High-Throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models.

High-throughput phenotyping serves as a framework to reduce chronological costs and accelerate breeding cycles. In this study, we developed models to estimate the phenotypes of biomass-related traits in soybean (Glycine max) using unmanned aerial vehicle (UAV) remote sensing and deep learning models. In 2018, a field experiment was conducted using 198 soybean germplasm accessions with known whole-genome sequences under 2 irrigation conditions: drought and control. We used a convolutional neural network (CNN) as a model to estimate the phenotypic values of 5 conventional biomass-related traits: dry weight, main stem length, numbers of nodes and branches, and plant height. We utilized manually measured phenotypes of conventional traits along with RGB images and digital surface models from UAV remote sensing to train our CNN models. The accuracy of the developed models was assessed through 10-fold cross-validation, which demonstrated their ability to accurately estimate the phenotypes of all conventional traits simultaneously. Deep learning enabled us to extract features that exhibited strong correlations with the output (i.e., phenotypes of the target traits) and accurately estimate the values of the features from the input data. We considered the extracted low-dimensional features as phenotypes in the latent space and attempted to annotate them based on the phenotypes of conventional traits. Furthermore, we validated whether these low-dimensional latent features were genetically controlled by assessing the accuracy of genomic predictions. The results revealed the potential utility of these low-dimensional latent features in actual breeding scenarios.

Raising root zone temperature improves plant productivity and metabolites in hydroponic lettuce production.

While it is commonly understood that air temperature can greatly affect the process of photosynthesis and the growth of higher plants, the impact of root zone temperature (RZT) on plant growth, metabolism, essential elements, as well as key metabolites like chlorophyll and carotenoids, remains an area that necessitates extensive research. Therefore, this study aimed to investigate the impact of raising the RZT on the growth, metabolites, elements, and proteins of red leaf lettuce. Lettuce was hydroponically grown in a plant factory with artificial light at four different air temperatures (17, 22, 27, and 30°C) and two treatments with different RZTs. The RZT was raised 3°C above the air temperature in one group, while it was not in the other group. Increasing the RZT 3°C above the air temperature improved plant growth and metabolites, including carotenoids, ascorbic acids, and chlorophyll, in all four air temperature treatments. Moreover, raising the RZT increased Mg, K, Fe, Cu, Se, Rb, amino acids, and total soluble proteins in the leaf tissue at all four air temperatures. These results showed that raising the RZT by 3°C improved plant productivity and the metabolites of the hydroponic lettuce by enhancing nutrient uptake and activating the metabolism in the roots at all four air temperatures. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology.

Reaction norm for genomic prediction of plant growth: modeling drought stress response in soybean.

KEY MESSAGE: We proposed models to predict the effects of genomic and environmental factors on daily soybean growth and applied them to soybean growth data obtained with unmanned aerial vehicles. Advances in high-throughput phenotyping technology have made it possible to obtain time-series plant growth data in field trials, enabling genotype-by-environment interaction (G × E) modeling of plant growth. Although the reaction norm is an effective method for quantitatively evaluating G × E and has been implemented in genomic prediction models, no reaction norm models have been applied to plant growth data. Here, we propose a novel reaction norm model for plant growth using spline and random forest models, in which daily growth is explained by environmental factors one day prior. The proposed model was applied to soybean canopy area and height to evaluate the influence of drought stress levels. Changes in the canopy area and height of 198 cultivars were measured by remote sensing using unmanned aerial vehicles. Multiple drought stress levels were set as treatments, and their time-series soil moisture was measured. The models were evaluated using three cross-validation schemes. Although accuracy of the proposed models did not surpass that of single-trait genomic prediction, the results suggest that our model can capture G × E, especially the latter growth period for the random forest model. Also, significant variations in the G × E of the canopy height during the early growth period were visualized using the spline model. This result indicates the effectiveness of the proposed models on plant growth data and the possibility of revealing G × E in various growth stages in plant breeding by applying statistical or machine learning models to time-series phenotype data.

Transcriptome Analysis of Rice Root Tips Reveals Auxin, Gibberellin and Ethylene Signaling Underlying Nutritropism.

