RosettR: protocol and software for seedling area and growth analysis

Plant height, number of leaves, diameter and fresh weight of the bulbs, and the dry weights of the component plant parts of 3 onion cvs were measured weekly, starting 40 days after transplanting, up to maturity. Red Kano had singificantly more leaves, greater leaf area, larger bulbs and fresh and dry weights than Eclipsel Bermuda and Texas Grano.Net Assimilation Rate (NAR), Relative Growth Rate (RGR), and Relative Leaf Growth Rate (RLGR) were generally high in the early stages of growth in all cvs and declined with plant age. Red Kano had much higher values than the other two. Crop Growth Rate (CGR) of tops was positive in the early stages of plant growth in all the cvs but decreased to negative values towards maturity which was due to a decrease in the dry weight of the leaf blades caused by decrease in leaf number. Red Kano and Texas Grano showed positive values throughout the experimental period. The higher CGR for the bulbs as compared to the blades was due to large quantities of carbohydrates which were translocated to the bulbs. Leaf Area Ratio (LAR) was constant in Red Kano, due to proportionate increase in leaf blade area and weight.Results of all the growth characteristics showed that Red Kano was superior to the other cvs in attaining a larger bulb size due to large number of leaves and longer growing season, resulting in the translocation of more carbohydrates to the bulbs.

Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites. eLife digest Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another. When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states. More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located. To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery. After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects. McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like. Introduction In allosteric regulation, protein activity is modulated by an input effector signal spatially removed from the active site. Allostery is a desirable engineering target because it can yield sensitive, reversible, and rapid control of protein activity in response to diverse inputs (Dagliyan et al., 2019; Pincus et al., 2017; Raman et al., 2014). One common approach for achieving allosteric regulation in both engineered and evolved systems is through domain insertion: the transposition, recombination, or otherwise fusion of an ‘input’ domain into an ‘output’ domain of interest (Aroul-Selvam et al., 2004; Dagliyan et al., 2016; Ostermeier and Benkovic, 2000; Nadler et al., 2016). In natural proteins, domain insertions and rearrangements play a key role in generating regulatory diversity, with kinases serving as a prototypical example (Fan et al., 2018; Huse and Kuriyan, 2002; Peisajovich et al., 2010; Shah et al., 2018). In engineered proteins, domain insertions have been used to generate fluorescent metabolite biosensors (Nadler et al., 2016), sugar-regulated TEM-1 β-lactamase variants (Guntas et al., 2005), and a myriad of light-controlled proteins including kinases, ion channels, guanosine triphosphatases, guanine exchange factors, and Cas9 variants (Dagliyan et al., 2016; Wang et al., 2016; Karginov et al., 2011; Toettcher et al., 2013; Shaaya et al., 2020; Coyote-Maestas et al., 2019; Richter et al., 2016). In all cases, domain insertion provides a powerful means to confer new regulation in a modular fashion. However, naively created domain insertion chimeras sometimes exhibit relatively modest allosteric dynamic range, with small observed differences in activity between the constitutive and activated states (Lee et al., 2008). These fusions then require further optimization by either evolution or empirical mutagenesis, but general principles to guide this process are largely absent. Which mutations tune or improve an allosteric system? Because we lack comprehensive studies of allosteric mutational effects in either engineered or natural systems, it remains unclear whether such mutations are common or rare, and what magnitude of allosteric effect we might typically expect for single mutations. Additionally, it is not obvious if such mutations are structurally distributed or localized (for example, to the insertion site). Answers to these questions would inform practical strategies for optimizing engineered systems and provide insight into the evolution of natural multi-domain regulation in proteins. To address these questions, we performed a deep mutational scan of a synthetic allosteric switch: a fusion between the E. coli metabolic enzyme Dihydrofolate Reductase (DHFR) and the blue-light sensing LOV2 domain from A. sativa (Lee et al., 2008; Reynolds et al., 2011). This modestly allosteric chimera shows a 30% increase in DHFR velocity in response to light. Focusing on mutations to the DHFR residues, we found that only a small fraction (4.4%) of the mutations that retained DHFR activity had a statistically significant impact on allostery. Individual mutations exhibited generally modest effect sizes; the most allosteric single mutant characterized (H124Q) yielded a twofold increase in velocity in response to light relative to the starting construct. Structurally, allostery disrupting mutations tended to cluster near the LOV2 insertion site and were modestly enriched at both conserved and co-evolving amino acid positions. In contrast, allostery enhancing mutations were distributed across the protein, and strongly associated with the protein surface. We observed that combining a few of these mutations yielded near-additive enhancements to allosteric dynamic range. Collectively, our data elucidates practical strategies for optimizing engineered systems, and shows that weakly conserved, structurally distributed surface sites can contribute to allosteric tuning. Results Characterization of an unoptimized allosteric fusion of DHFR-LOV2 To begin our study of allostery tuning mutations, we selected a previously characterized synthetic allosteric fusion between DHFR and LOV2 generated in earlier work (Lee et al., 2008; Reynolds et al., 2011). In this fusion, the LOV2 domain of A. sativa is inserted between residues 120 and 121 of the E. coli DHFR βF-βG loop; we refer to this construct as DL121 (Figure 1A,B). The choice of LOV2 insertion site was guided by Statistical Coupling Analysis (SCA), an approach for analyzing coevolution between pairs of amino acids across a homologous protein family (Rivoire et al., 2016; Lockless and Ranganathan, 1999; Halabi et al., 2009). A central finding of SCA is that co-evolving groups of amino acids, termed sectors, often form physically contiguous networks in the tertiary structure that link allosteric sites to active sites (Halabi et al., 2009; Süel et al., 2003; Pincus et al., 