Investigating the role of stomatal dynamics on agronomic traits using a slac1-2 Zea mays mutant

Investigating the role of stomatal dynamics on agronomic traits using a slac1-2 Zea mays mutant | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Investigating the role of stomatal dynamics on agronomic traits using a slac1-2 Zea mays mutant View ORCID Profile Robert J. Twohey III , View ORCID Profile Clay G. Christenson , Catherine Li , View ORCID Profile Harel Bacher , View ORCID Profile Sebastian Calleja , Bryan Pastor , View ORCID Profile Marjorie Hanneman , Liam Wickes-Do , View ORCID Profile Michael A. Gore , View ORCID Profile Duke Pauli , View ORCID Profile Stephen P. Moose , View ORCID Profile Anthony J. Studer doi: https://doi.org/10.1101/2025.01.21.634166 Robert J. Twohey III 1 Department of Crop Sciences, University of Illinois Urbana-Champaign , Urbana, IL 61801, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robert J. Twohey III Clay G. Christenson 2 The School of Plant Sciences, University of Arizona , Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Clay G. Christenson Catherine Li 1 Department of Crop Sciences, University of Illinois Urbana-Champaign , Urbana, IL 61801, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Harel Bacher 3 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University , Ithaca, NY 14853, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Harel Bacher Sebastian Calleja 2 The School of Plant Sciences, University of Arizona , Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sebastian Calleja Bryan Pastor 2 The School of Plant Sciences, University of Arizona , Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Marjorie Hanneman 3 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University , Ithaca, NY 14853, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Marjorie Hanneman Liam Wickes-Do 3 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University , Ithaca, NY 14853, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael A. Gore 3 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University , Ithaca, NY 14853, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Michael A. Gore Duke Pauli 2 The School of Plant Sciences, University of Arizona , Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Duke Pauli Stephen P. Moose 1 Department of Crop Sciences, University of Illinois Urbana-Champaign , Urbana, IL 61801, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Stephen P. Moose Anthony J. Studer 1 Department of Crop Sciences, University of Illinois Urbana-Champaign , Urbana, IL 61801, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anthony J. Studer For correspondence: astuder{at}illinois.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract The production of staple food crops is becoming increasingly difficult due to the amount of freshwater needed to realize food security for a growing global population. Climate projections show hotter and drier growing seasons in traditionally productive agricultural regions, which will increase the demand for limited water resources. Thus, strategies to improve water use efficiency will only become more important for sustainable agriculture. At the leaf level, stomatal conductance has a large influence on transpirational water loss and therefore water use efficiency. The anion channel SLAC1 has been shown in several plant species to function as the primary mechanism for stomatal closure, which allows stomatal aperture to change dynamically in response to environmental stimuli. Given that slac1 is a single gene that can significantly alter stomatal conductance, it has the potential to serve as a control point for improving water use efficiency. Here we fully characterize a Zea mays slac1-2 mutant in multiple field environments. Interestingly, homozygous slac1-2 hybrids did not show improved net CO 2 assimilation or increased grain yield despite having greater stomatal conductance compared to a wild-type hybrid. Net CO 2 assimilation and grain yield were either lower or similar in slac1-2 compared to wild-type across environments. Furthermore, the slac1-2 hybrid did not have increased nitrogen uptake. These results suggest that the C 4 carbon concentrating mechanism removes any stomatal conductance limitations to CO 2 assimilation, even in highly productive wild-type Z. mays hybrids. Because the slac1-2 hybrids eliminate stomatal conductance as a major variable for modulating water loss, future studies will be able to investigate alternate regulators of plant water potential to identify novel mechanisms for increasing water use efficiency. Introduction The production of staple food crops currently demands a large amount of water. It is estimated that current agricultural practices account for 70-75% of human freshwater consumption ( McDaniel et al ., 2017 ; Wallace, 2000 ). Climate projections predict a hotter and drier future, which would further increase agricultural water demand. The 2024 global average surface temperature was 1.6°C above pre-industrial levels and is expected to continue to rise through 2040 ( Copernicus Climate Change Service, 2024 ; IPPC, 2023). Precipitation patterns have also become more sporadic, increasing the occurrence and severity of droughts ( Gamelin et al ., 2022 ). Together, these climate variables drive the observed increases in atmospheric vapor pressure deficit (VPD), defined as the difference between the amount of moisture in the air and its saturation point. The drastic rise in VPD during growing seasons is significantly impacting crop productivity, and rectifying its effects remains challenging ( López et al ., 2021 ; Novick et al ., 