Photosynthesis in newly-developed leaves of heat-tolerant wheat acclimates to long-term nocturnal warming
Data files
Nov 06, 2023 version files 1.35 MB
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An400Data4ND_leaves.xlsx
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An400Data4PE_leaves.xlsx
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Data_for_A_Cc_models_ND_and_PE_Leaves.csv
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README.md
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TcritND_leaves.csv
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TcritPE_leaves.csv
Abstract
We examined photosynthetic capacity of newly-developed and pre-existing flag leaves of four wheat genotypes under three night temperatures (15, 20 and 25 °C) and common day temperature of 26 °C in two controlled environment experiments. In newly-developed leaves which acclimated (i.e. maintained or increased) the maximum rate of net CO2 assimilation (An) to long-term (9–13 weeks) nocturnal warming, acclimation was underpinned by greater capacity of Rubisco carboxylation (Vcmax) and photosynthetic electron transport (J). This indicates a night-dependent temperature sensitivity of the activation state of Rubisco. Metabolite profiling linked acclimation of An to greater accumulation of monosaccharides and saturated fatty acids in leaves, suggesting roles for osmotic adjustment of leaf turgor pressure and maintenance of cell membrane integrity. By contrast, warm night-induced inhibition of An was related to reductions in stomatal conductance of CO2 and J, despite higher basal electron transport thermal stability: Tcrit 51 of 45–46.5 °C in non-acclimated versus Tcrit of 43.8–45 °C in acclimated leaves. Pre-existing leaves exposed to short-term nocturnal warming (5–7 nights) showed no change in instantaneous temperature responses of An and photosynthetic capacity, except for an elite heat-tolerant genotype. These findings can be used to support strategies for developing climate-resilient wheat.
README
This README file was generated on 2023-11-02 by Onoriode Coast.
GENERAL INFORMATION
- Title of Dataset: Photosynthesis in newly-developed leaves of heat-tolerant wheat acclimates to long-term nocturnal warming
- Author Information
A. Principal Investigator Contact Information
Name: Onoriode Coast
Institution: University of New England Address: Armidale, NSW Australia Email: ocoast@une.edu.au <br> B. Co-investigator Contact Information Name: Andrew P. Scafaro Institution: Australian National University Address: Canberra, ACT Australia Email: andrew.scafaro@anu.edu.au <br> C. Co-investigator Contact Information Name: Helen Bramley Address: Hobart, TAS Australia Email: helbramley@gmail.com <br> D. Co-investigator Contact Information Name: Nicolas L. Taylor Institution: University of Western Australian Address: Crawley, WA Australia Email: nicolas.taylor@uwa.edu.au <br> E. Co-investigator Contact Information Name: Owen K. Atkin Institution: Australian National University Address: Canberra, ACT Australia Email: owen.atkin@anu.edu.au - Date of data collection (single date, range, approximate date): May 2019- March 2021
- Geographic location of experimentation: Canberra, ACT, Australia
- Information about funding sources that supported the collection of the data: A. ARC Centre of Excellence in Plant Energy Biology (CE140100008); <br> B. Australian Grains Research and Development Corporation (GRDC) Postdoctoral Fellowship on ‘Photosynthetic acclimation to high temperature in wheat’ (US1904-003RTX – 9177346), and project on ‘A national approach to improving heat tolerance in wheat through more efficient carbon allocation’ (US00080); and <br> C. Research England’s Expanding Excellence in England (E3)-funded Food and Nutrition Security Initiative of the Natural Resources Institute, University of Greenwich, UK.
SHARING/ACCESS INFORMATION
- Links to publications that cite or use the data: Coast, O., Scafaro, A. P., Bramley, H., Taylor, N. L., & Atkin, O. K. (2023). Photosynthesis in newly-developed leaves of heat-tolerant wheat acclimates to long-term nocturnal warming. Journal of Experimental Botany.
- Links to other publicly accessible locations of the data: None
- Links/relationships to ancillary data sets: None
- Was data derived from another source? No A. If yes, list source(s): NA
- Recommended citation for this dataset:
Coast, O., Scafaro, A. P., Bramley, H., Taylor, N. L., & Atkin, O. K. (2023). Data from: Photosynthesis in newly-developed leaves of heat-tolerant wheat acclimates to long-term nocturnal warming. Dryad Digital Repository. https://doi.org/10.5061/dryad.fqz612jx7
DATA & FILE OVERVIEW
- File List:
A) An400Data4ND_leaves.xlsx
B) An400Data4PE_leaves.xlsx
C) TcritND_leaves.csv
D) TcritPE_leaves.csv
E) Data_for_A_Cc_models_ND_andPE_leaves.csv
- Relationship between files, if important: None
- Additional related data collected that was not included in the current data package: Yes. A) Net assimilation at different CO2 concentration (A-Ci) measured during the early vegetative stage for all four cultivars (1704, 1898, 2254 and Mace) grown at three night temperatures (15, 20 and 25 degree C).