2018). To create the DL121 fusion, Lee et al. followed the guiding principle that sector connected surface sites in DHFR might serve as preferred sites (or ‘hot spots’) for the introduction of allosteric regulation (Lee et al., 2008). The resulting DL121 fusion covalently attaches the N- and C-termini of LOV2 into a sector connected surface on DHFR, and displays a twofold increase in DHFR hydride transfer rate (khyd) in response to blue light (Lee et al., 2008). Under steady-state conditions, we measured a 28% increase in the turnover number (kcat) in response to light and a statistically insignificant change in the Michaelis constant (Km) (Figure 1C). Thus, the DL121 fusion is modestly allosteric in vitro. As DHFR has no known natural allosteric regulation, the LOV2 insertion confers a new, evolutionarily unoptimized regulatory input. Figure 1 Download asset Open asset The DL121 DHFR/LOV2 fusion. (A) Composite structures of the individual DHFR and LOV2 domains (PDB ID: 1R × 2 and 2V0U), indicating the LOV2 insertion site between positions 120 and 121 of DHFR (Sawaya and Kraut, 1997; Halavaty and Moffat, 2007). DHFR is in gray cartoon, NADP co-factor in green sticks, and folate substrate in yellow sticks. In LOV2 signaling, blue light triggers the formation of a covalent adduct between a cysteine residue (C450) and a flavin mononucleotide (FMN, yellow sticks) (Salomon et al., 2001; Crosson and Moffat, 2002; Swartz et al., 2002) and associated unfolding of the C-terminal Jα-helix (red cartoon); this order-to-disorder transition is used for regulation in several synthetic and natural systems (Pudasaini et al., 2015; Glantz et al., 2016). (B) DHFR loop conformational changes near the LOV2 insertion site. While the mechanism of DHFR regulation by LOV2 is currently unknown, inspecting the native DHFR structure provides some insight. The substrate-bound Michaelis complex of native DHFR is in the ‘closed’ conformation (gray cartoon), while the product ternary complex is in the ‘occluded’ state (purple cartoon). The βF-βG loop, where LOV2 is inserted, is highlighted in cyan. In native DHFR, hydrogen bonds between this loop (Asp122) and the Met20 loop (Gly15, Glu17) are thought to stabilize the closed conformation (Sawaya and Kraut, 1997; Schnell et al., 2004). Mutations to positions 121 and 122 reduce activity and cause the enzyme to prefer the occluded conformation (Cameron and Benkovic, 1997; Mhashal et al., 2018; Miller and Benkovic, 1998). (C) Steady state Michaelis Menten kinetics for the DL121 fusion under lit (blue) and dark (gray) conditions. The kcat of DHFR increases 28% in response to light; the difference in Km is statistically insignificant (Supplementary file 1a). Error bars represent standard deviation for three replicates. (D) Quantifying the allosteric effect of mutation. Allostery for the DL121 fusion is reported as the ratio between lit and dark velocity. The effect of a mutation on allostery is then computed as the ratio of mutant allostery to wt-DL121 allostery (bottom blue box). But can this relatively small allosteric effect generate measurable physiological differences that could provide the basis for evolutionary selection? DHFR catalyzes the reduction of 7,8-dihydrofolate (DHF) to 5,6,7,8-tetrahydrofolate (THF) using NADPH as a co-factor. THF then serves as a one-carbon donor and acceptor in the synthesis of thymidine, purine nucleotides, serine, glycine, and methionine. Because of these critical metabolic functions, DHFR activity is strongly linked to growth rate, and under appropriate conditions, E. coli growth rate can be used as a proxy for DHFR activity (Reynolds et al., 2011; Thompson et al., 2020). Prior work found that the modest in vitro allosteric effect of DL121 conferred a selectable growth rate advantage in vivo: when an E. coli DHFR deletion strain (ER2566 ΔfolAΔthyA) was complemented with DL121, the resulting strain grew 17% faster in the light than in the dark (Reynolds et al., 2011). Thus, DL121 is a system where: (1) allosteric control is rapidly and reversibly applied, (2) the allosteric effects on activity can be readily quantified both in vitro and in vivo, and (3) there remains potential for large improvements in regulatory dynamic range through mutation. A high-throughput assay to resolve small changes in DHFR catalytic activity Our goal was to measure the effect of every single amino acid mutation in DHFR on the allosteric regulation of DL121. To do this, we aimed to follow a strategy loosely akin to a double mutant cycle (Figure 1D). The starting DL121 construct shows so-called V-type allostery, in which the effector (light) regulates the catalytic turnover number (kcat) (Carlson and Fenton, 2016). Thus, allostery can be quantified as the ratio of kcat between lit and dark states. More generally, allostery might be considered as a ratio of velocities (v = kcat [S]/(Km + [S])) between the lit and dark states, as the allosteric effector could regulate turnover, substrate affinity, or both. In either case, we defined the allosteric effect of mutation as the fold change in allosteric regulation upon mutation (Figure 1D, blue box). We sought to infer this quantity for every mutation in a saturation mutagenesis library of DHFR by using growth rate as a proxy for catalytic activity. As in prior work, we measured the growth