2024 ). Combined precipitation deficits and high VPD can result in flash droughts during the growing seasons, which are harder to predict and control through traditional management practices ( Christian et al ., 2021 ). While current irrigation practices can suppress crop loss due to drought, studies show that increasing irrigation to combat climate change will not be a sustainable management strategy ( McDonald and Girvetz, 2013 ). Therefore, efforts targeting biological processes to better understand and improve water use efficiency ( WUE ) strategies in our major crops are needed ( Leakey et al ., 2019 ). Leaf level WUE is greatly influenced by stomatal regulation of gas exchange between the atmosphere and the intercellular airspace of the leaf. Through changes in aperture, the ratio between CO 2 assimilation ( A net ) necessary for photosynthesis and water loss via transpiration ( E ) can dynamically change in response to environmental stimuli ( Wong et al., 1979 ; Assmann and Jegla, 2016 ; Lawson and Vialet-Chabrand, 2019). The precise control of CO 2 and water flux is vital for maintaining productive and efficient plants ( Farquhar and Sharkey, 1982 ; Leakey et al ., 2019 ). Vascular plants control stomatal conductance ( g s ) by altering stomatal aperture using changes in the turgor pressure of surrounding guard cells ( Keller et al ., 1989 ). Stomatal response to environmental factors is highly dependent on biochemical signaling cascades and the speed of solute flux, as the movement of anions across the guard cell plasma membrane results in stomatal aperture changes ( Mansfield, 1983 ; Lawson and Blatt, 2014 ). One of the main guard cell-specific anion channels, SLAC1 (Slow Anion Channel-Associated 1), was originally characterized in Arabidopsis thaliana ( Negi et al ., 2008 ). A loss of function mutant in At SLAC1 resulted in over-accumulation of osmoregulatory anions and hyposensitive stomatal response ( Negi et al ., 2008 ; Vahisalu et al ., 2008 ). Upstream signaling pathways activate slac1 through the phosphorylation at its N terminus, allowing for the efflux of anions out of the guard cells and stomatal closure ( Geiger et al ., 2009 ; Lee et al ., 2009 ). Multiple environmental stimuli alter slow anion channels such as light, humidity, atmospheric CO 2 , reactive oxygen species, and abscisic acid (ABA) drought response ( Pei et al ., 1997 ; Pei et al ., 2000 ; Roelfsema and Hedrich, 2005 ; Negi et al ., 2008 ; Vahisalu et al ., 2008 ). Rather than all stimuli independently altering SLAC1 through isolated signaling pathways, these environmental cues converge to fine-tune a core ABA signaling pathway that ultimately phosphorylates SLAC1 ( Hedrich and Geiger, 2017 ). In addition to A. thaliana , SLAC1 orthologs have been studied in crop species such as Hordeum vulgare ( Liu et al ., 2014 ), Gossypium herbaceum ( Ren et al ., 2021 ), Oryza sativa ( Kusumi et al ., 2017 ), Solanum tuberosum ( He et al ., 2025 ), and Zea mays ( Qi et al ., 2018 ). In this study, we use a previously identified Z. mays slac1-2 UniformMu transposable element insertion (mu1037824), which creates a null mutation. Z. mays contains a single gene copy of slac1 with 67.4% protein homology to the A. thaliana ortholog ( Goodstein et al ., 2012 ). Initial characterization by Qi et al . (2018) found slac1-2 to have similar hyposensitive stomatal responses to changing environmental conditions, and to be highly nitrate-selective with less permeability to other anions compared to At SLAC1. Other work in Z. mays showed multiple protein kinases (ZmCPK35 and ZmCPK37) and upstream phosphatases (ZmPP84) to activate slac1 through signaling cascades. However, a complete understanding of stomatal signaling pathways in Z. mays is still lacking and its similarity to A. thaliana is not fully known ( Li et al ., 2022 ; Guo et al ., 2023 ). In C 3 species, the tight connection between g s and A net have long been known. Many studies have shown increased atmospheric CO 2 levels or increased g s leading to increases in A net and yield ( von Caemmerer and Evans, 2010 ; Lawson et al ., 2011 ; Ainsworth and Long, 2012; Kusumi et al ., 2012 ). Multiple slac1 mutants in C 3 species have been characterized to better understand the dynamic relationship between slac1 activation, g s , A net , and yield. In barley, positive correlations were found between HvSLAC1 expression and salt tolerance, indicating that increased stomatal closure improved salt tolerance and yield ( Liu et al ., 2014 ). Alternatively, a greenhouse grown rice slac1 mutant with higher g s resulted in higher photosynthetic rates ( Kusumi et al ., 2012 ). The relationship between g s and A net is thought to be weaker in C 4 species due to the presence of a CO 2 concentrating mechanism, which saturates CO 2 around Rubisco in bundle sheath cells. If Rubisco is always CO 2 saturated, it eliminates the opportunity to realize increased photosynthesis and yield by increasing g s . In this study, slac1-2 hybrids were used to further determine if Z. mays productivity is limited by the stomatal regulation of g s . Here, we fully characterize an inbred slac1-2 mutant in a dynamic field environment. Z. mays hybrids homozygous for slac1-2 were also developed and evaluated at multiple field locations representing contrasting environments. These trials allowed us to directly test the performance of hybrids with increased g s and lack of dynamic stomatal response across variable field environments. Collecting leaf gas exchange, grain yield, and nitrogen utilization data from these field trials furthers our understanding of the relationships between physiological traits and agronomic