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\begin{document}

\title{The da1 mutation in wheat increases grain size under ambient and
elevated CO2 but not grain yield due to trade-off between grain size and
grain number}



\author[1]{Isabel Mora-Ramirez}%
\author[1]{Heiko Weichert}%
\author[1]{Nicolaus von Wiren}%
\author[2]{Claus Frohberg}%
\author[2]{Stefanie De-Bodt}%
\author[2]{Ralf-Christian Schmidt}%
\author[1]{Hans Weber}%
\affil[1]{Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung Gatersleben}%
\affil[2]{BASF Innovation Center Gent}%


\vspace{-1em}



  
  \date{June 14, 2024}


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\selectlanguage{english}
\begin{abstract}
Grain size is potentially yield-determining in wheat, controlled by the
ubiquitin pathway and negatively regulated by ubiquitin receptor DA1. We
analysed whether increased thousand grain weight in wheat da1 mutant is
translated into higher grain yield and whether additional carbon
provided by elevated (e)CO2 can be better used by the da1, displaying
higher grain sink strength and size. Yield-related, biomass, grain
quality traits and grain dimensions were analysed by two-factorial
analysis, regarding genotype and eCO2. da1 increased grain size but
reduced spikes and grains per plant, grains per spike and spikelets per
spike, independent of eCO2 treatment, leaving total grain yield
unchanged. eCO2 increased yield and grain number additively and
independently of da1, but did not overcome the trade-off between grain
size and number observed for da1. eCO2 but not da1 impaired grain
quality, strongly decreasing concentrations of several macro- and
micro-elements. In conclusion, intrinsic stimulation of grain sink
strength and grain size, achieved by da1, is not benefitting total yield
unless trade-offs between grain size and numbers can be overcome. The
results reveal interactions of yield components in da1-wheat under
ambient and eCO2, thereby uncovering limitations enhancing wheat yield
potential.%
\end{abstract}%



\sloppy




\textbf{Introduction}

Wheat (\emph{Triticum} spp.) accounts for 30\% of the global grain
production and of 45\% of the cereal nutrition, thus representing a
major food crop species (FAOSTAT, 2019). Despite significant breeding
progress, yield levels of wheat remain below the required amounts to
cope with the growing human population and with climate change
consequences (Ray, Mueller, West, \& Foley, 2013). Grain yield is the
result of different components that interact in a complex and
multiplicative manner (Schulthess et al., 2017; Sukumaran, Dreisigacker,
Lopes, Chavez, \& Reynolds, 2015) covering two main traits, related to
grain number and grain dimensions. Various agronomic traits have
contributed to grain yield improvement in the past such as plant height,
harvest index, total biomass, number of productive tillers, grain number
per spike, spike length, grain number per spike and per area and
thousand grain weight (TGW). From these, harvest index and grain number
per spike and per area are most important (Foulkes et al., 2011; Philipp
et al., 2018). Multiple interactions and compensatory mechanisms exist
among the different yield components, depending on genotype x
environment interactions (Slafer, Savin, \& Sadras, 2014).

Thousand grain weight is one component of yield and thus a potential
target for wheat yield improvement (Brinton \& Uauy, 2019; Foulkes et
al., 2011; Mohler et al., 2016; Tshikunde, Mashilo, Shimelis, \& Odindo,
2019). Genes involved in the ubiquitin pathway are central regulators of
grain size for a number of plants (reviewed by Li and Li, 2014).
Ubiquitin covalently binds to target proteins and triggers their
degradation in the 26S proteasome complex (Vierstra, 2003). Notably, the
ubiquitin proteasome pathway promotes irreversible proteolysis of a set
of regulatory proteins absolutely required for cell-cycle phase
transitions (Genschik et al., 2014).

DA1 encodes an ubiquitin receptor containing two ubiquitin-interacting
motifs (UIMs) and one zinc-binding LIM domain. DA1 binds
polyubiquitinated proteins mediating their degradation by the 26S
proteasome (Verma et al., 2004). Arabidopsis \emph{da1-1} was isolated
from a genetic screen by showing increased seed and organ size and by
producing larger and heavier seeds resulting from enlarged sporophytic
integuments (Li \emph{et al.,} 2008). Thus, the size of the maternal
outer layers can determine final grain size by setting a physical limit
on the available space for the growing filial seed organ
(Adamski\emph{et al.,} 2009; Hasan \emph{et al.,} 2011).

In spring wheat, the TaDA1 homeologs reveal high sequence similarities
to AtDA1, especially in the UIMs and LIM domains, implying similar
protein structures and functions and conserved interaction in the
ubiquitin-proteasome pathway in plants (Liu et al., 2020). While TaDA1-B
and TaDA1-D were predominantly expressed in the vegetative organs leaves
and roots, TaDA1-A was principally expressed in young spikes at prior to
anthesis. DA1-overexpressing plants contained fewer cells in the outer
pericarp. On the other hand, DA1-RNAi plants had more outer pericarp
cells, produced a wider pericarp cell layer and increased TGW by around
10\%. This confirmed that TaDA1 functions to restrict early maternal
cell proliferation (Liu et al., 2020). However, whether this increased
TGW can be translated into a higher wheat grain yield remained unclear.
Moreover, increases in grain weight have been frequently reported to
have little impact on wheat grain yield often due to the trade-off
between grain weight and grain number (Brinton et al., 2017; Philipp et
al., 2018; Song, Huang, Shi, Zhu, \& Lin, 2007; W. Wang et al., 2018).
However, in some cases grain yield improvement in wheat has been
significantly associated with increased TGW (Brinton \& Uauy, 2019;
Tshikunde et al., 2019).

Nevertheless, the positive effect of \emph{da1} on seed size\emph{,} as
shown in wheat and Arabidopsis plants, may provide approaches to improve
seed yield. In addition, higher grain size in wheat can positively
affect grain composition, flour extraction and/or quality (Nuttall et
al., 2017; Wiersma et al., 2001).