rate of many E. coli strains in parallel by using next generation sequencing (NGS) to monitor the frequency of individual DHFR mutants over time in a mixed culture (Figure 2; Reynolds et al., 2011; Thompson et al., 2020). Allele frequencies (fa) at each time point (t) were normalized as follows: fa=ln⁡NaNWTt-lnNaNWTt=0 where Na and NWT are the number of mutant and wildtype (WT) counts at a given time point. By performing a linear fit of the log normalized allele frequencies vs. time we calculated a slope corresponding to relative growth rate: this value is the difference in growth rate for the mutant relative to a reference ('WT') construct. Figure 2 Download asset Open asset A high-throughput, high-resolution assay for DHFR activity. (A) The turbidostat. The instrument has 15 individual growth chambers (vials), positioned on a stir plate inside an incubator. Illumination was provided by blue LEDs in each vial holder. (B) Log-normalized relative allele frequency over time for 11 DHFR point mutations of known catalytic activity and the DL121 fusion. Allele frequency (colored circles) was determined by next-generation sequencing of mixed-population culture samples at each time point. All frequencies were normalized to t = 0 and WT DHFR (no LOV2 insertion). Error bars reflect standard error across four measurements, they are sometimes obscured by the marker. The slope for each line of best fit provides the growth rate of each mutant allele relative to WT DHFR. (C) Relative growth rate vs. log10(velocity) for the 11 DHFR mutants and DL121 as characterized in panel B. Color coding of mutations is matched to panel B. Error bars reflect standard error of the mean over four replicates. The dashed line was fit by linear regression to all mutants in the linear regime (M42F excluded). As individual mutations tend to exhibit modest effects on allosteric regulation, we optimized the linear regime and resolution of the growth rate assay in two ways (Reynolds et al., 2011). First, we grew the E. coli populations in a turbidostat outfitted with blue LEDs to activate LOV2 (Figure 2A). The turbidostat maintains each culture in exponential growth by dynamically sensing optical density and adjusting media dilution rate accordingly Toprak et al., 2013; this ensures near-constant media conditions and eliminates the need for manual serial dilutions. Second, we selected media conditions – M9 minimal media with 0.4% glucose and 1 µg/ml thymidine supplementation – in which growth rate can resolve subtle differences in catalytic activity near the DL121 fusion. We evaluated the resolution of our assay using a ‘standard curve’ of 11 point mutations of known catalytic activity in non-chimeric DHFR (Figure 2B). Under these conditions, we observed a log-linear relationship between relative growth rate and DHFR velocity over nearly four orders of magnitude; this relationship saturates (plateaus) for the most active mutants (WT and M42F, Figure 2C). Importantly, the relative growth rate and velocity of DL121 were near the center of the linear regime of our assay. In using velocity to describe our data, we have incorporated two assumptions: (1) we presume minimal variation in protein abundance between mutants (enzyme concentration is equal to one) and (2) we fix the substrate concentration at 25 µM, which was previously reported as the endogenous concentration for WT E. coli (Kwon et al., 2008). Individual mutations may cause variation in protein abundance, but because allostery concerns a relative change in activity, light-independent differences in abundance can be removed by appropriate normalization (as discussed further below). As previously observed, the exponential divergence of mutants with different growth rates in a population makes it possible to detect even small biochemical effects (Breslow et al., 2008). More specifically, we can discriminate a change of ±0.02 µM−1 s-1 in catalytic power (kcat/Km) under these conditions. This level of precision is on par with – and in some cases better than – literature-reported errors for in vitro steady state kinetics measurements of DHFR (Reynolds et al., 2011; Wagner et al., 1992; et al., we can resolve small catalytic and allosteric effects of mutations on DL121 through this high-throughput assay. mutations are enriched at conserved, positions in DHFR In to the of individual DHFR positions to we a deep mutational library over all DHFR positions in the DL121 fusion (Figure we measured the growth rate effect of each mutation in under both lit and dark conditions using the assay (Figure Figure Figure data In this all growth rates were calculated relative to the DL121 fusion, which activity growth to WT DHFR. Mutations into four in of growth rate deleterious (Figure (Figure or light Figure We were to measure growth rate for of the possible mutations over were at the of the = for one or more to as and an were from the library the of three time for growth rate refer to these as see also Materials and Figure We these rapidly mutants as deleterious to growth rate and DHFR activity. The relative growth rates for the mutations were with a between pairs (Figure Figure with see all Download asset Open asset The effect of DL121 DHFR mutations on growth relative growth rate trajectories for three mutations. (A) DL121 was deleterious in both lit and dark