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DATA-SPECIFIC INFORMATION FOR: An400Data4ND_leaves.xlsx and An400Data4PE_leaves.xlsx
- Number of variables: 70
- Number of cases/rows: 256 for An400Data4ND_leaves.xlsx and 237 for An400Data4PE_leaves.xlsx
- Variable List: Most are defined below including all used for data analysis in the manuscript. <br> *Leaves: whether fully/newly-developed or pre-existing leaves <br> *Genotype: Genotypes used for this study. Mace (pedigree Wyalkatchem/Stylet/Wyalkatchem), a well-adapted, commercial, Australian cultivar; ACIAR09PBI C38-150C-DH9 (pedigree PBW343+L24+LR28/LANG; referred to as 1704), a heat susceptible genotype; ACIAR09PBI C27-0C-0N-3N (pedigree DBW16/ANNUELLO; referred to as 1898), also a heat-susceptible genotype; and 8:ZW11, (pedigree D67.2/P66.270//AE.SQUARROSA(320)/3/CUNNINGHAM/4/VORB; referred to as 2254), a heat tolerant elite genotype. <br> *curve: unique ID given to each group of net assimilation and CO2 response data used to produce the A-Ci curves. <br> *NightTemp: night time treatment temperature being one of 15, 20 or 25 degree C. <br> *Rep: Individual replicate plant <br> *Licor: Local name of LI6400XT machine used for gas exchange measurement. <br> *Day: Day or date of measurement. <br> *Unit ID: please ignore <br> *PID: Individual plant identification number <br> *LicorTemp: Set temperature of the LI6400XT chamber head during measurement of photosynthesis. <br> *Obs: The number of observations that have been stored since the log file was last opened. <br> *HHMMSS: Clock time string, 24 hour. Was not checked for correctness. <br> *FTime: Number of seconds since the file was opened <br> *EBal?: Energy balance flag <br> *Photo: Photosynthetic rate (μmol CO2 m-2 s-1) <br> *Cond: Conductance to H2O (mol H2O m-2 s-1) <br> *Ci: Intercellular CO2 concentration (µmol CO2 mol-1) <br> *Trmmol: Transpiration rate (mmol H2O m-2 s-1) <br> *VpdL: Vapour pressure deficit based on leaf temperature (kPa) <br> *CTleaf: Computed leaf temp (C). Same as Tleaf°C unless doing energy balance. <br> *Area: Leaf area (cm^2) <br> *BLC_1: One sided boundary layer conductance <br> *StmRat: Stomatal ratio <br> *BLCond: Total boundary layer conductance for the leaf (includes stomatal ratio) (mol m-2 s-1) <br> *Tair: Chamber air temperature (°C) <br> *Tleaf: Leaf temperature measured with the thermocouple (°C) <br> *TBlk: IRGA Block temperature (°C) <br> CO2R: Reference cell CO2 (μmol CO2 mol-1) <br> CO2S: Sample cell CO2 (μmol CO2 mol-1) <br> H2OR: Reference cell H2O (mmol H2O mol-1) <br> H2OS: Sample cell H2O (mmol H2O mol-1) <br> RH_R: Relative humdity in the reference cell (%) <br> RH_S: Relative humidity in the sample cell (%) <br> Flow: Flow rate to the sample cell (μmol s-1) <br> PARi: In-chamber quantum sensor (μmol m-2 s-1 ) <br> PARo: External quantum sensor (μmol m-2 s-1 ) <br> Press: Atmospheric pressure (kPa) <br> CsMch: Sample CO2 offset (μmol CO2 mol-1) <br> HsMch: Sample H2O offset (μmol H2O mol-1) <br> CrMchSD: Ref CO2 offset (μmol CO2 mol-1) <br> HrMchSD: Ref H2O offset (μmol H2O mol-1) <br> StableF: Stability status as a decimal value <br> BLCslope: Slope as function of area <br> BLCoffst: Offset as function of area <br> f_parin: Fraction of ParIn_μm to use for energy balance <br> f_parout: Fraction of ParOut_μm to use for energy balance <br> alphaK: Used in the conversion of (μmol mol-1 to W m-2) <br> Status: Stability status
- Missing data codes: NA (data not available)
- Specialized formats or other abbreviations used: None
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DATA-SPECIFIC INFORMATION FOR: TcritND_leaves.csv and TcritPE_leaves.csv
- Number of variables: 7 for TcritND_leaves.csv and 6 for TcritPE_leaves.csv
- Number of cases/rows: 96 for TcritND_leaves.csv and 25 for TcritPE_leaves.csv
- Variable List:
*Leaves: whether fully/newly-developed or pre-existing leaves
*Genotype: Genotypes used for detrmining Tcrit. Mace (pedigree Wyalkatchem/Stylet/Wyalkatchem), a well-adapted,
commercial, Australian cultivar; and ACIAR09PBI C38-150C-DH9 (pedigree PBW343+L24+LR28/LANG; referred to as 1704),
a heat susceptible genotype.