Nutritropism is a positive tropism toward nutrients in plant roots. An NH4+ gradient is a nutritropic stimulus in rice (Oryza sativa L.). When rice roots are exposed to an NH4+ gradient generated around nutrient sources, root tips bend toward and coil around the sources. The molecular mechanisms are largely unknown. Here, we analyzed the transcriptomes of the inside and outside of bending root tips exhibiting nutritropism to reveal nutritropic signal transduction. Tissues facing the nutrient sources (inside) and away (outside) were separately collected by laser microdissection. Principal component analysis revealed distinct transcriptome patterns between the two tissues. Annotations of 153 differentially expressed genes implied that auxin, gibberellin and ethylene signaling were activated differentially between the sides of the root tips under nutritropism. Exogenous application of transport and/or biosynthesis inhibitors of these phytohormones largely inhibited the nutritropism. Thus, signaling and de novo biosynthesis of the three phytohormones are necessary for nutritropism. Expression patterns of IAA genes implied that auxins accumulated more in the inside tissues, meaning that ammonium stimulus is transduced to auxin signaling in nutritropism similar to gravity stimulus in gravitropism. SAUR and expansin genes, which are known to control cell wall modification and to promote cell elongation in shoot gravitropism, were highly expressed in the inside tissues rather than the outside tissues, and our transcriptome data are unexplainable for differential elongation in root nutritropism.

OsbZIP1 regulates phosphorus uptake and nitrogen utilization, contributing to improved yield.

Increasing nutrient uptake and use efficiency in plants can contribute to improved crop yields and reduce the demand for fertilizers in crop production. In this study, we characterized a rice mutant, 88n which showed long roots under low nitrogen (N) or phosphorus (P) conditions. Low expression levels of N transporter genes were observed in 88n root, and total N concentration in 88n shoots were decreased, however, C concentrations and shoot dry weight in 88n were comparable to that in WT. Therefore, 88n showed high nitrogen utilization efficiency (NUtE). mRNA accumulation of Pi transporter genes was higher in 88n roots, and Pi concentration and uptake activity were higher in 88n than in WT. Therefore, 88n also showed high phosphorus uptake efficiency (PUpE). Molecular genetic analysis revealed that the causal gene of 88n phenotypes was OsbZIP1, a monocot-specific ortholog of the A. thaliana bZIP transcription factor HY5. Similar to the hy5 mutant, chlorophyll content in roots was decreased and root angle was shallower in 88n than in WT. Finally, we tested the yield of 88n in paddy fields over 3 years because 88n mutant plants showed higher PUpE and NUtE activity and different root architecture at the seedling stage. 88n showed large panicles and increased panicle weight/plant. Taken together, a mutation in OsbZIP1 could contribute to improved crop yields.

Controlling root zone temperature improves plant growth and pigments in hydroponic lettuce.

BACKGROUND AND AIMS: Air and root zone temperatures are important environmental factors affecting plant growth and yield. Numerous studies have demonstrated that air temperature strongly affects plant growth and development. Despite the extensive literature on air temperature, comprehensive studies on the effects of root zone temperature (RZT) on plant growth, elemental composition, and pigments are limited. In this study, we carefully observed the effects of RZT in red leaf lettuce to understand its effect on lettuce growth and pigment content. METHODS: Lettuce (Lactuca sativa, red leaf cultivar 'Red Fire') was grown hydroponically in a plant factory with artificial light under three RZT treatments (15, 25, or 35 °C) for 13 days. We investigated the comprehensive effects of RZT on the production of red leaf lettuce by metabolome and ionome analyses. KEY RESULTS: The 25 °C RZT treatment achieved maximum shoot and root dry weight. The 35 °C RZT decreased plant growth but significantly increased pigment contents (e.g. anthocyanins, carotenoids). In addition, a RZT heating treatment during plant cultivation that changed from 25 to 35 °C RZT for 8 days before harvest significantly increased shoot dry weight compared with the 35 °C RZT and significantly increased pigments compared with the 25 °C RZT. The 15 °C RZT resulted in significantly less pigment content relative to the 35 °C RZT. The 15 °C RZT also resulted in shoot and root dry weights greater than the 35 °C RZT but less than the 25 °C RZT. CONCLUSIONS: This study demonstrated that plant growth and pigments can be enhanced by adjusting RZT during different stages of plant growth to attain enhanced pigment contents while minimizing yield loss. This suggests that controlling RZT could be a viable method to improve lettuce quality via enhancement of pigment content quality while maintaining acceptable yields.