performance in a major C 4 field crop and indicates strategies for improving WUE . Material & Methods Germplasm The slac1-2 UniformMu insertion line (mu1037824 in stock UFMu 04043) was acquired from the USDA Maize Genetic Stock Center located at the University of Illinois ( Portwood et al ., 2019 ). Segregating seed was selfed in the greenhouse and field for multiple generations in 2017 to produce homozygous stocks of slac1-2 and its corresponding wild-type in a W22 background. During each generation, genetic screens were used to produce non-segregating Mu stocks. Tissue was collected from one week old seedlings and immediately placed in liquid nitrogen. DNA extractions were done following a CTAB protocol as described in ( Kolbe et al ., 2018 ). A forward AJS537 (AGCAGAGAGAAGACTTGCGG) and reverse AJS538 (TGGACGGGGAAACTTTGTAG) primer were designed to flank the transposable element insertion (mu1037824). A previously designed Mu specific primer AJS516 (GCCTCYATTTCGTCGAATCCS) was used that aligns with the inverted terminal repeats located on each end of the transposable element ( Settles et al ., 2004 ). Mu1037824 insertion was confirmed using genic-genic (AJS537/538) and genic-mutator (AJS537/516) primer sets with a Phire Hot Start II (#F-122L) PCR reaction following manufacturers recommendations. To produce the B73 X H99 slac1-2 two-way hybrid, slac1-2 was first crossed with the H99 and B73 inbred lines. Each line was then backcrossed multiple generations and selfed to produce BC 5 S 1 seed. During backcrossing, the AJS537/516 primer set was used to confirm that the slac1-2 allele was retained. Homozygous B73 X H99 slac1-2 and its corresponding B73 X H99 wild-type hybrids were then planted at each field site. Plant Growth Greenhouse grown slac1-2 and wild-type inbreds were planted in 50 well plug trays (T.O. Plastics #720568C) with a 1:1 mixture of Sun Gro Sunshine LC1 and a general purpose 1:1:1 – soil : peat : perlite mix with 2.3 kg of dolomitic lime, 0.9 kg of 0-46-0, 1.4 kg of gypsum, and 0.9 kg of Epsom per cubic yard. Plants remained in flats for 2 weeks and then were transplanted into a greenhouse ground bed. Plants were fertilized with 15-5-15 CalMag at a concentration of 300 ppm weekly and Sprint 330 chelated iron at 30 ppm was applied once to all plants around v5. During the 2021 field season, homozygous slac1-2 and wild-type inbreds were planted at the Crop Sciences Research and Education Center located in Urbana, Illinois under irrigation. Twenty kernels were planted in a 3.7 m row with 0.8 m spacing between rows and 0.9 m alleys. Nitrogen was applied to the field at a rate of 156.9 kg/ha before planting. Two rows of each genotype were planted, and six representative plants were chosen for analysis excluding end plants. The B73 X H99 slac1-2 hybrids were grown in 2022, 2023, and 2024. There were four different field locations. Illinois location 1 was the same irrigated field described for inbred measurements and Illinois location 2 was a non-irrigated field less than 1 km away. Both Illinois hybrid trials were planted in 2022 and 2023 containing thirty-five kernels planted in a 5.2 m row with 0.8 m spacing between rows and 0.9 m alleys. Illinois location 1 had nitrogen applied at a rate of 156.9 kg/ha before planting while Illinois location 2 had variable nitrogen rates that are described in the R6 sampling methods. The New York field location was located at Cornell University’s Musgrave Research Farm in Aurora, NY, trials were run in 2022 and 2023. The New York trial contained thirty-five kernels planted in 5.2 m two-row plots with 0.8 m spacing between rows and 0.9 m alleys. The New York field had 177.7 L/ha of liquid 12.5-25-0 band applied pre-planting and 318 L/ha of 30%UAN side-dressed at v5-v6. The Arizona trial was located at the University of Arizona’s Maricopa Agricultural Center in Maricopa, Arizona. The Arizona trial contained forty kernels planted in a 5.4 m row with 1 m spacing between rows and 0.7 m alleys. Total nitrogen application in Maricopa was approximately 261.2 kg/ha across the growing season. Approximately 37 kg/ha were applied preplant (DOY 71) via granular fertilizer with approximately 224.2 kg/ha applied in-season with four splits of 56 kg/ha occurring on DOY 117, 127, 139, and 155 delivered as UAN 32 applied through flood irrigation. Thermal Imaging The infrared imaging was taken in 2021 at the Illinois location 1 field site from a ladder approximately 3 m above ground level using a FLIR ThermaCAM T-400 Wes Camera (SN: 345001389) when plants were at v10. The FLIR thermal studio standard software (Version: 2.0.26) was used to capture n = 4 random but representative sampling locations on the canopy surface for each genotype. The average leaf temperature was calculated within the standardized area and used as a biological replicate. δ 13 C leaf Isotope Collection and Analysis All δ 13 C leaf sample collection was performed as described in Twohey III et al . (2019). During the 2018 greenhouse and 2021 Illinois location 1 field season, δ 13 C leaf samples were collected from healthy, uppermost fully expanded, v10-12 leaves. Leaf samples were collected from individual plants for a total of n = 4 greenhouse samples and n = 6 field samples. Each sample contained 6-12 tissue punches from each side of the midrib totaling 12-24 leaf punches per sample. Leaf tissue samples were then dried at 65°C for 7 d, ground, and stored in a desiccation cabinet until isotope analysis. Leaf stable carbon isotope analysis was run as described in Twohey III et al . (2019). The samples were run at the University of Illinois through a Costech Instruments elemental combustion