Higher grain size and therefore improved sink strength can be relevant
to the response to eCO\textsubscript{2}. This is especially important,
given the fact that due to anthropogenic activities, the atmospheric
CO\textsubscript{2} concentration is predicted to increase to 550 ppm by
2050 with profound consequences for crop growth (Lemonnier and
Ainsworth, 2018; Uddling et al., 2018). While
eCO\textsubscript{2}frequently improves carbon assimilation and
increases plant biomass in many species (Taub et al., 2008), sink
limitation often occurs, leading to photosynthetic feed-back inhibition
(White et al., 2016). Grain yield in wheat is predominantly sink-limited
during most of the grain filling period when grains grow under saturated
source supply (Borras, Slafer, \& Otegui, 2004; Sofield, Evans, Cook, \&
Wardlaw, 1977). Thus, a more efficient photosynthesis under
eCO\textsubscript{2} conditions could be possible at less-limiting sink
capacity and increasing the grain sink strength could be promising to
use additional CO\textsubscript{2} (Wang et al., 2013).

It is hypothesized that grain yield in the da\emph{1} mutant could
potentially benefit from additional source stimulation by
eCO\textsubscript{2} when compared to ambient conditions. Wheat
genotypes with increased grain size, as achieved in the
\emph{da1}mutant, exhibit higher sink capacity/strength at the level of
the individual grains. eCO\textsubscript{2} stimulates source activity,
which in many plants stimulates photosynthesis and induces faster growth
and biomass accumulation (Amthor, 2001; Jablonski, Wang, \& Curtis,
2002).

In this study, the \emph{da1} wheat mutant was characterised, which
provides a suitable model to better understand intrinsic yield
determinants in wheat. First, we asked whether the increased TGW in
\emph{da1} can be translated into higher wheat grain yield and what is
the relationship of grain size with other yield-related factors. Second,
we want to find out whether the additional carbon provided by
eCO\textsubscript{2} can be better used by the \emph{da1}mutant
displaying higher sink strength at the level off individual grains.
Using such an approach, simultaneously combines increases of both source
(eCO\textsubscript{2}) and sink strength (\emph{da1} ). To this end,
yield-related and biomass traits, grain dimensions and grain quality
traits were collected and analysed in a two-factorial analysis,
regarding genotype and eCO\textsubscript{2} treatment.

\textbf{Material and methods}

\textbf{Generation of the \emph{da1} mutant}

The \emph{da1} mutant derived from an ethyl methanesulfonate-mutant
population established in spring wheat (\emph{Triticum aestivum,}variety
Trappe) by KeyGene (www.keygene.com). The mutant population has been
screened for mutants in the \emph{DA1} gene. Positive lines have been
back-crossed (BC3) with Trappe to reduce background mutations. The
mutations in the different A, B and D genomes have been combined by
crossing.

The \emph{da1} wheat mutant, under analysis in this study, possesses
mutations in alleles of the wheat genomes A, B and D and in all three
cases the mutation affects the DA1-domain either by blocking its
transcription or by amino acid exchange (Fig. S1).

\textbf{Plant growth}

To simulate field-related conditions, plants were grown under
semi-controlled conditions in 4 small greenhouses (6.1 x 3.4 m) in soil
beds with regular irrigation and without supplemental light or
temperature regulation for the duration of the experiment (Saalbach et
al., 2014). The gables of the greenhouses consist of meshes to ensure
optimal ventilation. Outside temperature was recorded throughout the
experiment (Fig. S2). Grains of \emph{da1} and Trappe were sown on April
3rd, 2018 and harvested at full maturity at July 18th, 2018 on the IPK
campus, Saxony-Anhalt, Germany. A randomised block design was used with
six blocks (= replications) per greenhouse in two-fold repetition (2
greenhouses for both ambient and eCO\textsubscript{2}). Experimental
plots (0.5 x 1m) consisted of four rows (= 160 seeds, which resulted in
a density of 360 grains per m\textsuperscript{2}) Soil N content was
determined and adjusted with fertilisation to 180 kg N
ha\textsuperscript{-1} before the experiment with no further
fertilisation during the experiment. eCO\textsubscript{2} treatment was
started at the one-leaf stage in 2 greenhouses and continued until
physiological maturity, with daily exposition from 5.00 a.m. to 10.00
p.m. During that time, CO\textsubscript{2} was continuously supplied
from gas cylinders via a pipe system surrounding the interior of the
respective greenhouses. Levels within the greenhouses were recorded and
adjusted to 600 ppm using 2 CO\textsubscript{2} sensors per greenhouse.
The other 2 greenhouses served as an ambient control.

\textbf{Experimental design and data analysis}

A two-factorial experiment was performed. The factors were: (i) spring
wheat (\emph{Triticum aestivum} L. cv. Trappe) versus the
\emph{da1}mutant and (ii) ambient (approx. 380 ppm) versus
eCO\textsubscript{2}(600 ppm). In order to avoid border effects at the
front and the back of the plots, all samplings and measurements were
performed only for the interior of the 2 inner rows (30 plants of each
inner row = 60 plants per plot), resulting in a single measurement value
per plot (except for spikelets per spike). Mature spikes from 6 main
tillers per plot were harvested from both \emph{da1}and Trappe under
ambient and eCO\textsubscript{2} (6 spikes x 6 blocks x 2 greenhouses
ambient x 2 greenhouses eCO\textsubscript{2} x 2 genotypes (\emph{da1} ,
Trappe) = in total 288 spikes) and were harvested and investigated for
the total number of spikelets per spike. Harvest index was calculated
from each plot separately. The total dry weights of the 60 harvested
plants of the inner rows per plot were determined and divided by the
respective total grain weights

The experiment allowed to study the effect of each factor on response
variables related to plant dimensions, yield-related traits, biomass
traits, grain composition and spike-related traits. Interactions between
the two factors were calculated for all combinations but were not
significant. The data were analysed by two-way ANOVA using OriginPro 8.1
software (www.originlab.com/) and the statistical software program R
(www.r-project.org/).