conditions. (B) DL121 was under both lit and dark conditions. (C) DL121 was deleterious in the and near in the light. were by linear the slope of these provides the difference in growth rate relative to the DL121 construct. Relative growth rates were measured in for each mutant under lit (blue) and dark (gray) conditions. (D) of relative growth rates under dark conditions. The for all mutations with measurable growth rate effects is in gray and the for sector mutations is in The relative growth rate of DL121 a mutation that disrupts catalytic activity, is with a dashed The fraction of DL121 mutations with measurable growth rates that can be DHFR and evolutionarily conserved Materials and methods for The fraction is for both the library (gray and the library after mutations with growth rate DL121 The number of mutations is each A the between mutations in the sector a of and the mutations that yield growth rate DL121 of positions enriched for mutations with growth rates as as or than DL121 (red The DHFR is in gray cartoon, the folate substrate in yellow sticks, and the NADP co-factor in green sticks. of the sector blue to positions enriched for disrupting mutations (red as in Figure data 1 Relative growth rates under lit and dark conditions for DL121 point mutations as determined by next-generation 1 is the mutation are relative growth rates in the light is the lit relative growth rate, and is the standard deviation across lit replicates. are relative growth rates in the dark is the dark relative growth rate, and 11 is the standard deviation across dark replicates. Relative growth rate of indicate mutations with counts to fit a growth rate of indicate mutations from the library at t = 0 Download the allosteric effects of mutations, we considered the effects of mutations on growth rate DHFR in a single growth Prior work has found that deleterious mutations are enriched at evolutionarily conserved positions and the protein sector et al., The DHFR sector was defined by analyzing coevolution in a of native DHFR we to examine if sector positions were critical to function in the DL121 fusion. between the DHFR evolutionary and deleterious mutations in DL121 would provide that the of native DHFR in the The of mutations were at modestly deleterious to growth, with a relative growth rate of in the dark and in the light (Figure A cluster of mutations was observed just the LOV2 insertion site at 121 in both conditions, some potential to for the inserted LOV2 (Figure The of effects shows some differences relative to prior studies of natural proteins including native E. coli DHFR et al., 2020; et al., First, the of effects for mutations in natural proteins is often a of mutational et al., et al., of native DHFR – under conditions to resolve mutational effects near WT – many mutations et al., 2020). are two for the relative of and mutations in the First, the DL121 fusion is because the unoptimized LOV2 insertion an to DHFR the conditions of our assay and from prior work et al., and were selected to resolve mutational effects near mutations with (or activity are in the regime of our assay. To the – and or – mutations, we an empirical growth rate of to the lit and dark growth This to the growth rate for DL121 is an active site mutation that strongly the activity of WT DHFR (Figure The DL121 mutant in the conditions of our assay and is in the of thymidine supplementation (Figure We found that mutations with growth rates at or this the were enriched in both the sector Figure file and at evolutionarily conserved positions Figure file When to the WT DHFR positions enriched for deleterious mutations the active site and co-factor (Figure structurally with the sector (Figure and a number of positions known to play a critical role in WT DHFR and et al., et al., These data are with the that sector positions to play a key role in DHFR catalytic activity in the DL121 fusion. the that DHFR variants are both and associated with the growth rate measurements (Figure we removed the of rate and mutations prior to the of allostery. The retained 1548 mutations – of the growth assay data – between the DL121 and evolutionarily conserved positions (Figure These a and of the data for mutational effects on DL121 allosteric Allostery tuning mutations are To the allosteric effect of we considered the measurements of lit and dark relative growth rate for each mutant (Figure the log-linear relationship between growth rate and DHFR velocity (Figure growth rates of Thus, we the allosteric effect of mutation by the difference in the relative growth rates between lit and dark In the is relative growth rate is measured in our and to growth indicate allostery enhancing mutations and indicate allostery disrupting mutations and the 1548 mutations the allosteric effect is distributed with a mean near = Figure To the of allosteric we computed a for each mutation by under the that the lit and dark measurements have equal These were to a of determined by of Figure and 2011). Under these only mutations of all viable mutations enhanced allostery while disrupted allostery. We not a between the magnitude of growth rate effect and the allosteric effect mutations a range of growth rates and exhibited modest effects on light regulation (Figure Figure with see all Download asset Open asset The effect of DL121 DHFR mutations on