A fungal sesquiterpene biosynthesis gene cluster critical for mutualist-pathogen transition in Colletotrichum tofieldiae.

Plant-associated fungi show diverse lifestyles from pathogenic to mutualistic to the host; however, the principles and mechanisms through which they shift the lifestyles require elucidation. The root fungus Colletotrichum tofieldiae (Ct) promotes Arabidopsis thaliana growth under phosphate limiting conditions. Here we describe a Ct strain, designated Ct3, that severely inhibits plant growth. Ct3 pathogenesis occurs through activation of host abscisic acid pathways via a fungal secondary metabolism gene cluster related to the biosynthesis of sesquiterpene metabolites, including botrydial. Cluster activation during root infection suppresses host nutrient uptake-related genes and changes mineral contents, suggesting a role in manipulating host nutrition state. Conversely, disruption or environmental suppression of the cluster renders Ct3 beneficial for plant growth, in a manner dependent on host phosphate starvation response regulators. Our findings indicate that a fungal metabolism cluster provides a means by which infectious fungi modulate lifestyles along the parasitic-mutualistic continuum in fluctuating environments.

Random regression for modeling soybean plant response to irrigation changes using time-series multispectral data.

Plant response to drought is an important yield-related trait under abiotic stress, but the method for measuring and modeling plant responses in a time series has not been fully established. The objective of this study was to develop a method to measure and model plant response to irrigation changes using time-series multispectral (MS) data. We evaluated 178 soybean (Glycine max (L.) Merr.) accessions under three irrigation treatments at the Arid Land Research Center, Tottori University, Japan in 2019, 2020 and 2021. The irrigation treatments included W5: watering for 5 d followed by no watering 5 d, W10: watering for 10 d followed by no watering 10 d, D10: no watering for 10 d followed by watering 10 d, and D: no watering. To capture the plant responses to irrigation changes, time-series MS data were collected by unmanned aerial vehicle during the irrigation/non-irrigation switch of each irrigation treatment. We built a random regression model (RRM) for each of combination of treatment by year using the time-series MS data. To test the accuracy of the information captured by RRM, we evaluated the coefficient of variation (CV) of fresh shoot weight of all accessions under a total of nine different drought conditions as an indicator of plant's stability under drought stresses. We built a genomic prediction model (MTRRM model) using the genetic random regression coefficients of RRM as secondary traits and evaluated the accuracy of each model for predicting CV. In 2020 and 2021,the mean prediction accuracies of MTRRM models built in the changing irrigation treatments (r = 0.44 and 0.49, respectively) were higher than that in the continuous drought treatment (r = 0.34 and 0.44, respectively) in the same year. When the CV was predicted using the MTRRM model across 2020 and 2021 in the changing irrigation treatment, the mean prediction accuracy (r = 0.46) was 42% higher than that of the simple genomic prediction model (r =0.32). The results suggest that this RRM method using the time-series MS data can effectively capture the genetic variation of plant response to drought.

Differential Anti-Tumor Effects of IFN-Inducible Chemokines CXCL9, CXCL10, and CXCL11 on a Mouse Squamous Cell Carcinoma Cell Line.

