DOI: 10.5061/dryad.x95x69ptj
title: Ecophysiology and specialized metabolite trait data for the sunflower association mapping population

description: The use of hybrid breeding systems to increase crop yields has been the
 cornerstone of modern agriculture and is exemplified in the breeding and
 improvement of cultivated sunflower (Helianthus annuus). However, it is
 poorly understood what effect supporting separate breeding pools in such
 systems, combined with continued selection for yield, may have on leaf
 ecophysiology and specialized metabolite variation. We analyzed
 288 cultivated H. annuus lines to examine the genomic basis of several
 specialized metabolites and agronomically important traits across major
 heterotic groups. Heterotic group identity supports phenotypic
 divergences between fertility restoring and cytoplasmic male-sterility
 maintainer lines in leaf ecophysiology and specialized metabolism.
 However, the divergence is not associated with physical linkage to nuclear
 genes that support current hybrid breeding systems in cultivated H.
 annuus. Further, we identified four genomic regions associated with
 variation in leaf ecophysiology and specialized metabolism that
 co-localize with previously identified QTLs in cultivated H. annuus for
 quantitative self-compatibility traits and with SPH-proteins, a recently
 discovered family of proteins associated with self-incompatibility and
 self/nonself recognition in Papaver rhoeas (common poppy) with suggested
 conserved downstream mechanisms among eudicots. Self-compatibility is a
 derived trait in cultivated H. annuus with quantitative variation in
 selfing success, suggesting that trait linkage to divergent phenotypic
 traits may have partially arisen as a potential unintended consequence of
 historical breeding practices. Further work is necessary to confirm the
 self-incompatibility mechanisms in cultivated H. annuus and their
 relationship to the integrative and polygenic architecture of leaf
 ecophysiology and specialized metabolism in cultivated
 sunflower. 
description: An association mapping population of sunflower (Helianthus
 annuus) was grown in growth chambers in 3-4 replicates. For each replicate
 of every genotype, we identified the pair of most recently fully expanded
 leaves. For this leaf pair, one of the two leaves was used to assess
 ecophysiological traits: leaf fresh mass, dry mass, water content, leaf
 area, perimeter, aspect ratio, circularity, solidity, leaf mass per area
 (LMA), lamina thickness, lamina toughness, lamina density, and chlorophyll
 content on an area and mass basis. From the selected ecophysiology leaf,
 we first took chlorophyll content measurements in SPAD units and then
 clipped the leaf at the base of the petiole and weighed it for fresh mass.
 We scanned the leaf with a digital scanner to later derive leaf area,
 perimeter, aspect ratio, circularity, and solidity via ImageJ. Following
 scanning, we measured lamina thickness with digital calipers at the
 midpoint of the leaf's length, avoiding major veins. Lamina toughness
 was assessed using a digital penetrometer, averaging three measurements of
 force required to penetrate the leaf lamina with a millimeter-wide
 flat-tipped needle. Leaves were then dried at 60°C in a forced-air oven
 for 96 hours and weighed for dry mass. SPAD scores were converted into an
 area-basis (μmol m<sup>-2</sup>). Dry mass was used to
 calculate other traits, including water content, LMA, and mass-based
 chlorophyll content. In an unfortunate turn of events, dried leaves were
 accidentally destroyed for a subset of lines (N=125) while in storage
 awaiting processing, resulting in missing data for these lines for dry
 mass and the three traits derived using it. The missing data is listed as
 n/a in each respective cell. We took the opposing leaf
 to phenotype coarse defense traits and sample tissue for analytical
 chemistry analysis of secondary metabolism. We split this leaf down the
 midrib, and one half was rolled, placed into a microcentrifuge tube, and
 snap-frozen in liquid nitrogen. This leaf sample was stored at -80°C for
 later analysis. The other half of the leaf was dried at 60°C for at least
 36 h. This dried leaf material was used to assess four coarse leaf defense
 metrics: trichome density, ash content, total phenolics, and total
 flavonoids. Trichome density was calculated using a dissecting scope to
 count the trichomes present in a 0.25 cm<sup>2</sup> region.
 The dried leaf tissue was then ground into a fine, homogenous powder. This
 material was used to estimate total flavonoids via the aluminum
 complexation assay and estimate total phenolics via the Folin-Ciocalteu
 assay. To estimate total ash content, leaf powder was combusted in
 crucibles in a muffle furnace at 600°C for 12 hours, and the pre-and
 post-combustion mass was compared. To characterize
 broad metabolomic variation across cultivars, we used an untargeted
 approach. For each genotype, replicate frozen leaf samples were pooled in
 even proportion by mass, and these samples were ground to homogeneity
 under liquid nitrogen. A total of 10 mg of homogenized frozen material was
 extracted in 0.4 ml of 1:1 methanol:chloroform (v/v. in a sonicated
 ice-water bath for 30 min. Post-extraction, 0.2 ml of HPLC-grade water was
 added to each sample, and the mixture was vortexed and centrifuged. The
 aqueous layer was collected and further vortexed and centrifuged. The
 resulting aqueous layer extract was used for analysis by high-performance
 liquid chromatography (HPLC). three µl of extract from
 each sample was injected into an Agilent 1200 HPLC with a ultraviolet
 diode array detector (Agilent Technologies, Santa Clara, California, USA).
 Separation was achieved using an Agilent ZORBAX Rapid Resolution Eclipse
 XDB-C18 column (4.6 ⋅ 50 mm 1.8 μm), with mobile phase solvents of
 water:acetonitrile:formic acid = 97:3:0.1 (A) and 3:97:0.1 (B). The flow
 rate was set to 1 ml min<sup>-1</sup>, and the elution
 gradient was as follows: 3% B from 0-1 min, linear gradient to 17% B over
 2 min, isocratic at 17% B for 2 min, linear gradient to 60% B over 4 min,
 then to 98% B over 2 min. The ultraviolet diode array detector was set at
 260, 270, 280, 310, and 350 nm. We chose only the 350nm wavelength for
 analyses based on the high number of peaks detected via the diode array
 detector at this wavelength versus the others. We linearly calibrated
 retention time and peak area based on the averages of retention time (RT)
 and peak areas for two common peaks (RT 4.11 and 7.05) found among all
 samples. We further used manual binning of peaks based on retention time
 similarity, producing a list of metabolites present among at least 200 of
 288 lines. 
description: # Ecophysiology and specialized metabolite trait data for the sunflower
 association mapping population ## Description of the data and file
 structure The Dataset consists of line means for ecophysiology and
 specialized metabolite traits in the sunflower association mapping panel.
 The first sheet consists of descriptions for each column found in the
 secondary trait sheet. Any missing data is listed as n/a in each
 respective cell. Missing data occurred as. For any missing data, dried
 leaves were accidentally destroyed for a subset of lines (*N* = 125) while
 awaiting processing, resulting in missing data for these lines for dry
 mass and the three traits derived using it.