Growth and development of channel millet (Echinochloa turneriana) in relation to its potential as a crop plant and compared with other Echinochloa millets, rice and wheat

Relative growth of the human fetal skull in width, length and height

Potassium requirements for growth—dry matter (DM) and leaf area (LA) and related processes — relative leaf growth rate (RLGR), relative growth rate (RGR), net assimilation rate (NAR) and crop growth rate (CGR) were determined by plant analysis during the entogeny of wheat. Wheat (Triticum aestivum cv. HD 2329) plants were supplied with different amounts of K from deficient to adequate through nutrient solution. Samples were taken at specific stages for K determinations. The DM and LA were recorded at 45d, 75d and 105d. The growth related processes RGR, NAR and CGR were estimated between 30–45d, 45–75d and 75–105d. In case of RLGR the observations were carried out between 15–30d, 30–45d and 45–75d. These physiological processes and grain yield were correlated with K concentration in whole plant at 30 and 45d and top two leaves at 75 and 105d.

• To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes. • The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times. • Using the system, a single researcher can phenotype up to 7000 plants d⁻¹. Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excess mutant sex4-3 and the growth-enhanced mutant grf9. • We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.

Aims: Relative growth rate (RGR) is an indicator of the extent to which a species is using its photosynthates for growth and it is affected by environmental factors, including temperature. Nevertheless, most of plant growth studies have been carried out at a single growth temperature or at different temperature treatments, resulting in the lack of information on the relationship between RGR and changing mean daily air temperature. We analyzed the temporal changes in RGR during early growth stages in three Cistus species grown outdoor in a common garden from seeds of different provenances. Moreover, we wanted to define the relationship between daily changes in RGR and mean daily air temperature for the considered provenances. The hypothesis that intra-specific temporal variations in RGR can reflect differences in the behavior to maximize RGR (RGRmax) in response to temperature was tested. Methods: Seedlings of C. salvifolius, C. monspeliensis and C. creticus subsp. eriocephalus were grown outdoor in the experimental garden of the Sapienza University of Rome under a Mediterranean climate. We analyzed early growth with non-linear growth models and calculated function-derived RGRs as the derivative with respect to time of the parameterized functions used to predict height divided by current height. The relationships between function-derived RGRs and mean daily air temperature were analyzed by linear and non-linear models, which were ranked according to their standard errors and correlation coefficients. The temperature dependency of RGRmax per each provenance was evaluated through the relationship between RGRmax and the coefficients of the best regression model obtained. Important Findings: A parameter that could summarize the temperature dependency of RGR up to RGRmax during the early growth stages for the selected provenances was defined. This allowed us to highlight that a greater RGR temperature responsiveness was related to a delay in the time to reach RGRmax independently by the species. Nevertheless, a greater temperature sensitivity of RGR lead to a reduced maximum height which reflects a negative trade-off between the length of the developmental phases and the extent of RGR temperature responsiveness. Thus, variations in temperature responsiveness of RGR up to RGRmax have a significant role in shaping the early growth for the investigated species. Our findings quantitatively define provenance dependent strategies by which the selected species cope with daily air temperature variations during early growth.

Silver maple (Acersaccharinum L.) and eastern cottonwood (Populusdeltoides Bartr.) seedlings were treated with either 0.0, 0.1, 0.2, or 0.3 ppm ozone for 12 h/day for up to 60 consecutive days. Six seedlings were harvested from each treatment at 10-day intervals to construct growth curves for leaf area, leaf weight, and stem plus leaf weight. Relative growth parameters were calculated from these curves. Relative growth rate, relative leaf-area growth rate, and relative leaf-weight growth rate declined with an increase in time and ozone concentration. Net assimilation rate declined with time in both species. Specific leaf area and leaf-area ratio had no consistent trends.

The growth and yields in respect to the water relations of field bean crops (Vicia faba L. cv. Maris Bead) subjected to three irrigation regimes were examined. The well-watered crop showed significantly higher seed and biological yields than the intermediate and dry ones. Moreover, the wet plots exhibited significantly higher values of leaf area duration (LAD) than the intermediate and dry plots. Significant differences were found occasionaly between the wet and the other two treatments as regards the relative growth ratesin dry matter and leaf area. The crop growth rate and net assimilation rate were mainly affected by plant development and other factors. LAD was highly correlated with the average plant water potential (Ψ), while the relative growth rates in dry matter and leaf area exhibited significant though less marked correlations. Seed yield was well correlated with the LAD only after flowering, but with Ψ already from the initial growth stages. Cell turgor appeared to have played an important role on both leaf area growth and final yields.

Experiments were performed at farmers’ fields of five locations viz., Mymensingh, Sherpur, Jamalpur, Natore and Naogaon districts with two promising Boro rice mutants, RM-16(N)-8, RM-16(N)-10 and a check, BRRI dhan58 to evaluate some morpho-physiological features and its impact on grain yield. The experiment was setup in RCB design with three replications. Results revealed that high yielding genotypes, in general, showed superiority in morpho-physiological characters (leaf area, leaf area index, total dry mass production, absolute growth rate, relative growth rate, chlorophyll, total sugar and soluble protein content in leaves and harvest index) than the low yielding one. Results further indicated that genotype improvement efforts have achieved higher grain yield by higher growth rate at early growth stages and better assimilate partitioning to economic yield and short stature plants are unlikely to improve harvest index and resistant to lodging in rice. The mutant, RM-16(N)-10 had medium plant stature with greater biomass production capacity, superiority in growth and biochemical parameters and improve dry matter partitioning to economic yield which resulted higher number of grains panicle-1, thereby grain yield. In contrast, RM-16(N)-8 showed inferiority in morpho-physiological characters and performed the lowest yield attributes and grain yield. This information may be used in future plant breeding programme. Bangladesh J. Nuclear Agric, 37(2): 69-80, 2023