Chemokines are a group of cytokines involved in the mobilization of leukocytes, which play a role in host defense and a variety of pathological conditions, including cancer. Interferon (IFN)-inducible chemokines C-X-C motif ligand 9 (CXCL), CXCL10, and CXCL11 are anti-tumor chemokines; however, the differential anti-tumor effects of IFN-inducible chemokines are not completely understood. In this study, we investigated the anti-tumor effects of IFN-inducible chemokines by transferring chemokine expression vectors into a mouse squamous cell carcinoma cell line, SCCVII, to generate a cell line stably expressing chemokines and transplanted it into nude mice. The results showed that CXCL9- and CXCL11-expressing cells markedly inhibited tumor growth, whereas CXCL10-expressing cells did not inhibit growth. The NH2-terminal amino acid sequence of mouse CXCL10 contains a cleavage sequence by dipeptidyl peptidase 4 (DPP4), an enzyme that cleaves the peptide chain of chemokines. IHC staining indicated DPP4 expression in the stromal tissue, suggesting CXCL10 inactivation. These results suggest that the anti-tumor effects of IFN-inducible chemokines are affected by the expression of chemokine-cleaving enzymes in tumor tissues.

Time-series multispectral imaging in soybean for improving biomass and genomic prediction accuracy.

Multispectral (MS) imaging enables the measurement of characteristics important for increasing the prediction accuracy of genotypic and phenotypic values for yield-related traits. In this study, we evaluated the potential application of temporal MS imaging for the prediction of aboveground biomass (AGB) in soybean [Glycine max (L.) Merr.]. Field experiments with 198 accessions of soybean were conducted with four different irrigation levels. Five vegetation indices (VIs) were calculated using MS images from soybean canopies from early vegetative to early reproductive stage. To predict the genotypic values of AGB, VIs at the different growth stages were used as secondary traits in a multitrait genomic prediction. The prediction accuracy of the genotypic values of AGB from MS and genomic data largely outperformed that of the genomic data alone before the flowering stage (90% of accessions did not flower), suggesting that it would be possible to determine cross-combinations based on the predicted genotypic values of AGB. We compared the prediction accuracy of a model using the five VIs and a model using only one VI to predict the phenotypic values of AGB and found that the difference in prediction accuracy decreased over time at all irrigation levels except for the most severe drought. The difference in the most severe drought was not as small as that in the other treatments. Only the prediction accuracy of a model using the five VIs in the most severe droughts gradually increased over time. Therefore, the optimal timing for MS imaging may depend on the irrigation levels.

A Koshihikari X Oryza rufipogon Introgression Line with a High Capacity to Take up Nitrogen to Maintain Growth and Panicle Development under Low Nitrogen Conditions.

Nitrogen (N) is an important macronutrient for plant growth and development. Currently, N fertilizers are required for the efficient production of modern crops such as rice due to their limited capacity to take up N when present at low concentrations. Wild rice represents a useful genetic resource for improving crop responses to low nutrient stress. Here, we describe the isolation and characterization of an introgression line, KRIL37, that carries a small region of the Oryza rufipogon genome in the Oryza sativa L. cv Koshihikari (KH) background. This line was found to grow better under low N conditions and have similar or lower C/N ratios in aerial portions compared to those in the parental KH cultivar, suggesting that KRIL37 has a higher capacity to take up and assimilate N when present at low concentrations. KRIL37 performance in the field was also better than that of KH cultivated without N and fertilizer (-F). Transcriptome analyses of 3-week-old seedlings based on RNA-sequencing revealed that KH induced a wider suite of genes than the tolerant line KRIL37 in response to low N conditions. Some ammonium transporters and N assimilation genes were found to be induced under low N in KRIL37, but not in KH. Our findings suggest that the superior growth performance of KRIL37 under limited N conditions could be due to the expression of wild alleles influencing N uptake and assimilation. Our study demonstrates the potential to use wild rice genomes to improve modern crops for low nutrient tolerance.

Genomic Prediction of Green Fraction Dynamics in Soybean Using Unmanned Aerial Vehicles Observations.