To verify the results, the experiment with \emph{da1} and Trappe was
repeated in 2019 under the same management conditions with eight plots
of each genotype. However, the eCO\textsubscript{2} treatment was
omitted in the 2019 experiments.

\textbf{Analysis of grain morphology, sucrose, starch, carbon, nitrogen
and micro-elements}

Grain dimensions, thousand grain weight (TGW), grain width, length and
area were determined on mature dry grains using the digital seed
analyser MARVIN (www.marvitech.de). The traits harvest index, grain
yield per spike, grain yield per spikelet and grain number per spikelet
were calculated.

From each plot a sample of mature grains (app. 50 g) were ground by
ball-mill to a fine flour, which was used for subsequent analysis of
grain components, macro- and microelements. Starch and sucrose contents
were determined using a coupled enzyme assay as described (Weigelt et
al., 2009). Total carbon and nitrogen in dried wheat flour were
determined with the Vario EL Elemental analyser (www.elementar.de).

Milled flour from multiple mature grains (see above) were weighed into
PTFE digestion tubes and digested in HNO\textsubscript{3} under pressure
using a microwave digester (UltraCLAVE IV; MLS). Macro- and
microelements were measured by inductively coupled plasma optical
emission spectrometry (ICP-OES, iCAP 6500, Thermo Fisher Scientific,
Germany) combined with the CETAC ASXPRESS PLUS rapid sample
introduction system, and a CETAC autosampler (CETAC Technologies, Omaha,
NE, USA). Element standards were prepared from certified reference
materials from CPI international (Eroglu et al., 2017).

\textbf{Results}

\textbf{Sequences alignment and phylogenetic analysis}

DA1 from the genome B was selected to perform a blastp search of
orthologs on EnsemblPlants (https://plants.ensembl.org/index.html).
Those sequences with a percentage of identity higher than 60\% were
selected for the following analyses i.e. \emph{Zea mays}
Zm00001d035844\_T012, \emph{Hordeum vulgare} HORVU2Hr1G002700.14,
\emph{Sorghum bicolor}SORBI\_3010G064600:KXG19479, \emph{Triticum
dicoccoides}TRIDC2AG001610.3, \emph{Brachypodium
distachyon}BRADI\_4g42580v3:KQJ92266, \emph{Glycine max}
GLYMA\_17G247700:KRH05774,\emph{Triticum turgidum} TRITD2Av1G003900.3,
\emph{Oryza sativa Japonica group} Os06t0182500-02, Arabidopsis thaliana
AT1G19270.1, Aegilops tauschii AET0Gv20035900.10, \emph{Triticum
urartu}TRIUR3\_12237:TRIUR3\_12237-T1, \emph{Medicago
truncatula}MTR\_5g018900:AES94835, \emph{Manihot
esculenta}MANES\_10G022200:OAY38533, \emph{Cucumis sativus}
Csa\_2G286500:KGN62017 and \emph{Beta vulgaris}
BVRB\_6g138060:KMT08523). Amino acid alignment was performed with
CLUSTALW followed by the construction of an unrooted phylogenetic tree
using MEGA-X v10.1.5 with the ML (Maximum Likelihood) and NNI
(Nearest-Neighbour-Interchange) JTT model on a 2000 bootstrap method
(Kumar, Stecher, Li, Knyaz, \& Tamura, 2018).

The ClustalO alignment indicated that the sequences TraesCSU02G00780.1,
TraesCS2B02G007700.1 and TraesCS2D02G0169.1 correspond to DA1 genes of
the genome A, B and D respectively and share 99\% identity (Fig. 1). The
DA1 gene in wheat encodes 504 amino acids and harbours a DA1-typical
domain, ubiquitin interacting motif domain (UIM) and LIM-type zinc
finger domain (Znf\_LIM), (Fig. S3). Wheat DA1 has high identity to the
homeologs of barley (98\%), rice (88\%), maize (86\%), millet (86\%),
and Arabidopsis (60\%), which suggests similar functions across plant
species.

\textbf{Plant performance and grain dimensions}

After sowing the germination rate was determined as 99\% to 100\% with
no apparent genotype and treatment effects. Days to anthesis (app. at 61
d after sowing) and length of flowering (app. 3.5 d) were found to be
not dependent on either genotype or treatment.

The analysis of grain dimensions of mature grains revealed that thousand
grain weight (TGW) for \emph{da1} was increased by 8\% (\emph{P = 2E-5}
). eCO\textsubscript{2} further enlarged TGW for \emph{da1} and Trappe,
each by another approx. 8\% (\emph{P = 3E-6,} Fig. 2). The increased TGW
by both genotype and treatment was reflected by parallel and highly
significant increases of grain length, width and area (Fig. 2). Thus,
the\emph{da1} mutant exhibited increased TGW compared to Trappe, and
eCO\textsubscript{2} further increased TGW in a similar manner in both
genotypes.

\textbf{Yield-related traits}

Grain yield calculated as tons ha\textsuperscript{-1} was not different
between \emph{da1} and Trappe but was significantly increased by 28\%
and 22\% upon eCO\textsubscript{2}treatment for \emph{da1} and Trappe,
respectively (Fig. 3). Spike number per plant was unchanged by
eCO\textsubscript{2} treatment but the genotype effect revealed 6\% more
spikes per plant for Trappe compared to \emph{da1} .