The influence of ontogeny, light environment and species on relationships of relative growth rate (RGR) to physiological and morphological traits were examined for first-year northern hardwood tree seedlings. Three Betulaceae species (Betula papyrifera, Betula alleghaniensis and Ostrya virginiana) were grown in high and low light and Quercus rubra and Acer saccharum were grown only in high light. Plant traits were determined at four ages: 41, 62, 83 and 104 days after germination. In high light (610 μmol m-2 s-1 PPFD), across species and ages, RGR was positively related to the proportion of the plant in leaves (leaf weight ratio, LWR; leaf area ratio, LAR), in situ rates of average canopy net photosynthesis (A) per unit mass (Amass) and per unit area (Aarea), and rates of leaf, stem and root respiration. In low light (127 μmol m-2 s-1 PPFD), RGR was not correlated with Amass and Aarea whereas RGR was positively correlated with LAR, LWR, and rates of root and stem respiration. RGR was negatively correlated with leaf mass per area in both high and low light. Across light levels, relationships of CO2 exchange and morphological characteristics with RGR were generally weaker than within light environments. Moreover, relationships were weaker for plant parameters containing a leaf area component (leaf mass per area, LAR and Aarea), than those that were solely mass-based (respiration rates, LWR and Amass). Across light environments, parameters incorporating the proportion of the plant in leaves and rates of photosynthesis explained a greater amount of variation in RGR (e.g. LWR*Amass, R2=0.64) than did any single parameter related to whole-plant carbon gain. RGR generally declined with age and mass, which were used as scalars of ontogeny. LWR (and LAR) also declined for seven of the eight species-light treatments and A declined in four of the five species in high light. Decreasing LWR and A with ontogeny may have been partially responsible for decreasing RGR. Declines in RGR were not due to increased respiration resulting from an increase in the proportion of solely respiring tissue (roots and stems). In general, although LWR declined with ontogeny, specific rates of leaf, stem, and root respiration also decreased. The net result was that whole-plant respiration rates per unit leaf mass decreased for all eight treatments. Identifying the major determinants of variation in growth (e.g. LWR*Amass) across light environments, species and ontogeny contributes to the establishment of a framework for exploring limits to productivity and the nature of ecological success as measured by growth. The generality of these relationships both across the sources of variation we explored here and across other sources of variation in RGR needs further study.

The responses to increasing salintiy (in the range 0-420 mol m-3 NaCl) of an Australian accession of the halophytic grass, Diplachne fusca, have been studied in two experiments; in terms of growth, water relations, ion uptake and leaf photosynthesis. Twenty-one to 41 days after salinisation, plant dry weight, leaf area and relative growth rate were decreased at salinities at and above 300 mol m-3. Although salinity in the range 0-200 mol m-3 did not significantly affect growth rate, the highest value was at 200 mol m-3. Towards the end of the sampling period, a recovery of leaf growth rates was greater in plants at salinity levels of 90-200 mol m-3. The salt tolerance of this accession is similar to that reported for other populations of this species. As salinity in the root environment was increased, the osmotic potential of the leaf sap (Ψs) and the difference between leaf water potential and Ψs increased progressively with each harvest. There was no evidence that a lack of a capacity to adjust osmotically was related to the observed inhibition of growth at high salinity levels. It was confirmed that D. fusca possessed a C4 mode of leaf photosynthesis: the maximum assimilation rate (A) observed was high (&gt;50 μmol m-2 s-1), the operating intercellular CO2 concentration (Ci) was approximately 140 μmol mol-1, the initial slope of the A v. CI curve ('carboxylation efficiency') was steep (1.24 μmol m-2 s-1) and the optimum leaf temperature for photosynthesis was approximately 45°C. At high salinities leaf conductance (g) was reduced by 78%. Using an analysis of A v. I and A v. CI relationships, the components of the 'photosynthetic capacity' of the mesophyll reduced by high salinity were Amax, carboxylation efficiency and photorespiration rate. There was no consistent relationship, at three salinity levels, between growth rates and Amax and carboxylation efficiency. It appears unlikely, therefore, that the primary inhibitory effects of salinity on growth are attributable to effects on leaf photosynthetic processes.