With the widespread use of high-throughput phenotyping systems, growth process data are expected to become more easily available. By applying genomic prediction to growth data, it will be possible to predict the growth of untested genotypes. Predicting the growth process will be useful for crop breeding, as variability in the growth process has a significant impact on the management of plant cultivation. However, the integration of growth modeling and genomic prediction has yet to be studied in depth. In this study, we implemented new prediction models to propose a novel growth prediction scheme. Phenotype data of 198 soybean germplasm genotypes were acquired for 3 years in experimental fields in Tottori, Japan. The longitudinal changes in the green fractions were measured using UAV remote sensing. Then, a dynamic model was fitted to the green fraction to extract the dynamic characteristics of the green fraction as five parameters. Using the estimated growth parameters, we developed models for genomic prediction of the growth process and tested whether the inclusion of the dynamic model contributed to better prediction of growth. Our proposed models consist of two steps: first, predicting the parameters of the dynamics model with genomic prediction, and then substituting the predicted values for the parameters of the dynamics model. By evaluating the heritability of the growth parameters, the dynamic model was able to effectively extract genetic diversity in the growth characteristics of the green fraction. In addition, the proposed prediction model showed higher prediction accuracy than conventional genomic prediction models, especially when the future growth of the test population is a prediction target given the observed values in the first half of growth as training data. This indicates that our model was able to successfully combine information from the early growth period with phenotypic data from the training population for prediction. This prediction method could be applied to selection at an early growth stage in crop breeding, and could reduce the cost and time of field trials.

Enhanced Cytotoxic Effects in Human Oral Squamous Cell Carcinoma Cells Treated with Combined Methyltransferase Inhibitors and Histone Deacetylase Inhibitors.

Combined treatment of human oral squamous cell carcinoma (OSCCs) with DNA methyltransferase inhibitors (DNMTis), histone methyltransferase inhibitors (HMTis), and histone deacetylase inhibitors (HDACis), and the molecular mechanisms underlying their anticancer effects, have not been fully elucidated. Herein, we investigated the cytotoxic effects of combined DNMTis (5-Aza-deoxycytidine: 5-Aza-dC, RG108), HMTis (3-deazaneplanocin A: DZNep), and HDACis (trichostatin A: TSA) treatment on human OSCC cells and explored their molecular mechanisms. Combined 5-Aza-dC, or RG108, and TSA treatment significantly decreased HSC-2 and Ca9-22 cell viability. Combinatorial DZNep and TSA treatment also decreased Ca9-22 cell viability. Although caspase 3/7 activation was not observed in HSC-2 cells following combined treatment, caspase activity was significantly increased in Ca9-22 cells treated with DZNep and TSA. Moreover, combined treatment with 5-Aza-dC, RG108, and TSA increased the proportion of HSC-2 and Ca9-22 cells in the S and G2/M phases. Meanwhile, increased phosphorylation of the histone variant H2A.X, a marker of double-stranded DNA breaks, was observed in both cells after combination treatment. Hence, the decreased viability induced by combined treatment with epigenomic inhibitors results from apoptosis and cell cycle arrest in S and G2/M phases. Thus, epigenomic therapy comprising combined low concentrations of DNMTi, HMTi, and HDACi is effective against OSCC.

Simultaneous Expression of Th1- and Treg-Associated Chemokine Genes and CD4+, CD8+, and Foxp3+ Cells in the Premalignant Lesions of 4NQO-Induced Mouse Tongue Tumorigenesis.

Chemokines and cytokines in the tumor microenvironment influence immune cell infiltration and activation. To elucidate their role in immune cell recruitment during oral cancer development, we generated a mouse tongue cancer model using the carcinogen 4-nitroquinoline 1-oxide (4NQO) and investigated the carcinogenetic process and chemokine/cytokine gene expression kinetics in the mouse tongue. C57/BL6 mice were administered 4NQO in drinking water, after which tongues were dissected at 16 and 28 weeks and subjected to analysis using the RT2 Profiler PCR Array, qRT-PCR, and pathologic and immunohistochemical analyses. We found that Th1-associated chemokine/cytokine (Cxcl9, Cxcl10, Ccl5, and Ifng) and Treg-associated chemokine/cytokine (Ccl17, Ccl22, and Il10) mRNA levels were simultaneously increased in premalignant lesions of 4NQO-treated mice at 16 weeks. Additionally, although levels of Gata3, a Th2 marker, were not upregulated, those of Cxcr3, Ccr4, and Foxp3 were upregulated in the tongue tissue. Furthermore, immunohistochemical analysis confirmed the infiltration of CD4+, CD8+, and Foxp3+ cells in the tongue tissue of 4NQO-treated mice, as well as significant correlations between Th1- or Treg-associated chemokine/cytokine mRNA expression and T cell infiltration. These results indicate that CD4+, CD8+, and Foxp3+ cells were simultaneously recruited through the expression of Th1- and Treg-associated chemokines in premalignant lesions of 4NQO-induced mouse tongue tissue.

