Publications by authors named "Haifu Tu"

Drought and heat are major abiotic stresses frequently coinciding to threaten rice production. Despite hundreds of stress-related genes being identified, only a few have been confirmed to confer resistance to multiple stresses in crops. Here we report ONAC023, a hub stress regulator that integrates the regulations of both drought and heat tolerance in rice.

View Article and Find Full Text PDF

Drought stress significantly impacts global rice production, highlighting the critical need to understand the genetic basis of drought resistance in rice. Here, through a genome-wide association study, we reveal that natural variations in DROUGHT RESISTANCE GENE 9 (DRG9), encoding a double-stranded RNA (dsRNA) binding protein, contribute to drought resistance. Under drought stress, DRG9 condenses into stress granules (SGs) through liquid-liquid phase separation via a crucial α-helix.

View Article and Find Full Text PDF

NARROW LEAF 1 (NAL1) is a breeding-valuable pleiotropic gene that affects multiple agronomic traits in rice, although the molecular mechanism is largely unclear. Here, we report that NAL1 is a serine protease and displays a novel hexameric structure consisting of two ATP-mediated doughnut-shaped trimeric complexes. Moreover, we identified TOPLESS-related corepressor OsTPR2 involved in multiple growth and development processes as the substrate of NAL1.

View Article and Find Full Text PDF

In plants, cortical microtubules anchor to the plasma membrane in arrays and play important roles in cell shape. However, the molecular mechanism of microtubule binding proteins, which connect the plasma membrane and cortical microtubules in cell morphology remains largely unknown. Here, we report that a plasma membrane and microtubule dual-localized IQ67 domain protein, IQD21, is critical for cotyledon pavement cell (PC) morphogenesis in Arabidopsis.

View Article and Find Full Text PDF

Abscisic acid (ABA) is a critical phytohormone that regulates multiple physiological processes including plant growth and stress tolerance. The core ABA signaling pathway has been well established, but genetic variations mediating ABA responses remain largely unknown. In this study, we performed genome-wide association study (GWAS) to identify loci and genes associated with ABA sensitivity (reflected by seed germination inhibition by ABA) in a panel of 425 rice accessions.

View Article and Find Full Text PDF

Accurate and high-throughput phenotyping of the dynamic response of a large rice population to drought stress in the field is a bottleneck for genetic dissection and breeding of drought resistance. Here, high-efficiency and high-frequent image acquisition by an unmanned aerial vehicle (UAV) was utilized to quantify the dynamic drought response of a rice population under field conditions. Deep convolutional neural networks (DCNNs) and canopy height models were applied to extract highly correlated phenotypic traits including UAV-based leaf-rolling score (LRS_uav), plant water content (PWC_uav) and a new composite trait, drought resistance index by UAV (DRI_uav).

View Article and Find Full Text PDF

Histone H2B monoubiquitination (H2Bub1) plays important roles in several physiological and developmental processes, but its roles in the regulation of plant stress responses remain elusive. Here, we report that H2Bub1 is crucially involved in abscisic acid (ABA) signaling and drought response in rice. We found that rice HISTONE MONOUBIQUITINATION2 (OsHUB2), an E3 ligase for H2Bub1, interacted with OsbZIP46, a key transcription factor regulating ABA signaling and drought response in rice.

View Article and Find Full Text PDF

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions.

View Article and Find Full Text PDF

Understanding how plants respond to drought can benefit drought resistance (DR) breeding. Using a non-destructive phenotyping facility, 51 image-based traits (i-traits) for 507 rice accessions were extracted. These i-traits can be used to monitor drought responses and evaluate DR.

View Article and Find Full Text PDF

Background: Rice panicle phenotyping is important in rice breeding, and rice panicle segmentation is the first and key step for image-based panicle phenotyping. Because of the challenge of illumination differentials, panicle shape deformations, rice accession variations, different reproductive stages and the field's complex background, rice panicle segmentation in the field is a very large challenge.

Results: In this paper, we propose a rice panicle segmentation algorithm called Panicle-SEG, which is based on simple linear iterative clustering superpixel regions generation, convolutional neural network classification and entropy rate superpixel optimization.

View Article and Find Full Text PDF