Bettina Berger

High-throughput shoot imaging to study drought responses

Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic studies of drought are particularly difficult. Elucidation of the genetic basis of components contributing to drought tolerance is likely to be more tractable than that of overall drought tolerance. Certain of the traits which contribute to drought tolerance in plants and the high-throughput phenotyping techniques available to measure those traits are described in this paper. On the basis of the dynamic nature of drought, plant development, and the resulting stress response, the focus is on non-destructive imaging techniques which allow a temporal resolution and monitoring of the same plants throughout the experiment. Information on the physiological changes in response to drought over time is vital in order to identify and characterize different drought-tolerance mechanisms. High-throughput imaging provides a valuable new tool which allows the dissection of plant responses to drought into a series of component traits.

Accurate inference of shoot biomass from high-throughput images of cereal plants

With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model). For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM) for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent set of barley data. The technique presented in this paper may extend to other plants and types of stresses.

High-Throughput Phenotyping to Detect Drought Tolerance QTL in Wild Barley Introgression Lines

Drought is one of the most severe stresses, endangering crop yields worldwide. In order to select drought tolerant genotypes, access to exotic germplasm and efficient phenotyping protocols are needed. In this study the high-throughput phenotyping platform “The Plant Accelerator”, Adelaide, Australia, was used to screen a set of 47 juvenile (six week old) wild barley introgression lines (S42ILs) for drought stress responses. The kinetics of growth development was evaluated under early drought stress and well watered treatments. High correlation (r = 0.98) between image based biomass estimates and actual biomass was demonstrated, and the suitability of the system to accurately and non-destructively estimate biomass was validated. Subsequently, quantitative trait loci (QTL) were located, which contributed to the genetic control of growth under drought stress. In total, 44 QTL for eleven out of 14 investigated traits were mapped, which for example controlled growth rate and water use efficiency. The correspondence of those QTL with QTL previously identified in field trials is shown. For instance, six out of eight QTL controlling plant height were also found in previous field and glasshouse studies with the same introgression lines. This indicates that phenotyping juvenile plants may assist in predicting adult plant performance. In addition, favorable wild barley alleles for growth and biomass parameters were detected, for instance, a QTL that increased biomass by approximately 36%. In particular, introgression line S42IL-121 revealed improved growth under drought stress compared to the control Scarlett. The introgression line showed a similar behavior in previous field experiments, indicating that S42IL-121 may be an attractive donor for breeding of drought tolerant barley cultivars.

Investigating glutamate receptor-like gene co-expression in Arabidopsis thaliana

There is increasing evidence of the important roles of glutamate receptors (GLRs) in plant development and in adaptation to stresses. However, the studies of these putative ion channels, both in planta and in Xenopus oocytes, may have been limited by our lack of knowledge of possible GLR heteromer formation in plants. We have developed a modification of the single-cell sampling technique to investigate GLR co-expression, and thus potential heteromer formation, in single cells of Arabidopsis thaliana leaves. Micro-EXpression amplification (MEX) has allowed us to amplify gene transcripts from a single cell, enabling expression of up to 100 gene transcripts to be assayed. We measured, on average, the transcripts of five to six different AtGLRs in a single cell. However, no consistent patterns of co-expression or cell-type-specific expression were detected, except that cells sampled from the same plant showed similar expression profiles. The only discernible feature was the detection of AtGLR3.7 in every cell examined, an observation supported by GUS staining patterns in plants stably expressing promoter::uidA fusions. In addition, we found AtGLR3.7 expression in oocytes induces a Ba2+-, Ca2+- and Na+-permeable plasma membrane conductance.

Specific and coordinated control of indolic and aliphatic glucosinolate biosynthesis by R2R3-MYB transcription factors in Arabidopsis thaliana

Five members of subgroup 12 R2R3-MYB transcription factors, namely MYB51, MYB122, MYB28, MYB29 and MYB76, are novel regulators of glucosinolate biosynthesis in Arabidopsis thaliana. Overexpression of MYB51 and MYB122 led to an increased accumulation of tryptophan-derived indolic glucosinolates whereas MYB28, MYB29 and MYB76 overexpression lines showed an increase in methionine-derived aliphatic glucosinolates. Likewise, disruption of the corresponding genes caused a significant downregulation of indolic and aliphatic glucosinolates, respectively. Expression analysis of promoter-GUS fusions revealed promoter activities at the sites of glucosinolate synthesis and accumulation. Indolic glucosinolate regulators were mainly found in vegetative organs and roots, whereas aliphatic glucosinolate regulators were preferentially expressed in generative organs. Mechanical stimuli such as touch or wounding induced a transient expression of the regulators and overexpression of MYB28 and MYB51 reduced insect performance demonstrating the role of these transcription factors in plant biotic responses. The subgroup 12 R2R3-MYB transcription factors interdependently control the response to biotic challenges. For the regulation of methionine-derived glucosinolates, the coordinated activation of MYB28, MYB76 and MYB29 is required, whereas MYB51, MYB122 and the sixth member of subgroup 12 R2R3-MYB transcription factors, the previously described ATR1/MYB34, are involved in the regulation of tryptophan-derived glucosinolates. Because these two pathways are reciprocally inhibiting each other, a metabolic balance between both biosynthetic pathways can be accomplished in plants exposed to continuous biotic challenges.