Growth and Nitrate Reductase Activity Are Impaired in Rice Osnlp4 Mutants Supplied with Nitrate.

Nitrate is an important nutrient and signaling molecule in plants, which modulates the expression of many genes and regulates plant growth. In paddy-grown rice (Oryza sativa), nitrogen is mostly supplied in the form of ammonium but can also be supplied in the form of nitrate. Several nitrogen transporters and nitrate assimilation enzymes have been identified and functionally characterized in rice. However, little is known regarding the nitrate sensing system in rice, and the regulatory mechanisms of nitrate-related genes remain to be elucidated. In recent years, NIN-like proteins (NLPs) have been described as key transcription factors of nitrogen responses in Arabidopsis thaliana, which implies that OsNLP4 is involved in the regulation of nitrate assimilation and nitrogen use efficiency in rice. Here, we show that OsNLP4 can influence plant growth by affecting nitrate reductase (NR) activity. The growth of OsNLP4 knockdown mutants was reduced when nitrate was supplied, but not when ammonium was supplied. The nitrate concentration was significantly reduced in osnlp4 mutants. Furthermore, the concentrations of iron and molybdenum, essential elements for NR activity, were reduced in OsNLP4 knockdown mutants. We propose that, in addition to the regulation of gene expression within the nitrate signaling pathway, OsNLP4 can affect the NR activity and nitrate-dependent growth of rice. Our results support a working model for the role of OsNLP4 in the nitrate signaling pathway.

CURLED LATER1 encoding the largest subunit of the Elongator complex has a unique role in leaf development and meristem function in rice.

The Elongator complex, which is conserved in eukaryotes, has multiple roles in diverse organisms. In Arabidopsis thaliana, Elongator is shown to be involved in development, hormone action and environmental responses. However, except for Arabidopsis, our knowledge of its function is poor in plants. In this study, we initially carried out a genetic analysis to characterize a rice mutant with narrow and curled leaves, termed curled later1 (cur1). The cur1 mutant displayed a heteroblastic change, whereby the mutant leaf phenotype appeared specifically at a later adult phase of vegetative development. The shoot apical meristem (SAM) was small and the leaf initiation rate was low, suggesting that the activity of the SAM seemed to be partially reduced in cur1. We then revealed that CUR1 encodes a yeast ELP1-like protein, the largest subunit of Elongator. Furthermore, disruption of OsELP3 encoding the catalytic subunit of Elongator resulted in phenotypes similar to those of cur1, including the timing of the appearance of mutant phenotypes. Thus, Elongator activity seems to be specifically required for leaf development at the late vegetative phase. Transcriptome analysis showed that genes involved in protein quality control were highly upregulated in the cur1 shoot apex at the later vegetative phase, suggesting the restoration of impaired proteins probably produced by partial defects in translational control due to the loss of function of Elongator. The differences in the mutant phenotype and gene expression profile between CUR1 and its Arabidopsis ortholog suggest that Elongator has evolved to play a unique role in rice development.

A Positive Tropism of Rice Roots toward a Nutrient Source.