system, and then a Delta V Advantage mass spectrometer to determine δ 13 C leaf values. The instrument precision has been shown to be ±0.2‰ when measuring δ 13 C. Vienna Peedee Belemnite was used as a calibration standard. Stomatal Density Three tissue samples (5 x 3cm) were collected from each greenhouse grown plant. Samples were immediately placed in liquid nitrogen then transferred to a -80°C freezer. Leaf samples were thawed and placed on microscope slides using double sided tape before imaging. A μsurf explorer optical topometer with a 20×/0.60 objective lens (image size 0.8 × 0.8 mm 2 ) was used for imaging (Nanofocus, Oberhausen, Germany). Total number of stomata were counted in each image. Three images were taken on each side of the leaf sample and averaged to produce one biological replicate (n=12). Li-6800 Steady-State and Response Curve Measurements The inbred slac1-2 measurements were taken using a LI-6800 photosynthesis system (LI-COR Biosciences, Lincoln, NE, USA) with a 3 x 3cm chamber and LED light source. Chamber temperature was set to 29°C during the 30 min. acclimation stage, and then leaf temperature was held constant during measurements. Humidity was controlled to maintain a leaf VPD of 1.5 kPa. Light was set constant at 2,000 μmol m⁻² s⁻¹. Individual plants were measured as biological replicates (n=6). Gas exchange measurements started 1 h after daybreak and ended by 14:00 the same day. For each plant measured, the leaf was clamped and remained under constant conditions at 400 ppm CO 2 for at least 30 min. When steady state was achieved, data collection began, and a measurement was taken every 10 s throughout the time course. Data points were logged at 400 ppm CO 2 for 30 min. Then the CO 2 concentration of the chamber was increased to 800 ppm and data points were logged for 30 min. allowing for the observation of stomatal closure rates and steady state values under a high CO 2 concentration. The final CO 2 change was a decrease to 100 ppm to observe stomatal opening rates. Data points were logged for 1 h at 100 ppm CO 2 due to a longer acclimation time necessary to reach steady state. Li-6800 survey measurements Survey measurements were taken on sunny days between 11:00 and 13:00. The hybrid slac1-2 measurements were taken using a Li-6800 gas exchange system with a 3 cm 2 chamber and LED light source. Flow rate was set to 500 µmol s -1 . The remaining environmental conditions were set to replicate atmospheric CO 2 , temperature, light, and humidity at the time of measurement. Plants were measured on the uppermost fully expanded leaf once v12 was reached. Once a leaf was clamped, a log was recorded after all environmental conditions reached steady state. Biological replicates varied based on location (Illinois location 1 n=12, Arizona n=24). Grain Yield Data To measure grain yield data, total ears from five plants were collected from each field trial row making sure to exclude end plants. Biological replicates varied based on location (Illinois location 1 n=12, Illinois location 2 n=6, New York n=8, Arizona n=12). The ears were dried for at least seven days at approximately 65°C. Each row was then shelled, and grain weight and grain moisture were collected. The grain weight and moisture were used to calculate grain yield at a normalized moisture of 15.5%. When grain yield data was used to calculate total Mg/ha, differences in row spacing and density were accounted for. R6 Sampling and Analysis Nitrogen uptake and utilization were determined using whole shoots sampled at physiological maturity (R6) when at least 50% of the plants showed a visible black layer at the base of the kernel. Biomass and nitrogen samples were collected and measured as described in ( Cheng et al ., 2021 ). Biomass nitrogen combustion analysis with a Fisons EA-1108 N elemental analyzer and grain nitrogen analysis using a near-infared reflectance spectroscopy on a Perten DA7200 analyzer was completed at the University of Illinois. Biological replicates varied for 2022 and 2023 ( Table 2 ). Statistical analysis Significant differences between slac1-2 and wild-type plants were tested using the (t.test) function (version 3.6.2) in R ( R Core Team (2021) ) by running a Welch’s t -test. Results Canopy thermal imaging Although the effect of mutations in slac1 have been documented at the leaf level, less is known about the extent to which the mutation alters canopy traits in the field. Thermal images were taken to determine if slac1-2 leaf temperature differences could be observed at a field canopy level. The slac1-2 inbred showed an average canopy temperature of 27.58 ± 0.19 °C. The wild-type comparator had a significantly higher canopy temperature (28.83 ± 0.08 °C) compared to slac1-2 (P < 0.001, t -test, Fig. 1 ). These results indicate that leaf level temperature scales to the canopy level in field grown slac1-2 mutants. Download figure Open in new tab Figure 1 Infrared image taken with a ThermaCAM T400 Camera. A ) RGB photo taken in 2021 field trial of slac1-2 and wild-type rows, B ) Thermal image of A, C ) Temperature analysis. The boxes in panel C represent technical reps of canopy temperature. Average temperature was calculated for the area within each square, wild-type (28.83 ± 0.08 °C) (Left, W1-4), slac1-2 (27.58 ± 0.19 °C) (Right, S1-4). Leaf isotope composition analysis of field and greenhouse grown slac1-2 inbreds The slac1-2 inbred and its comparative wild-type were planted during the 2018 greenhouse and 2021 field season to determine how the slac1-2 stomatal phenotype affects leaf isotope composition. In the greenhouse, slac1-2 showed significantly lower percent carbon (%C) values compared