Expression of the Arabidopsis vacuolar H⁺-pyrophosphatase gene (AVP1) improves the shoot biomass of transgenic barley and increases grain yield in a saline field

Cereal varieties with improved salinity tolerance are needed to achieve profitable grain yields in saline soils. The expression of AVP1, an Arabidopsis gene encoding a vacuolar proton pumping pyrophosphatase (H⁺-PPase), has been shown to improve the salinity tolerance of transgenic plants in greenhouse conditions. However, the potential for this gene to improve the grain yield of cereal crops in a saline field has yet to be evaluated. Recent advances in high-throughput nondestructive phenotyping technologies also offer an opportunity to quantitatively evaluate the growth of transgenic plants under abiotic stress through time. In this study, the growth of transgenic barley expressing AVP1 was evaluated under saline conditions in a pot experiment using nondestructive plant imaging and in a saline field trial. Greenhouse-grown transgenic barley expressing AVP1 produced a larger shoot biomass compared to null segregants, as determined by an increase in projected shoot area, when grown in soil with 150 mM NaCl. This increase in shoot biomass of transgenic AVP1 barley occurred from an early growth stage and also in nonsaline conditions. In a saline field, the transgenic barley expressing AVP1 also showed an increase in shoot biomass and, importantly, produced a greater grain yield per plant compared to wild-type plants. Interestingly, the expression of AVP1 did not alter barley leaf sodium concentrations in either greenhouse- or field-grown plants. This study validates our greenhouse-based experiments and indicates that transgenic barley expressing AVP1 is a promising option for increasing cereal crop productivity in saline fields.

Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time

Highlight A high-throughput imaging system was used to compare growth and architectural traits of sorghum grown under different environmental conditions, and validated against traditional measures of plant performance and composition.

Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice

The genetic basis of dynamic salinity stress responses is elucidated using image-based phenomics and functional association analysis. Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.

bHLH05 Is an Interaction Partner of MYB51 and a Novel Regulator of Glucosinolate Biosynthesis in Arabidopsis

Protein-protein interaction studies of R2R3 MYB transcription factors regulating glucosinolate biosynthesis and the analysis of multiple loss-of-function mutants and gain-of-function alleles demonstrated the specific role of an associated transcription factor complex in the transcriptional regulation of glucosinolate biosynthesis. By means of yeast (Saccharomyces cerevisiae) two-hybrid screening, we identified basic helix-loop-helix transcription factor05 (bHLH05) as an interacting partner of MYB51, the key regulator of indolic glucosinolates (GSLs) in Arabidopsis (Arabidopsis thaliana). Furthermore, we show that bHLH04, bHLH05, and bHLH06/MYC2 also interact with other R2R3-MYBs regulating GSL biosynthesis. Analysis of bhlh loss-of-function mutants revealed that the single bhlh mutants retained GSL levels that were similar to those in wild-type plants, whereas the triple bhlh04/05/06 mutant was depleted in the production of GSL. Unlike bhlh04/06 and bhlh05/06 mutants, the double bhlh04/05 mutant was strongly affected in the production of GSL, pointing to a special role of bHLH04 and bHLH05 in the control of GSL levels in the absence of jasmonic acid. The combination of two specific gain-of-function alleles of MYB and bHLH proteins had an additive effect on GSL levels, as demonstrated by the analysis of the double MYB34-1D bHLH05D94N mutant, which produces 20-fold more indolic GSLs than bHLH05D94N and ecotype Columbia-0 of Arabidopsis. The amino acid substitution D94N in bHLH05D94N negatively affects the interaction with JASMONATE-ZIM DOMAIN protein, thereby resulting in constitutive activation of bHLH05 and mimicking jasmonic acid treatment. Our study revealed the bHLH04, bHLH05, and bHLH06/MYC2 factors as novel regulators of GSL biosynthesis in Arabidopsis.

Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping

High-throughput phenotyping produces multiple measurements over time, which require new methods of analyses that are flexible in their quantification of plant growth and transpiration, yet are computationally economic. Here we develop such analyses and apply this to a rice population genotyped with a 700k SNP high-density array. Two rice diversity panels, indica and aus, containing a total of 553 genotypes, are phenotyped in waterlogged conditions. Using cubic smoothing splines to estimate plant growth and transpiration, we identify four time intervals that characterize the early responses of rice to salinity. Relative growth rate, transpiration rate and transpiration use efficiency (TUE) are analysed using a new association model that takes into account the interaction between treatment (control and salt) and genetic marker. This model allows the identification of previously undetected loci affecting TUE on chromosome 11, providing insights into the early responses of rice to salinity, in particular into the effects of salinity on plant growth and transpiration.