*NT: Night temperature (°C)
*PID: Individual plant identification number
*Rep: Plant replicate
*Tcrit: Estimates of critical temperature for PSII function (°C)
*A-Ci: 1 indicates same plant/leaf was used for determining photosynthetic capacity
by measuring net photosynthesis at different CO2 concentration to get A-Ci curves.
- Missing data codes: NA (data not available)
- Specialized formats or other abbreviations used: None
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DATA-SPECIFIC INFORMATION FOR: Data_for_A_Cc_models_ND_and_PE_Leaves.csv
- Number of variables: 41
- Number of cases/rows: 3227
- Variable List: All 41 variable lists are a subset of the 70 presented for An400Data4ND_leaves.xlsx and An400Data4PE_leaves.xlsx, and are as described previously.
- Missing data codes: NA (data not available)
- Specialized formats or other abbreviations used: None
Methods
Tcrit: leaf discs were excised during the day from the middle section of detached dark-adapted and were exposed to a temperature ramp at a constant rate of 1°C min−1 from 20 to 65 °C with simultaneous continuous measurement of F0 taken. Tcrit was calculated as the intersection point of two regression lines extrapolated from the flat and steep portion of the F0–temperature response curve.
Leaf gas exchange and An-Ci curves: Five LI-COR portable photosynthesis systems (LI-6400XT, LI-COR Inc., Lincoln, NE, USA) were used for gas exchange measurements. The LI-COR units were fitted with 6 cm2 leaf chambers with red-blue light source (6400-18 RGB Light Source, LI-COR). Leaves were exposed to saturating irradiance of 1500 μmol photons m−2 s−1 within the LI-COR leaf chamber, with both the LI-COR leaf chamber/block, and the whole plants were placed within the temperature-controlled cabinet. The LI-COR leaf chamber was initially set to 20°C, reference line atmospheric [CO2] of 400 ppm, a flow rate of 500 μmol s−1, and relative humidity maintained between 40 and 75%. photosynthetic [CO2] response curves (A:Ci curves) were generated, at constant irradiance of 1500 μmol photons m−2 s−1, by varying the [CO2] inside the LI-COR leaf chambers as follows: 30, 50, 100, 150, 250, 400, 400, 600, 800, 1000, 1200, 1400 and 400 μmol mol−1. The A:Ci curves were repeated with the leaves exposed to measurement temperatures of 25, 30, 35, 40 and 50 °C.
Modelling photosynthetic capacity: Model parameters for each growth and measurement temperature were estimated following the FvCB model and using the Plantecowrap package (Stinziano et al., 2018) in the R computing environment (R-Development-Core-Team, 2021).
The kinetic parameters used in modelling photosynthetic capacity for wheat were: mesophyll conductance at 25°C (gm = 5.5 mmol m−2 s−1 Pa-1); activation energy of mesophyll conductance (Ea = 47.65 kJ mol-1); apparent Michaelis-Menten constant for Rubisco carboxylation in 21% oxygen (Kair = 772 µmol mol-1); activation energy of Kc (93.72 kJ mol–1); photorespiratory CO2 compensation point or Gamma star at 25°C (Γ* = 37.74 µmol mol–1, equivalent to µbar bar–1); and Gamma star activation energy (24.42 kJ mol–1). The temperature response of Vcmax, J1500 and TPU were modelled using non-linear least squares fit of the Arrhenius temperature response function accounting for deactivation (Medlyn et al., 2002, Kattge and Knorr, 2007). The deactivation energy (Ed) was assumed to be 200 kJ mol–1, the activation energy (Ea) and entropy factor (DS) were estimated from iterative fits of the model.
Metabolites: Metabolite extraction was conducted using a gas chromatography coupled to mass spectrometry (GC-MS) procedure.
Usage notes
MS Excel and R/R Studio.