to wild-type, ( P < 0.01, t -test, Table 1 ) while percent nitrogen (%N) was not significantly different ( Table 1 ). Significantly less negative δ 13 C leaf values were observed in greenhouse grown slac1-2 plants compared to wild-type ( P < 0.01, t -test, Table 1 ). In the field, slac1-2 had significantly lower %C and significantly higher %N compared to wild-type ( P < 0.05 and P < 0.01 respectively, t -test, Table 1 ). Similar to the greenhouse, field grown slac1-2 also showed less negative δ 13 C leaf values compared to wild-type ( P < 0.001, t -test, Table 1 ). View this table: View inline View popup Download powerpoint Table 1 Stable carbon isotope values of greenhouse and field grown slac1-2 and wild-type W22 inbred Z. mays . Stomatal density Stomatal density was measured in slac1-2 inbred and wild-type plants, grown in the 2018 greenhouse, to determine if gas exchange differences observed in slac1-2 were solely due to dynamic aperture differences. No significant differences in stomatal density were observed between slac1-2 and wild-type plants. Average abaxial density was 52.36±1.67 in slac1-2 and 54.58±1.43 in wild-type ( P = 0.32, t -test, Sup. Fig. 1). Average adaxial density was 42.69±1.06 in slac1-2 and 43.14±1.35 in wild-type ( P = 0.80, t -test, Sup. Fig. 1). Therefore, the observed gas exchange differences were due to stomatal aperture and not stomatal density differences between slac1-2 mutant and wild-type plants. Field measured slac1-2 inbred response to CO 2 Previously, leaf level gas exchange was measured to determine slac1-2 response to CO 2 in a controlled environment with rapid (<20 minute) response curves ( Qi et al ., 2018 ). To capture the full dynamic response, extended time-course measurements were performed that allowed plants to reach a steady-state at each CO 2 concentration. Furthermore, the slac1-2 response to changes in CO 2 concentration was measured using field grown plants. Leaf g s was measured at three different atmospheric CO 2 concentrations. During the 400ppm and 800ppm CO 2 steady state, slac1-2 had significantly higher g s compared to wild-type. ( P < 0.01, t -test, Fig. 2A , Sup. Table 1 ). At a 100ppm steady state, no significant differences were observed. The same trend was seen for transpiration ( E ) where slac1-2 rates were significantly higher compared to wild-type at 400ppm and 800ppm steady states ( P < 0.01, t -test, Sup. Table 1 ). No significant difference in A net was observed between slac1-2 and wild-type across all CO 2 concentration steady states ( Fig. 2B , Sup. Table 1 ). During the CO 2 stepwise response measurements, slac1-2 had minimal response to increased or decreased CO 2 concentrations compared to wild-type ( Fig. 2C ). Download figure Open in new tab Figure 2 During the 2021 Illinois location 1 field season, stomatal response to atmospheric CO 2 was measured using gas exchange in a slac1-2 and wild-type W22 background. A) Average g s level ± standard error at ten second intervals for slac1-2 (blue) and wild-type (WT, red) during three different CO 2 concentrations defined at the top of each graph (400ppm, 800ppm, and 100ppm). Vertical dashed lines indicate change in CO 2 concentration. B) Average A net ± standard error at ten second intervals for slac1-2 and wild-type during three different CO 2 concentrations. C) Average g s ± standard error is normalized to the final point collected during the previous CO 2 concentration. Initial steady state values are normalized to the final 400 ppm data point. Hybrid slac1-2 mid-day gas exchange measurements Mid-day gas exchange measurements were taken using the Li-6800 survey method. At the 2022 Illinois location 1 field site, significantly higher mid-day rates of g s were observed in the slac1-2 hybrid compared to wild-type ( P < 0.05, t -test, Fig. 3A ). Due to higher g s rates, significantly higher E and intercellular CO 2 ( C i ) values were also observed ( P < 0.05 and P < 0.01 respectively, t -test, Fig. 2B and D ). Higher g s rates resulted in significantly lower leaf temperature in slac1-2 compared to wild-type ( P < 0.01, t -test, Fig. 3F ). Although higher C i levels were observed, there was no significant difference in A net between the slac1-2 and wild-type hybrid ( Fig. 2E ). Due to the observed increase in g s with no benefit to A net , intrinsic WUE ( iWUE , A net / g s ) was significantly lower in the slac1-2 hybrid compared to wild-type ( P < 0.01, t -test, Fig. 2C ). Mid-day gas exchange measurements taken during the 2023 Illinois location 1 and 2024 Arizona field seasons showed no significant differences in g s , E , C i , and A net / g s when the slac1-2 hybrid was compared to its respective wild-type hybrid ( Fig. 3 ). Significantly lower A net values were observed in the slac1-2 hybrid during the 2023 Illinois location 1 mid-day measurements ( P < 0.05, t -test, Fig. 2E ). Download figure Open in new tab Figure 3 Survey measurements were taken with a Li-6800 during the 2022 and 2023 Illinois location 1 and 2024 Arizona field seasons on a sunny day between 11:00 and 12:00. A) Stomatal Conductance ( g s ), B) Transpiration ( E ), C) Intrinsic water use efficiency ( iWUE, A net / g s ) , D) Intercellular CO 2 ( C i ), E) Net CO 2 Assimilation ( A net ), F) Leaf Temperature ( T leaf ). Points represent individual replicates, and the solid dash represents the average for each trait. Significant differences between slac1-2 (blue) and wild-type (WT, red) are denoted by * = P < 0.05 or ** = P < 0.01 ( t- test). To investigate the relationship between g s and A net in Z. mays , A/C i curves were measured on slac1-2 and wild-type hybrids during the 2022 field season. No