While grain number per plant was significantly enhanced under
eCO\textsubscript{2} by 19\% and 13\% for Trappe and
\emph{da1}respectively, there was a negative effect of the genotype
resulting in 10\% and 15\% lower grain number per plant for \emph{da1}
under ambient and eCO\textsubscript{2}conditions compared to Trappe,
respectively. Similarly, the trait grain number per spike increased upon
eCO\textsubscript{2} in both Trappe and \emph{da1} by 9\% and 8\%,
respectively, whereas the genotype effect decreased grains per spike
in\emph{da1} by app. 6\% under ambient and
eCO\textsubscript{2}conditions. Taken together, the\emph{da1} mutant
displayed reduced spikes per plant, grains per plant and grains per
spike, independent of the treatment, which could outcompete the higher
TGW (Fig. 2), resulting in no gain of grain yield per area of
\emph{da1}compared to Trappe. The results also indicated a higher
response of Trappe to eCO\textsubscript{2} conditions compared to
Trappe, for the traits spikes per plant, grain number per plant and
grains per spike.

\textbf{Biomass traits}

eCO\textsubscript{2} in many plants stimulates source activity,
photosynthesis and induces faster growth and biomass accumulation
(Jablonski et al., 2002). On the other hand, DA1 is supposed to be a
regulator of cell proliferation in maternal seed organs (Liu et al.,
2020). Therefore, possible effects of eCO\textsubscript{2} treatment and
genotype on biomass traits were analysed (Fig. 4). Tiller number at the
beginning of the stem elongation stage was not different between the
genotypes but increased similarly by 7\% and 9\% upon
eCO\textsubscript{2} for Trappe and \emph{da1} , respectively. Whereas
plant height at anthesis was not different between genotypes at either
treatments (data not shown), eCO\textsubscript{2}increased plant height
at 10 days after anthesis by 6\% and 7\% for Trappe and \emph{da1} ,
respectively, compared to ambient CO\textsubscript{2}. Plant biomass was
independent of the genotype but increased upon eCO\textsubscript{2} by
22\% and 17\% for Trappe and\emph{da1} , respectively. Harvest index
(HI) did not changed by genotype but was slightly higher upon
eCO\textsubscript{2} treatment by 4\% for both \emph{da1} and Trappe.

Taken together, the results revealed no differences in the biomass
traits analysed between \emph{da1} and Trappe. As expected,
eCO\textsubscript{2} treatment leads to an increase in these traits,
with no apparent differences in the response between \emph{da1} and
Trappe.

\textbf{Spike-related traits}

The results described above indicated specific changes at the level of
grain number and grain size. We therefore analysed spike related traits.
The genotype and treatment effects are shown in Fig. 5. Grain yield per
spike did not differ between \emph{da1} and Trappe for both ambient and
eCO\textsubscript{2} conditions, lacking a genotype effect. However,
levels increased significantly upon eCO\textsubscript{2} treatment by 18
and 16\% for \emph{da1} and Trappe, respectively, showing a clear
treatment effect. Spikelets per spike did not show significant treatment
effects upon eCO\textsubscript{2}, but with a trend to lower levels due
to eCO\textsubscript{2} (not significant at \emph{P \textless{} 0.05} ).
However, the genotype effect led to approx. 3\% less spikelets per spike
in \emph{da1} compared to Trappe.

Grain yield per spikelet was not changed between \emph{da1} and Trappe
for both ambient and eCO\textsubscript{2} conditions, lacking a genotype
effect. Grain number per spikelet behaved similar, lacking a genotype
effect. However, both, grain yield per spikelet and grain number per
spikelet increased upon eCO\textsubscript{2} by 15\% and 8\%,
respectively.

Taken together, the results indicated reduced numbers of spikelets per
spike in \emph{da1,} which is probably balanced by a higher TGW (Fig. 2)
resulting in no gain of grain yield per area of \emph{da1} compared to
Trappe.

\textbf{Grain composition}

While eCO\textsubscript{2} can increase grain yield of wheat there is
often a shift in grain components and functional properties (Fangmeier,
Gr\selectlanguage{ngerman}üters, Högy, Vermehren, \& Jäger, 1997; P. Högy et al., 2009).
Likewise, differences in grain size can change the relationship between
seed organs affecting grain composition and quality (Nuttall et al.,
2017). Therefore, possible effects of treatment and genotype on the
composition of mature grains were analysed.

Grain starch content was increased by approx. 2\% in \emph{da1} grains
compared to Trappe under ambient conditions and by 3\% in response to
eCO\textsubscript{2}. Sucrose content in mature grains was 9\% lower
for\emph{da1} compared to Trappe under ambient conditions and 6\% under
eCO\textsubscript{2}. The results showed that both \emph{da1} effects
and eCO\textsubscript{2} only slightly affected starch and sucrose
levels. Both factors resulted in a small increase of the starch to
sucrose ratio. Grain total carbon content of mature grains was unchanged
between \emph{da1} and Trappe but was slightly lower upon
eCO\textsubscript{2} treatment, however with only 0.5\%. Grain total
nitrogen content was not different between \emph{da1} and Trappe but
decreased significantly upon eCO\textsubscript{2} treatment by as much
as 15\% in both \emph{da1} and Trappe (Fig. 6).

The concentrations of major macro- and microelements were measured by
ICP-OES (Table 1). The analysis of flour from mature grains revealed
that \emph{da1} did not differ considerably from Trappe with respect to
important grain nutrient and micro-element concentrations including Fe,
Zn, S, Mn, Mg, K, Ca, Na and N. Significant genotype-dependent
differences were found only for Na with 8\% lower values in \emph{da1} .
In contrast, eCO\textsubscript{2} treatment strongly decreased the
concentrations of several of the essential elements, including Fe, Zn,
S, Mn and N by 7, 12, 12, 10 and 15\%, respectively, whereas levels of
Mn, K, Ca and Na were unchanged.

