Expression of the Arabidopsis thaliana BBX32 Gene in Soybean Increases Grain Yield

Crop yield is a highly complex quantitative trait. Historically, successful breeding for improved grain yield has led to crop plants with improved source capacity, altered plant architecture, and increased resistance to abiotic and biotic stresses. To date, transgenic approaches towards improving crop grain yield have primarily focused on protecting plants from herbicide, insects, or disease. In contrast, we have focused on identifying genes that, when expressed in soybean, improve the intrinsic ability of the plant to yield more. Through the large scale screening of candidate genes in transgenic soybean, we identified an Arabidopsis thaliana B-box domain gene (AtBBX32) that significantly increases soybean grain yield year after year in multiple transgenic events in multi-location field trials. In order to understand the underlying physiological changes that are associated with increased yield in transgenic soybean, we examined phenotypic differences in two AtBBX32-expressing lines and found increases in plant height and node, flower, pod, and seed number. We propose that these phenotypic changes are likely the result of changes in the timing of reproductive development in transgenic soybean that lead to the increased duration of the pod and seed development period. Consistent with the role of BBX32 in A. thaliana in regulating light signaling, we show that the constitutive expression of AtBBX32 in soybean alters the abundance of a subset of gene transcripts in the early morning hours. In particular, AtBBX32 alters transcript levels of the soybean clock genes GmTOC1 and LHY-CCA1-like2 (GmLCL2). We propose that through the expression of AtBBX32 and modulation of the abundance of circadian clock genes during the transition from dark to light, the timing of critical phases of reproductive development are altered. These findings demonstrate a specific role for AtBBX32 in modulating soybean development, and demonstrate the validity of expressing single genes in crops to deliver increased agricultural productivity

Can uncertainties in sea ice albedo reconcile patterns of data-model discord for the Pliocene and 20th/21st centuries?

General Circulation Model simulations of the mid-Pliocene warm period (mPWP, 3.264 to 3.025 Myr ago) currently underestimate the level of warming that proxy data suggest existed at high latitudes, with discrepancies of up to 11°C for sea surface temperature estimates and 17°C for surface air temperature estimates. Sea ice has a strong influence on high-latitude climates, partly due to the albedo feedback. We present results demonstrating the effects of reductions in minimum sea ice albedo limits in general circulation model simulations of the mPWP. While mean annual surface air temperature increases of up to 6°C are observed in the Arctic, the maximum decrease in model-data discrepancies is just 0.81°C. Mean annual sea surface temperatures increase by up to 2°C, with a maximum model-data discrepancy improvement of 1.31°C. It is also suggested that the simulation of observed 21st century sea ice decline could be influenced by the adjustment of the sea ice albedo parameterization

<i>AtBBX32</i> transgenic soybean plants increase yield components.

<p>Both field and growth chamber grown plants show increases in plant height and pod number in the transgenic lines relative to controls. Node number, flower number, seed number, and 100 seed weight were also increased in growth chamber grown plants. Growth chamber experiments were performed in a 10:14 hour photoperiod (Light∶Dark) with 900 mE of light. Data was collected from ten plant replicates that were randomized among entries in the chamber. Field grown plants were grown under standard agronomic conditions and ambient light. All differences between the transgenic lines and control are significant to p<0.05 unless otherwise indicated as (ns) not significant.</p

<i>AtBBX32</i> transgenic soybean plants demonstrate improved grain yield over non-transgenic controls.

<p>Mean yield values (kilograms per hectare) and percent improvement over controls for transgenic plots are shown for three growing seasons. The difference in the day of flowering (DOF) between the transgenic lines and control was calculated to determine delta DOF. The difference in day of final maturity (MAT) was examined in transgenic lines and compared to control to determine delta MAT (units = days). The low yielding event 4 produced no detectable transcript. N represents the number of environments tested. p-values were based on the difference between the transgenic lines and wildtype control.</p><p>*p≤0.05,</p><p>**p≤0.01.</p

Microarray data from field grown plants.

<p>Microarrays performed on tissue sampled throughout the day from two <i>AtBBX32</i>-expressing lines (lines 1 and 2 from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030717#pone-0030717-t001" target="_blank">Table 1</a>) in the field demonstrate 219 genes show 2–8 fold changes (8-fold is maximum change observed) in abundance in both transgenic events relative to the control and that the majority of these changes occur around ZT 0 (6 am). Dark bar represents genes increased in abundance and light bar represents genes decreased in abundance. All changes significant at a false discovery rate of 5 percent.</p

<i>AtBBX32</i> extends the reproductive period between R3 and R7 developmental stages in soybean resulting in a delay in final maturity compared to control.

<p>The timing of reproductive development was measured according to standard methods <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030717#pone.0030717-Fehr1" target="_blank">[16]</a> in ten field plot replicates for each line. R1 is the initiation of flowering. R3 is the onset of pod development. R7 is the beginning of maturation. R8 is the stage where 95 percent of the pods are physiologically mature. The number of days to reach each developmental stage was calculated on a whole plot basis and the mean is indicated below, where units are days after planting.</p><p>*p<0.05.</p

Expression of <i>AtBBX32</i> in soybean affects the transcript abundance of central clock components near ZT 0.

<p>Levels of both central clock components <i>GmLCL2</i> (A) and <i>GmTOC1</i> (B) were assayed by quantigene RNA extraction and expression analysis from V2 leaf tissue harvested from soybean plants grown in a controlled environment. Growth chamber experiment was performed in a 14:10 hour photoperiod (Light∶Dark) with 650 mE of light. p-values based on the difference between both transgenic lines and wildtype control. * p≤0.05. Where error bars are not visible they are smaller than the data points.</p

<i>AtBBX32</i> expression in soybean delays leaf senescence and brown pod maturity.

<p>A) Field grown soybeans were visually assessed and scored every few days late in the season on a whole plot basis according to green leaf color. Leaf senescence was rated on a 1–9 scale based on whole plot appearance. 9 = dark green, no yellow leaves on the top canopy; 5 = 40 percent change yellow leaves, 10 percent change fallen leaves; 1 = more than 95 percent change fallen leaves. B) The same soybean plots were visually inspected for the appearance of brown pods and the percentage of the plot containing brown pods was determined. * Event 1 significantly different from control at p<0.05, † Event 2 significantly different from control at p≤0.05.</p