differences in the rate of maximum carboxylation capacity of phosphoenolpyruvate ( V pmax ) was observed between the two genotypes. For slac1-2 and wild-type, average V pmax was 68.02±2.82 and 80.20±4.66 μmol CO 2 m -2 s -1 respectively ( P > 0.05, t -test, Fig. 4 ). No difference in CO 2 saturated photosynthetic capacity ( V max ) was observed between slac1-2 and wild-type, with an average V max of 51.97±1.02 and 53.71±1.37 μmol CO 2 m -2 s -1 respectively ( P > 0.05, t -test, Fig. 4 ). The ratio between intercellular CO 2 and atmospheric CO 2 ( C i / C a ) was calculated at two points of the A/C i curve when C a was equal to 400ppm and 800ppm. At a C a of 400ppm, C i / C a was on average 0.49±0.02 and 0.42±0.03 for slac1-2 and wild-type hybrids ( P > 0.05, t -test, Fig. 4 ), respectively. When C a reached 800ppm, significant differences were observed between slac1-2 and wild-type plants, with averages of 0.70±0.01 and 0.39±0.03 respectively ( P < 0.0001, t -test, Fig. 4 ). Download figure Open in new tab Figure 4 A/Ci curves were measured on slac1-2 (blue) and wild-type (WT, red) hybrids during the 2022 Illinois location 1 field season. Net CO 2 Assimilation ( A net ), Intercellular CO 2 ( C i ), Ambient CO 2 ( C a ). Black error bars represent standard error. Open and black filled arrows indicate the data used to calculate C i / C a at a C a of 400ppm and 800ppm CO 2 respectively. The inset bar graph represents average C a / C i ratios with error bars representing standard error (* = P < 0.05, t -test). During the 2024 Arizona field season, a weather event increased cloud cover and caused a decrease in light intensity and a corresponding parabolic shaped VPD trend within the time span of four hours (7:00 – 11:00, Fig. 5 ). A Li-600 gas exchange system was used to measure slac1-2 and wild-type hybrids throughout the morning to capture dynamic responses to changing VPD and light levels. During the first two hours of measurements (7:00 and 8:00) atmospheric VPD was 2.08 kPa and 1.98 kPa respectively. When the 9:00 measurements were taken, VPD had decreased to 1.34 kPa. Atmospheric VPD returned to 2.31 kPa before the final measurements were taken at 11:00. During this time span, the only significant difference between slac1-2 and wild-type g s was during the 9:00 measurement at a VPD of 1.34 kPa ( P < 0.05., t -test, Fig. 5 ). These results demonstrate that the slac1-2 hybrid lacked the ability to dynamically respond to environmental change ( Fig. 5 ). Download figure Open in new tab Figure 5 Gas exchange data was measured in the Arizona field trial using a Li-600 every hour from 7:00 to 11:00. The only significant difference between slac1-2 (blue) and wild-type (WT, red) hybrids was during the 9:00 measurement (* = P < 0.05, t -test). The left y-axis and colored box plots represent the stomatal conductance ( g s ) values. The box plots show the first and third quartiles, with middle horizontal lines indicating the median and the whiskers showing the outliers. Smooth trend lines were added for each genotype. The right y-axis and black points with a smooth trend line represent vapor pressure deficit (VPD) values collected from the Maricopa field site weather station. Hybrid slac1-2 yield trials and nitrogen sampling Grain yield was measured in seven different environments, across three years and four locations. Grain yield was found to be significantly different in four of the environments: Illinois location 1 2023, Illinois location 2 2022 and 2023, and Arizona 2024 ( P < 0.01 for all, t -test, Fig. 6 ). While significant differences were observed between slac1-2 and wild-type hybrids, slac1-2 never out yielded wild-type. The slac1-2 hybrid either had equal or lower grain yield compared to wild-type at all locations across all years ( Fig. 6 ). Download figure Open in new tab Figure 6 slac1-2 (blue) and wild-type (red) hybrids were grown at multiple field locations to determine if stomatal control of CO 2 uptake limits grain yield in Z . mays. slac1-2 and wild-type grain yield data was normalized to 15.5% moisture and converted to megagrams per hectare (Mg hec -1 ) for all field sites. Field site years are denoted on the top x-axis and field locations are on the right y-axis. Significant differences between the two genotypes are denoted by * = P < 0.05, ** = P < 0.01, *** = P < 0.001, **** = P < 0.0001 ( t -test). In 2022 and 2023, R6 biomass and nitrogen content was measured under two nitrogen treatments (0 kg/ha and 225 kg/ha) at the Illinois location 2 field. Overall, trends showed that dry stalk biomass, cob biomass, dry stover biomass, and total biomass was lower in slac1-2 compared to wild-type hybrids ( P > 0.05, t -test, Table 2 ). In 2023, slac1-2 plant height was significantly shorter than wild-type under 0 kg/ha nitrogen ( P < 0.001, t -test) and 225 kg/ha nitrogen ( P < 0.01, t -test, Supp. Table 2 ). Stalk nitrogen and stalk percent nitrogen was similar between the two genotypes, except stalk percent nitrogen was significantly greater in slac1-2 compared to wild-type in the 2022 0 kg/ha treatment ( P < 0.05, t -test, Table 2 ). Grain nitrogen was similar under 0 kg/ha applied nitrogen in both years and significantly lower in slac1-2 compared to wild-type at 225 kg/ha nitrogen in 2022 and 2023 ( P < 0.05 and P < 0.01 respectively, t -test, Table 2 ). Grain protein was significantly higher in slac1-2 compared to wild-type across all years and nitrogen treatments ( P < 0.05, t -test, Table 2 ). View this table: View inline View popup Table 2 Measured traits from R6 sampling during the 2022 and 2023 Illinois location 2 field trial. Discussion During this study, slac1-2 inbred and hybrid lines were evaluated in multiple field locations. These trials improved our understanding of the relationships between physiological traits and agronomic performance. The collection of leaf gas exchange, grain yield, and nitrogen utilization data from hybrids with increased g s and lack of dynamic stomatal response further elucidates the role stomata play in the delicate balance between improved WUE and plant productivity. Thermal imaging has become a well-established high-throughput method for screening diverse populations and predicting crop productivity under varying water conditions ( Liu et al . 