\textbf{Validation on ambient conditions}

In order to confirm the results from the 2018 experiment, the field
trial was repeated in the following year 2019 with \emph{da1} and
Trappe, while the eCO\textsubscript{2} treatment was omitted. Fig. 7
shows the data as a comparison between \emph{da1} and Trappe and between
the two years. According to the first-year's results, \emph{da1} again
exhibited significantly increased TGW, grain length, width and area.
Similar to the 2018 experiment, grain yield and spike number per plant
were not different between \emph{da1} and Trappe. Thus, the trial in
2019 confirmed the differences between \emph{da1} and Trappe. Grain
morphology traits such as TGW, grain length, area and width behaved
similarly as in the 2018 trial, thus confirming the increased grain size
phenotype of \emph{da1} mutants. Likewise, yield parameter results were
consistent between both experiments, grain yield per spike was not
different between both lines. The \emph{da1} mutant exhibited increased
grain size but decreased grain number per plant and spike.

\textbf{Discussion}

Grain size in wheat is a potential target to improve yield potential.
The ubiquitin pathway affects organ growth and seed size, which is
negatively regulated by the ubiquitin receptor DA1 restricting early
maternal cell proliferation in Arabidopsis and crop plants such as
canola, maize and wheat (N. Li \& Li, 2014; Liu et al., 2020; J. L. Wang
et al., 2017; Xie, Li, Ran, Wang, \& Zhang, 2018). The \emph{da1} wheat
mutant increases grain size and provides a suitable model to better
understand intrinsic yield determinants in wheat. The aim was to study
whether the increased TGW in\emph{da1} can be translated into higher
grain yield and what is the relationship between the different
yield-related traits. In order to alleviate possible source limitation,
it was also tested whether the additional carbon provided by high
CO\textsubscript{2}, expected in the future, can be better used by the
\emph{da1} mutant displaying higher sink strength at the level off
individual grains. The results show that increased grain size in
\emph{da1} wheat is interacting with other yield-related components at
both eCO\textsubscript{2} and ambient conditions, leaving the final
grain yield unchanged.

\textbf{The \emph{da1} mutation and elevated CO\textsubscript{2}
independently increase grain size}

The \emph{da1} wheat mutant exhibited 8\% increased TGW compared to
Trappe (Fig. 2). This increase is related to both grain length and width
and indicated higher sink strength of individual grains. Accordingly,
the Arabidopsis \emph{da1-1} mutant produces larger and heavier seeds
resulting from enlarged sporophytic integuments (Y. Li, Zheng, Corke,
Smith, \& Bevan, 2008). In wheat, grain size is associated with carpel
size (Calderini, Abeledo, Savin, \& Slafer, 1999) and with variations in
the ovary wall size, which is related to cell number rather than cell
size (Reale, Cerri, Ayano, \& Benincasa, 2017). Furthermore, grain
length and pericarp cell length are associated (Muñoz \& Calderini,
2015; Pielot et al., 2015). TaDA1 has been described as a negative
regulator of grain size. DA1-RNAi plants resembles the wheat
\emph{da1}mutant and produced more outer pericarp cells at 15 DAP,
formed a wider pericarp cell layer and displayed increased grain size by
around 10\% (Liu et al., 2020). It was also shown that TaDA1-A is
predominantly expressed in young spikes at pre-anthesis (Liu et al.,
2020). Cell division in the cereal pericarp is terminated as early as
two days after fertilization (Radchuk, Weier, Radchuk, Weschke, \&
Weber, 2011). Thus, it is hypothesised that the impact of \emph{da1} on
grain size most probably comes from a prolonged cell division phase in
the early maternal grain tissue, probably before anthesis. Hence, the
increased maternal grain layers may overcome physical barriers to
endosperm expansion, thereby increasing the available space for
endosperm growth, which finally leads to increased grain size (Hasan,
Herrera, Lizana, \& Calderini, 2011).

Our results reveal that eCO\textsubscript{2} further increased TGW in a
similar manner for both genotypes by app. 8\%, independently from
the\emph{da1} -effects (Fig. 2). In plants, eCO\textsubscript{2} has
been shown to enhance cell division, to shorten the duration of the cell
cycle, and to promote cell production as well as expansion (Gamage et
al., 2018). Thus, eCO\textsubscript{2} could possibly further stimulate
the cell proliferation in the developing grains. This is probably due to
the eCO\textsubscript{2}-mediated carbon ``fertilisation effect'', which
mediates an assimilate and/or sugar supply effect stimulating cell
proliferation within the developing grain (Lastdrager, Hanson, \&
Smeekens, 2014; H. Weichert et al., 2017).

\textbf{Improvement of grain size in \emph{da1} is compensated by lower
grain number}

The finding that biomass traits such as tiller number, plant height at
10 days after anthesis, harvest index and spike number per plant were
not changed in \emph{da1} indicates that the mutation does not change
vegetative parameters but preferentially affects grain development
around anthesis. While grain size was increased in \emph{da1} compared
to Trappe (+ 8\%, Fig. 2), some of the other important yield components
were decreased (Fig. 3) such as spikes per plant (- 6\%), grains per
plant (- 12\%) and grains per spike (- 6\%). However, total grain yield
was not altered (Fig. 3). These results reveal that the improvement of
grain size is counter-balanced in a way that final grain yield is not
altered. Thereby, the larger grain size was compensated by several other
traits related to grain number per spike such as less spikes per plant,
lower grain number per spike, lower number of spikelets per spike and,
eventually less grains per spikelets, even the latter was not
significant here (Fig. 5). Altogether, this results in a lower number of
grains per plant and per area in \emph{da1}compared to Trappe. The
comparison between \emph{da1} and Trappe confirms the well-known
trade-off between grain size and grain number, which finally maintains
grain yield stability (Sadras, 2007).

