene Expression

Gene Expression Gene Expression

TRANSCRIPTION FACTOR Gene Expression

Stress Tolerance

cor6.6 cor15a kin1 erd10 More than 40 genes

rd17 rd29A

STRESS TOLERANCE


ABA Independent

ABA Independent

ABA Independent

ABA Dependent

Yamaguchi-Shinozaki & Shinozaki (2005) Trends Plant Sci.10:88-94.


From the Laboratory to the Field Important Crops

Model Plant

Legumes

Rice

Arabidopsis Tolerance in Model Plants

Corn

Wheat

Cane

Tolerance in Commercial Crops


Ito et al. (2006) Plant & Cell Physiology

Survival Rate

WT 0% (0/82)

ubi:: ubi:: ubi:: ubi:: ubi:: OsDREB1Ba DREB1Aa DREB1Ba DREB1Bb DREB1Ca 70% (7/10)

46% (16/35)

73% (43/59)

51% (29/57)

30% (15/30)


rd29A:DREB1A

WT

Pellegrineschi et al. (2004) genome

rd29A:DREB1A

WT


Water deficit 12 days

Greenhouse block casualization

WT

RD29A:DREB1A

Bhatnagar-Mathur et al. (2007) Plant Cell Rep. 26


Line P58 (BR16 with DREB gene) 5% GH Soil

BR16 without DREB gene 5% GH Soil



The MON 87460 is a GM Corn Plant overexpressing the Cold shock protein B (CspB) derived from the common soil bacterium Bacillus subtilis. The CspB protein has been shown to bind to a broad array of RNA, allowing them to adopt the correct conformation under stress conditions and improve cellular function in the plant.

Source: Monsanto, 2012


Source: Monsanto, 2012



- Two early maturity (RB855156, RB835486) -Two medium maturity (RB867515, RB855536) - Two late maturity varieties (RB928064, RB92579). - Line source irrigation system – water deficit gradient 0% to 100% of field capacity Experimental design: 120 x 50 m 3 reps with two double lines – 5 m Three seasons evaluated (plant cane and first and second ratoon).

- Culm production - Total recoverable sugar (TRS), - Biometric data (leaf area, root system distribution, leaf area index, number, diameter and length culms, number of emerging green and dried leaves, length and width of the +3 leaf) - Physiological data (photosynthesis rate, chlorophyll and proline content) - Biophysical data (water potential)

Susceptible variety

Tolerant variety


Biometric parameters that showed differences among the treatments: -diameter and length of culm; -number of green leaves; -length of +3 leaf; -leaf area index; -RB867515 showed the highest root system distribution under rescue irrigation; Parameters that showed difference between RB855536 and RB867515 were: -diameter and mean length of culms; -number of expanded green leaves; -length of +3 leaf; -leaf area index; -leaf water potential; -Photosynthesis rate.

Dawbacks: Field evaluation, high demand on manpower, time-consuming evaluations, destructive methods... This kind of “low throughput phenotyping� restricts the number of parameters that can be measured and, especially, the number of varieties that can be evaluated.


Chlorophyll fluorescence - Imaging PAM M-Series Maxi Version (Heinz Walz, GmbH, Effeltrich, Germany)

Near Infraed – Xenics Cheetah 640 (Xenics, Lexington, Massachusetts, USA)

Thermal image – FLIR E60 (FLIR Systems, Inc, Wilsonville, Oregon, USA)

GFP and DsRed fluorescence: Republic)

measurements: FluorCAM 800C (PSI Instruments, Tchec

- Our team are planning analyze few plants

RGB image – Canon PowerShot A640 (Canon, Inc, Tkyo, Japan)

(1º phase) and then to migrate for automated system (in house or commercial platform) (2º phase) to attend the demand of our Monocot platform for functional genomics and bioinformatics - Embrapa Agroenergy. - We are working mainly with Brachypodium distachyon and Setaria viridis (model plants) and sugarcane (target crop).


GM Hundreds of transgenic events are being generated using different maturity curves varieties in combination with different transcription factors (DREB2A and AREB) and cell wall modification (acyl transferases BAHD). Therefore, a high-throughput phenotyping system will be

required to assess and select the most promising events. Dias et al., 2012; Reis et al., 2012

C


Planned field tests (4 sites Pelotas – RS/Embrapa Temperate Agriculture; Planaltina – DF/Embrapa Cerrados; Maceió – AL/Embrapa Coastal Tablelands and Paranavaí – PR RIDESA/Federal University of Parana

Field Tests (GM Cane)



Thank you for your attention! Hugo Bruno Correa Molinari E-mail: hugo.molinari@embrapa.br


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