2011 ; Pignon et al ., 2021 ; Wen et al ., 2023 ). Significant correlations have been observed between leaf temperature and g s using thermal imaging ( Winterhalter et al ., 2011 ; Zia et al ., 2013 ). Thermal imaging was previously used to identify At slac1-2, an allelic variant of the original At slac1-1, in an EMS-mutagenized A. thaliana population ( Negi et al ., 2008 ). Other studies have observed that slac1 significantly alters leaf temperature in A. thaliana , O. sativa , and Z. mays ; however, all of the thermal imaging data has been collected in controlled growing environments ( Kusumi et al ., 2012 ; Qi et al ., 2018 ; Wang et al ., 2022 ). To test these findings in a natural and dynamic environment, field grown slac1-2 Z. mays was imaged using a thermal camera. Field grown slac1-2 was found to have a significantly cooler leaf canopy by an average of 1.25°C compared to wild-type ( Fig. 1 ). This result supports that slac1-2 has higher g s rates in a field environment and at a level that impacts canopy dynamics. During CO 2 response measurements, field grown slac1-2 inbreds were insensitive to a CO 2 change from 400ppm to 800ppm. These findings are consistent with past results showing slac1-2 insensitivity to increased CO 2 measured during a shorter time-course in a controlled growth environment ( Qi et al ., 2018 ). These findings provide strong evidence that Z. mays slac1 facilitates anion efflux out of guard cells and controls stomatal closure, similar to A. thaliana ( Vahisalu et al ., 2008 ; Cotelle and Leonhardt, 2016 ). Unique to this study is the measurement of Z. mays slac1-2 mutant plant’s response to decreasing CO 2 . An increase in g s was observed in slac1-2 , indicating maintained ability to accumulate anions within the guard cells and open its stomata in response to decreased CO 2 ( Fig. 2A ). It is believed that stomatal opening occurs while S-type anions are inactivated and they do not play a vital role (Schwarts et al ., 1995; Marten et al ., 2007 ). However, past evidence would suggest slac1 can affect the rate of stomatal opening, indicating potential crosstalk between anion and uptake channels ( Laanemets et al ., 2013 ; Hedrich and Geiger, 2017 ). The vast difference in g s starting values within this data set makes comparing stomatal response rate to decreasing CO 2 unreliable. Therefore, further studies are needed to determine if slac1 can alter stomatal opening rates in Z. mays . During three of the slac1-2 hybrid field trials, survey measurements were collected to determine leaf gas exchange of field adapted plants. These measurements allowed us to capture how slac1-2 was performing in a dynamic field environment rather than a controlled environment where plants are allowed time to reach steady state. In the 2022 Illinois location 1 field, slac1-2 showed a significantly higher g s , E , and C i . However, during the 2023 and 2024 field trials slac1-2 performed equal to wild-type and no differences were observed ( Fig. 3 ). Similar trends were observed in greenhouse grown rice where slac1 g s was only significantly higher than wild-type for a proportion of the developmental timeline ( Kusumi et al ., 2017 ). Previous data collected from acclimated plants implies that slac1 -2 shows a consistently more open stomatal phenotype and higher rates of g s all the time ( Fig. 2A ). However, this survey data suggests that in a field environment, slac1-2 loses its ability to dynamically respond to environmental changes. This can further be supported by the 2024 Arizona survey measurements taken during the weather event that resulted in variable VPD ( Fig. 5 ). Wild-type plants close their stomata and reduce g s in response to increased cloud cover and decreased light and VPD. A slight decrease in g s can also be observed in slac1-2 due to a decrease in transpirational demand (lower VPD). However, the absence of a stomatal closure response to increased cloud cover results in a significantly higher g s in slac1-2 compared to wild-type at 9:00. Interestingly, slac1-2 and wild-type hybrids do not show significantly different g s values before and after the light and VPD drop occurred. Thus, because the true phenotype of a slac1 mutant is lack of response, depending on the environment, mutants could have either a higher or lower g s value than wild-type plants when instantaneous measurements are taken. Leaf stable carbon isotope composition (δ 13 C leaf ) was measured for tissue collected from greenhouse and field grown slac1-2 plants. Assaying δ 13 C leaf has been shown to be an integrated measure of carbon metabolism linked to iWUE in C 4 species ( O’Leary, 1981 ; Twohey III et al ., 2019). Based on C 4 isotope theory, increased g s would result in a less negative δ 13 C (O’Leary, 1988), which has been observed in other Z. mays studies ( Avramova et al ., 2019 ; Crawford et al ., 2024 ). In the greenhouse and field grown slac1-2 plants, significantly less negative δ 13 C values were observed compared to wild-type ( P < 0.01 and P < 0.001 respectively, t -test, Table 