\textbf{The \emph{da1} mutation and elevated CO\textsubscript{2}
additively increase grain size but not grain yield}

Both \emph{da1} and eCO\textsubscript{2} independently stimulate sink
activity, which leads to a larger grain size. However, it can be
hypothesised that \emph{da1} acts only on early grain development by
sustaining cell proliferation without directly affecting source strength
or assimilate availability. This may cause competition for assimilates
between individual grains within the spike, which opens up in a
compensation of the larger grain size by less grains per plant and per
spike. In contrast, eCO\textsubscript{2} operates at the whole plant
level including grain development by a metabolite/assimilate effect,
which becomes evident by a stimulation of different biomass traits (Fig.
4) such as higher grain number per plant (+ 7\%), grain yield (+ 14\%,
Fig. 3) and grain number per spikelet (+ 8\%, Fig. 6). Additional supply
of eCO\textsubscript{2} produced a significant increase of grain size in
Trappe and \emph{da1} each by 8\% (Fig. 2), indicating that TGW in both
genotypes can benefit in a similar manner from eCO\textsubscript{2}.
Thus, the CO\textsubscript{2} treatment and the \emph{da1} mutation
increased grain size additively leading to an increase in TGW of 17\% in
the \emph{da1} x eCO\textsubscript{2} combination compared to Trappe at
ambient CO\textsubscript{2}. However, the reduction of grain number is
still maintained in the \emph{da1} x eCO\textsubscript{2} combination
compared to Trappe x eCO\textsubscript{2}. In consequence, total grain
yields of \emph{da1} or Trappe at eCO\textsubscript{2} remained
unchanged. In summary, even though eCO\textsubscript{2} increases yield
and grain number in general, it cannot overcome the negative effect of
the \emph{da1} genotype, which goes back to a trade-off between grain
size and grain number. Thus, total yield in the genetic background of a
\emph{da1} mutation cannot profit from source stimulation by higher
CO\textsubscript{2}, expected in the future due to climate change, as
final yield gain remained unchanged between\emph{da1} and Trappe in
eCO\textsubscript{2}.

\textbf{Grain quality is not altered by \emph{da1} but impaired by
elevated CO\textsubscript{2}}

Grain starch and sucrose contents were only slightly altered by
both\emph{da1} mutation and eCO\textsubscript{2}, leading to a small
increase of the starch to sucrose ratio in \emph{da1} (Fig. 6).
Moreover, the concentration of essential macro- and microelements
in\emph{da1} grains were not changed with respect to Trappe (Table 1).
In contrast, eCO\textsubscript{2}treatment strongly decreased several of
the macro- and micro-elements similarly in \emph{da1} and Trappe, such
as Fe, Zn, S and Mn by 7, 12, 12 and 10\%, respectively. However, other
elements remain constant such as Mg, K, Ca and Na. C3 plants such as
wheat generally respond to eCO\textsubscript{2} with increased
photosynthesis, reduced stomatal conductance and a significant reduction
in the amount of essential elements in grains (Amthor, 2001; Petra Högy
\& Fangmeier, 2008; Pleijel \& Högy, 2015). It has been suggested that
reduced transpiration\selectlanguage{english}-driven mass flow of nutrients under
eCO\textsubscript{2} contributes to decreases in seed concentrations of
several elements (Houshmandfar et al., 2018). Especially the grain N
concentration decreased upon eCO\textsubscript{2} by 15\% (Table 1).
CO\textsubscript{2} enrichment causes lower N and protein levels in
non-leguminous C3 species and alters acquisition, remobilisation,
redistribution, and accumulation of N (Taub \& Wang, 2008).
eCO\textsubscript{2} physiologically induces N deficiency, reducing both
nitrate uptake from soil and nitrate reduction while ammonium uptake is
favoured (Bloom, Burger, Kimball, \& Pinter Jr, 2014).

\textbf{Enhancing grain size via\emph{da1} is not a suitable way to
increase yield potential in wheat}

The negative relationship between grain size and grain number is an
intrinsic property of many crop and non-crop plants (Acreche \& Slafer,
2006; Quintero, Molero, Reynolds, \& Calderini, 2018). From an
evolutionary point, the adjustment between these two traits is important
and guarantees yield stability (Sadras, 2007). This trade-off is
probably not easy to overcome by conventional breeding and results from
the complex interaction of source limitation such as shortage of
assimilate supply to grains, sink limitation such as inability of each
grain to unload and/or accumulate assimilates, and translocation
limitation such as inefficient delivery of assimilates from leaves to
grains (Seki et al., 2015).

The breeding process in the past essentially increased grain number per
area by enhancing grains per spike and spikelets, however without much
gain in TGW (Philipp et al., 2018). An increase of grain number per
spike strongly depends on assimilates allocated to the spike (Ghiglione
et al., 2008). Competition for assimilates occurs within the spike and
is controlled by assimilate loading and unloading within the vascular
system and the short-distance transport within the spike, rachis and
spikelets. Possible limitations in transport capacities and competition
for assimilates between spikelets and/or florets could impact on biomass
distribution among individual tissues within the spike (Reynolds et al.,
2009). A potential issue could be to target resistance to assimilate
movement imposed by the vascular system of the spike. Resistance to
assimilate movement within the spike, and particularly that within the
spikelets, may be an important component of spike 'sink activity' and a
possible limitation to yield (Bremner \& Rawson, 1978). Disparity in
number and dimensions of vascular bundles in different spike segments
could be critical affecting ultimate size and grain number along the
rachis (Asli \& Houshmandfar, 2011). In rice, simultaneous increases in
sink size and translocation capacity through the vascular bundles
increased the number of vascular bundles and contributed to increased
grain yield (Fujita et al., 2013; Terao, Nagata, Morino, \& Hirose,
2010).