Plants take up water and nutrients through roots, and uptake efficiency depends on root behavior. Roots recognize the moisture gradient in the soil and grow toward the direction of high moisture. This phenomenon is called hydrotropism, and it contributes to efficient water uptake. As nutrients in soil are also unevenly distributed, it is beneficial for plants to grow their roots in the direction of increasing nutrient concentrations, but such a phenomenon has not been demonstrated. Here, we describe the directional growth of roots in response to a nutrient gradient. Using our assay system, the gradient of a nitrogen nutrient, NH4+, was sufficient to stimulate positive tropic responses of rice lateral roots. This phenomenon is a tropism of plant roots to nutrients; hence, we propose the name 'nutritropism'. As well as other tropisms, differential cell elongation was observed before the elongation zone during nutritropism, but the pattern promoting cell elongation preferentially on the non-stimulated side was opposite to those in root hydrotropism and gravitropism. Our evaluation of the NH4+ gradient suggested that the root tips responded to a sub-micromolar difference in NH4+ concentration on both sides of the root. Hydrotropism, gravitropism and phototropism were described in plants as the 'power of movement' by Charles and Francis Darwin in 1880, and these three tropisms have attracted the attention of plant scientists for more than 130 years. Our discovery of nutritropism represents the fourth 'power of movement' in plants and provides a novel root behavioral property used by plants to acquire nutrients efficiently.

DWARF WITH SLENDER LEAF1 Encoding a Histone Deacetylase Plays Diverse Roles in Rice Development.

In plants, reversible histone acetylation and deacetylation play a crucial role in various biological activities, including development and the response to environmental stress. Histone deacetylation, which is generally associated with gene silencing, is catalyzed by multiple histone deacetylases (HDACs). Our understanding of HDAC function in plant development has accumulated from molecular genetic studies in Arabidopsis thaliana. By contrast, how HDACs contribute to the development of rice (Oryza sativa) is poorly understood and no rice mutants of HDAC have been reported. Here we have characterized a new rice mutant showing semi-dwarfism, which we named dwarf with slender leaf1 (dsl1). The mutant showed pleiotropic defects in both vegetative and reproductive developments; e.g. dsl1 produced short and narrow leaves, accompanied by a reduction in the number and size of vascular bundles. The semi-dwarf phenotype was due to suppression of the elongation of some culm (stem) internodes. Interestingly, despite this suppression of the upper internodes, the elongation and generation of lower internodes were slightly enhanced. Inflorescence and spikelet development were also affected by the dsl1 mutation. Some of the observed morphological defects were related to a reduction in cell numbers, in addition to reduced cell division in leaf primordia revealed by in situ hybridization analysis, suggesting the possibility that DSL1 is involved in cell division control. Gene cloning revealed that DSL1 encodes an HDAC belonging to the reduced potassium dependence3/histone deacetylase1 family. Collectively, our study shows that the HDAC DSL1 plays diverse and important roles in development in rice.

Silencing of the interferon-inducible gene Ifi204/p204 induces resistance to interferon-γ-mediated cell growth arrest of tumor cells.

Many tumor cells escape from cancer immunosurveillance and resist treatment with interferons (IFNs). Although the mechanism underlying IFN resistance is mostly attributed to a deficiency of components of the IFN-signaling pathway, some types of tumor cells resist IFN-mediated cell growth arrest despite the presence of an intact JAK/STAT signaling pathway. However, the molecular mechanisms underlying the unresponsiveness to IFNs independent of the defective JAK/STAT pathway remain to be clarified. To elucidate the mechanisms underlying IFNγ resistance, we examined the anti-proliferative effect of IFNγ on mouse tumor cell lines. Mouse squamous cell carcinoma (SCCVII) cells were resistant to IFNγ-mediated cell growth arrest despite the presence of the IFNγ-induced STAT1-dependent signaling pathway, whereas IFNγ inhibited cell growth of B16/F1 cells, a well-known IFNγ-sensitive mouse melanoma cell line, at the G1 phase of the cell cycle. Treatment of SCCVII cells with IFNγ neither downregulated the expression of cyclin D1, cyclin A2, and cyclin E1 nor induced a hypo-phosphorylated, active form of retinoblastoma protein (pRb). Interestingly, the hyper-phosphorylated, inactive form of pRb was exclusively localized in the cytoplasm in SCCVII cells. The IFN-inducible 204 gene (Ifi204), whose gene product, p204, binds to pRb and exerts an anti-proliferative effect, was repressed in SCCVII cells. p204 overexpression in SCCVII significantly inhibited cell growth, and mutation of a pRb-binding LXCXE motif decreased the anti-proliferative effect. These results suggest that silencing of Ifi204/p204 induces resistance to IFNγ-mediated cell growth arrest in SCCVII cells.