High temperatures, whether of shoot or root, are reported to affect shoot and root growth of various plant species. The scanty information available on the differential response of wheat genotypes to high shoot and root‐zone temperatures triggered this investigation to study the response and adaptation of shoot and root growth of three wheat genotypes to high shoot and root‐zone temperatures during early growth stages. Three wheat genotypes; Fang (heat tolerant), Siete Cerros (heat sensitive) and Imam (recent cultivar adapted to a hot irrigated environment) were grown in soil and hydroponically. Three shoot/root‐zone temperatures (23/23, 23/35 and 35/35 °C for the soil experiment and 22/22, 22/38 and 38/38 °C for the hydroponic experiment) were applied at three‐leaf growth stage. High root‐zone temperature alone or combined with high shoot temperature reduced xylem sap flow rate, root dry weight, root length and root/shoot ratio. Unexpectedly, shoot fresh and dry weights and relative growth rate (RGR) were not significantly affected by the high root‐zone temperature except for the susceptible genotype, Siete Cerros, after prolonged exposure in the hydroponic experiment. In contrast, high shoot/root‐zone temperature significantly reduced shoot fresh and dry weights from as early as the first week of the hydroponic experiment. The 38/38 °C treatment also caused significant reduction in RGR and net assimilation rate during the first 2 weeks, but no significant differences were found during the last 2 weeks compared with 22/22 °C. Interesting responses were observed among genotypes in terms of shoot and root dry weights and root/shoot ratio at 38/38 °C treatment. The heat‐sensitive Siete Cerros showed the least reduction in these traits during the first 2 weeks while the heat‐tolerant Fang and Imam responded by greatly reducing their shoot and root weights. The situation was almost reversed with the duration of treatments such that Siete Cerros became the most affected genotype while Fang and Imam were better adapted to high shoot/root‐zone temperature. Specific root weight was the exceptional trait that increased under high temperature treatments. Results indicate that despite the reduction in root length and weight observed under high root‐zone temperature, shoot growth was not much affected suggesting that the use of suitable cultivar coupled with proper management could alleviate most of high root‐zone temperature effects during early growth stages.

Spaced plants of soybean (Glycine max (L.) Merrill) cultivars were subjected to classical growth analysis. Varietal differences in mean net assimilation rate (NAR), relative growth rate (RGR), relative leaf growth rate (RLGR), leaf area ratio (LAR), specific leaf weight (SLW), and shoot/root ratio (S/R) were detected within a group of 21 cultivars grown in three tests over 3 years. Only LAR and SLW differed within another group of 23 cultivars grown in 2 years. Comparisons of cultivars with their parents showed that selection for yield had resulted in increased NAR and SLW, and in decreased LAR, S/R, plant weight, and leaf area. Many of the cultivars were transgressive segregants for higher NAR and SLW and for lower LAR. Phenotypic correlations showed that NAR was highly correlated with SLW and inversely correlated with LAR. SLW might be a useful character for indirect selection of soybean yield.

Summary Functional traits contribute to the success of invasive plants. These traits can reflect inherent properties or they can be new adaptations from evolutionary responses to escape from natural enemies of the introduced range. We tested the hypothesis that genetic shifts in morphological and physiological traits have occurred between native and invasive populations of Sapium sebiferum. Sapium sebiferum seedlings were grown in a greenhouse using seed collected from four populations of its introduced range (US) and four from native Chinese populations that are thought to be genetic candidates of the introduced populations. We examined plant biomass production, relative growth rate (RGR), relative stem height growth rate (RHR), root : shoot ratio (RSR), total number of leaves (TLN) and leaf area (TLA), specific leaf area (SLA), leaf area ratio (LAR), net CO2 assimilation (A) and shoot specific respiration rate (RD). US populations of S. sebiferum differed from Chinese populations for most plant variables. Final shoot and total biomass, as well as, RGRs of invasive (US) populations were significantly greater than those of native (Chinese) populations, although RHR and TLN per seedling did not differ between them. Root : shoot ratios (RSR) were significantly lower, while leaf traits including TLA, LAR and SLA were generally greater for invasive populations compared to native populations. Net CO2 A was significantly higher for invasive populations than for native populations, but no significant difference in RD was found between two population types. Of 13 measured plant variables, RSRs, TLA and CO2 A were identified as traits that contributed the most to differences observed between native Chinese and invasive US populations. The suite of morphological and physiological traits functioning together may result in different growth strategies for native versus invasive populations. By virtue of these traits, invasive populations of S. sebiferum may use soil resources and light more efficiently than native populations, which may have given rise to their competitive superiority in the introduced range.