Eventually, genetic yield gain during breeding has not been accompanied
by similar increases in the vasculature size of the wheat spike.
Accordingly, no clear association was found between the genetic
improvement and magnitude of vascular systems in peduncles of the wheat
spike (Lopez-Garrido, Molina-Quiros, De la Puerta-Lopez, Vidal-Bernabe,
\& Garcia-Del-Moral, 2001). Hence, the spike architecture in terms of
the relative distribution of grain yield and number along the spike is
surprisingly stable and has not been improved by breeding in the past
(Philipp et al., 2018).

The results in this study give valuable insights into the interactions
among yield components related to grain size and grain number and the
possible limitations of yield potential in wheat. Apparently, the
intrinsic stimulation of sink strength and/or growth by increasing cell
proliferation, as achieved in \emph{da1} grains, is not expedient
towards benefiting total yield, unless the trade-off between grain size
and grain number can be overcome. While eCO\textsubscript{2} increased
yield and grain number additively and independently of \emph{da1} , it
did not prevail the trade-off between grain size and number in\emph{da1}
. The attempt to increase grain sink strength by ectopic expression of a
sucrose transporter in the wheat endosperm increased individual grain
weight but also decreased grain number per spike, thereby confirming the
predominant trade-off between grain size and number (Saalbach et al.,
2014; N. Weichert et al., 2010). This firm relationship supports the
conclusion that the improvement of grain yield is best achieved through
an integrated approach targeting several yield-component traits in
parallel (Wurschum, Leiser, Langer, Tucker, \& Longin, 2018).

\textbf{Supplementary data}

\textbf{Fig. S1,} Overview on the location of the mutations in
the\emph{da1} -wheat.

\textbf{Fig. S2,} Mean day temperature as recorded by the IPK
Gatersleben whether station 2018. \textbf{Fig. S3,} Schematic
representation of the DA1 wheat sequence and its domains.

\textbf{Conflict of interest statement:} The authors declare that they
have no conflict of interest.

\textbf{Acknowledgement:} We are grateful to Katrin Blaschek, Elsa
Fessel, Angela Schwarz, and Uta Stemmler for excellent technical
assistance, and we thank Dr. Yudelsy Antonia Tandron Moya, Dept.
Physiology \& Cell Biology, IPK, for element analysis.

\textbf{Author contribution:} I.M.-R., H.Wei. and H.W., investigation,
formal analysis, funding acquisition, writing -- review \& editing;
H.W., data curation, project administration, writing-original draft;
N.v.W., investigation, writing -- review \& editing; BASF colleagues,
funding acquisition, resources, conceptualisation, data curation writing
-- review \& editing.

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F. H. (2018). Phenotypic and genetic analysis of spike and kernel
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\textbf{Figure Legends}

\textbf{Fig. 1, Phylogenetic tree of selected DA1 proteins.}

Wheat DA1 sequences are shaded. \emph{Zea mays}
Zm00001d035844\_T012,\emph{Hordeum vulgare} HORVU2Hr1G002700.14,
\emph{Sorgum bicolor}SORBI\_3010G064600:KXG19479, \emph{Triticum
dicoccoides}TRIDC2AG001610.3, \emph{Brachypodium
distachyon}BRADI\_4g42580v3:KQJ92266, \emph{Glycine max}
GLYMA\_17G247700:KRH05774,\emph{Triticum turgidum} TRITD2Av1G003900.3,
\emph{Oryza sativa}Japonica group Os06t0182500-02, \emph{Arabidopsis
thaliana} AT1G19270.1,\emph{Aegilops tauschii} AET0Gv20035900.10,
\emph{Triticum urartu}TRIUR3\_12237:TRIUR3\_12237-T1, \emph{Medicago
truncatula}MTR\_5g018900:AES94835, \emph{Manihot
esculenta}MANES\_10G022200:OAY38533, \emph{Cucumis sativus}
Csa\_2G286500:KGN62017 and \emph{Beta vulgaris} BVRB\_6g138060:KMT08523.

\textbf{Fig, 2, Grain Dimensions}

Box plots show the distribution of 4 grain dimension-related traits,
measured for \emph{da1} wheat and wildtype Trappe. P-values indicate
statistical significance between values. Two factors, genotype and
treatment influencing grain dimension traits.

\textbf{Fig. 3, Yield-related traits.}

Box plots show the distribution of 4 yield-related traits, measured
for\emph{da1} wheat and wildtype Trappe. P-values indicate statistical
significance between values. Two factors, genotype and treatment
influencing yield-related traits.

\textbf{Fig. 4, Biomass traits.}

Box plots show the distribution of 4 biomass-related traits, measured
for \emph{da1} wheat and wildtype Trappe. P-values indicate statistical
significance between values. Two factors, genotype and treatment
influencing biomass-related traits.

\textbf{Fig. 5, Spike-related traits.}

Box plot show the distribution of 4 spike-related traits, measured
for\emph{da1} wheat and wildtype Trappe. P-values indicate statistical
significance between values. Two factors, genotype and treatment
influencing grain composition-related traits.

\textbf{Fig. 6, Grain composition.}

Box plots show the distribution of 4 grain composition-related traits,
measured for \emph{da1} wheat and wildtype Trappe. P-values indicate
statistical significance between values. Two factors, genotype and
treatment influencing grain composition-related traits.

\textbf{Fig. 7, Repetition experiment.}

Box plots show the distribution of grain dimension-, yield-, biomass-,
and grain composition-related traits, measured for da1 wheat and
wildtype Trappe. P-values indicate statistical significance between
values. Percentages gives the change of values for da1 compared to
Trappe. Table insert shows a comparison between experiments from 2018
and 2019 in percentage, (Trappe = 100 \%), green and red colour
designate significant higher and lower values of da1 compared to Trappe.
n = 8; bold, significant differences; *, P\textless{}0.05;
**P\textless{}0.01; ***, P\textless{}0.001.