1 ). These results indicate that slac1-2 stomatal hyposensitivity is altering plant g s not only at the time of extreme environmental changes, but throughout plant development. Furthermore, because of the less negative δ 13 C value, even though not all instantaneous gas exchange measurements capture greater g s in slac1 mutant plants, the cumulative effect of the mutation is higher g s and greater water loss. To determine if stomatal limitation of CO 2 uptake for photosynthesis exists in C 4 Z. mays , A / C i curves were measured. During the A / C i curves no significant difference was observed in A max , although slac1-2 mutants tended to be slightly lower. During increased C a (800ppm), slac1-2 had a significantly higher C i / C a value compared to wild-type, consistent with a greater stomatal aperture and inability to close in response to elevated CO 2 concentrations ( Fig. 4 ). Observing higher C i / C a values with no significant benefit in A net supports the idea that C 4 often remains CO 2 saturated and increased g s does not increase productivity. Although not shown to be significant, the opposite trend was observed in rice, a C 3 species. Two studies observed slight increases in A net under high C i / C a levels in slac1-2 compared to wild-type ( Kusumi et al ., 2012 ; Kusumi et al ., 2017 ). To further determine if Z. mays productivity is at all limited by CO 2 uptake, we collected grain yield data from seven different field environments. Some significant differences were seen between slac1-2 and wild-type hybrids; however, slac1-2 never out yielded wild-type ( Fig. 6 ). These results highlight the utility of the C 4 carbon concentrating mechanism, and the extent to which it enables a reduced g s without a corresponding decrease in A net or grain yield. The diverse environments highlight the performance of a CO 2 concentrating mechanism in wild-type hybrids under well-watered and high light environments. Therefore, an opportunity exists for targeting g s in Z. mays to improve iWUE while maintaining plant productivity. These results are consistent with a previous study targeting slac1 in a field environment to determine its effects on yield under drought conditions. Z. mays inbred and hybrid lines overexpressing the protein kinases ZmCPK35 and ZmCPK37 increased yields by activating slac1 and inducing stomatal closure under drought conditions ( Li et al ., 2022 ). There is mounting evidence that plant transpiration passively regulates nitrogen uptake (Mengel and Kirby, 1987; Novák and Vidovič, 2003 ; Niu et al ., 2007 ; Kunrath et al ., 2020 ). The slac1-2 field trials allowed us to directly measure if increased g s would lead to higher plant nitrogen uptake or utilization. Despite slac1-2 inbreds having a higher leaf %N at V10-12 ( Table 1 ), a greater %N was not observed in the hybrid R6 data ( Table 2 ). During the two field trials both slac1-2 and wild-type had equally reduced grain nitrogen under a 0 kg/ha nitrogen rate, but wild-type had a significantly greater response to a nitrogen rate of 225 kg/ha compared to slac1-2 . Overall, nitrogen availability seemed to be similar in slac1-2 and wild-type; however, slac1-2 did not utilize the available nitrogen. This can be observed in the grain nitrogen utilization efficiency (NutE) values where slac1-2 was significantly lower than wild-type in almost all conditions ( Table 2 ). The slac1-2 hybrid facilitated the investigation of stomatal dynamics in a Z. mays background comparable to commercially relevant germplasm and in production field environments. Using gas exchange, grain yield, and nitrogen data to measure slac1-2, we observed that the CO 2 concentrating mechanism in Z. mays is not significantly limited by g s under a variety of field conditions. This is supported by the lack of A net or grain yield increases in slac1-2 hybrids across all field trials. Future studies using an overexpression of slac1-2 might allow us to reduce g s and identify an optimum response sensitivity that maximizes WUE without negatively affecting A net and grain yield. Additionally, because slac1-2 removes stomata as the major regulator of plant water loss, alternate mechanisms that modulate plant water potential can be probed to reveal novel approaches to further improving WUE . Author Contributions R.J.T and A.J.S conceived the project. R.J.T. and A.J.S. developed the germplasm. R.J.T, A.J.S, S.P.M, M.A.G, and D.P designed field experiments. R.J.T performed inbred field experiments. R.J.T, C.G.C, C.L, H.B, S.C, B.P, M.H, and L.W performed hybrid field experiments. R.J.T analyzed the data. R.J.T and A.J.S wrote the manuscript. All authors reviewed and revised the manuscript. We have no conflicts of interest to disclose. Acknowledgments and Funding We thank all technical support and field managers from the Studer, Moose, Gore, and Pauli Labs. Much thanks to Andrew Leaky for the use of the stomatal imaging microscope. We would like to thank the Maize Genetic Cooperation Stock Center for supplying the original slac1-2 germplasm, especially Marty Sachs for valuable discussion. This research was performed with support from the Center for Research on Programmable Plant Systems under National Science Foundation Grant No. DBI-2019674 and the United States Department of Agriculture Hatch funds as well as additional funding to D. P. (NSF IOS 2102120; NSF IOS 2023310; USDA NIFA SCRI # 2021-51181-35903; Cotton Inc. 23-890). Citations Ainsworth EA , Long SP ( 2021 ) 30 years of free-air carbon dioxide enrichment (FACE): What have we learned about future crop productivity and its potential for adaptation? 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