\textbf{Table 1, Grain macro- and micro elements.}

Factors genotype and eCO\textsubscript{2} treatment influencing the
concentration of nutrient elements in mature grains of \emph{da1} and
Trappe.\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllllllllllllll@{}}
\toprule
& \textbf{ambient CO\textsubscript{2}} & \textbf{ambient
CO\textsubscript{2}} & \textbf{ambient CO\textsubscript{2}} &
\textbf{ambient CO\textsubscript{2}} & \textbf{ambient
CO\textsubscript{2}} & \textbf{eCO\textsubscript{2}} &
\textbf{eCO\textsubscript{2}} & \textbf{eCO\textsubscript{2}} &
\textbf{eCO\textsubscript{2}} & \textbf{eCO\textsubscript{2}} &
\textbf{Genotype} & \textbf{Genotype} & \textbf{Genotype} &
\textbf{Genotype} & \textbf{Genotype} & \textbf{eCO\textsubscript{2}
treatment} & \textbf{eCO\textsubscript{2} treatment} &
\textbf{eCO\textsubscript{2} treatment} & \textbf{eCO\textsubscript{2}
treatment} &\tabularnewline
& \textbf{Trappe} & \textbf{Trappe} & da1 & da1 & & \textbf{Trappe} &
\textbf{Trappe} & da1 & da1 & & \textbf{Trappe} & \textbf{Trappe} & da1
& da1 & \emph{} & \textbf{ambient CO\textsubscript{2}} & \textbf{ambient
CO\textsubscript{2}} & \textbf{eCO\textsubscript{2}} &
\textbf{eCO\textsubscript{2}} &\tabularnewline
\selectlanguage{greek}\textbf{µg g-1}\selectlanguage{english} & \textbf{MW} & \textbf{SD} & \textbf{MW} & \textbf{SD}
& P & \textbf{MW} & \textbf{SD} & \textbf{MW} & \textbf{SD} & P &
\textbf{MW} & \textbf{SD} & \textbf{MW} & \textbf{SD} & P & \textbf{MW}
& \textbf{SD} & \textbf{MW} & \textbf{SD} & P\tabularnewline
& & & & & \emph{} & & & & & \emph{} & & & & & \emph{} & & & &
&\tabularnewline
\textbf{Fe} & 43.57 & 3.33 & 43.51 & 4.45 & \emph{0.970} & 38.81 & 3.61
& 39.70 & 4.22 & \emph{0.590} & 41.19 & 4.18 & 41.69 & 4.68 &
\emph{0.700} & 42.15 & 2.48 & 39.09 & 3.64 & 0.013\tabularnewline
\textbf{Zn} & 41.63 & 2.98 & 42.04 & 5.23 & \emph{0.820} & 35.51 & 3.32
& 36.73 & 4.53 & \emph{0.460} & 38.57 & 4.39 & 39.39 & 5.50 &
\emph{0.570} & 41.24 & 3.77 & 36.12 & 3.93 & 0.001\tabularnewline
\textbf{S} & 1849.34 & 84.90 & 1843.99 & 108.94 & \emph{0.089} & 1613.93
& 125.97 & 1611.98 & 135.33 & \emph{0.970} & 1731.64 & 159.66 & 1727.99
& 168.75 & \emph{0.930} & 1824.37 & 79.84 & 1612.96 & 127.86 &
0.000\tabularnewline
\textbf{Mn} & 43.40 & 5.19 & 42.98 & 4.20 & \emph{0.830} & 37.18 & 3.70
& 37.54 & 3.50 & \emph{0.810} & 40.29 & 5.43 & 40.26 & 4.69 &
\emph{0.980} & 41.50 & 3.93 & 37.36 & 3.52 & 0.003\tabularnewline
\textbf{Mg} & 1461.40 & 115.42 & 1481.99 & 139.07 & \emph{0.670} &
1334.60 & 106.99 & 1402.97 & 121.90 & \emph{0.670} & 1398.00 & 126.65 &
1442.48 & 134.11 & \emph{0.240} & 1423.46 & 100.45 & 1368.79 & 117.48 &
\emph{0.180}\tabularnewline
\textbf{K} & 6546.57 & 397.98 & 6472.35 & 564.25 & \emph{0.710} &
6566.76 & 400.75 & 6564.18 & 562.71 & \emph{0.980} & 6556.66 & 390.73 &
6518.27 & 553.09 & \emph{0.780} & 6497.41 & 410.34 & 6565.47 & 477.75 &
\emph{0.680}\tabularnewline
\textbf{Ca} & 618.97 & 90.75 & 623.27 & 80.29 & \emph{0.900} & 540.57 &
55.65 & 564.93 & 50.04 & \emph{0.270} & 579.77 & 83.81 & 594.10 & 71.89
& \emph{0.530} & 573.30 & 63.65 & 552.75 & 53.23 &
\emph{0.310}\tabularnewline
\textbf{Na} & 12.78 & 1.33 & 11.64 & 1.32 & \emph{0.050} & 12.92 & 1.40
& 12.02 & 1.10 & \emph{0.090} & 12.85 & 1.33 & 11.83 & 1.21 & 0.008 &
11.76 & 0.97 & 12.47 & 1.31 & \emph{0.100}\tabularnewline
\textbf{N} & 2373.72 & 105.18 & 2328.41 & 58.44 & \emph{0.210} & 2008.45
& 124.99 & 1980.55 & 136.19 & \emph{0.610} & 2191.08 & 218.10 & 2154.48
& 205.11 & \emph{0.550} & 2360.71 & 71.24 & 1994.50 & 128.63 &
0.000\tabularnewline
\bottomrule
\end{longtable}

n = 24, P-values in bold, significant differences according to two-way
ANOVA, P \textless{} 0.05.

\selectlanguage{english}
\FloatBarrier
\end{document}

