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Summary Grain weight is the most important component of rice yield and is mainly determined by grain size, which is generally controlled by quantitative trait loci (QTLs). Although numerous QTLs that regulate grain weight have been identified, the genetic network that controls grain size remains unclear. Herein, we report the cloning and functional analysis of a dominant QTL, grain length and width 2 (GLW2), which positively regulates grain weight by simultaneously increasing grain length and width. The GLW2 locus encodes OsGRF4 (growth‐regulating factor 4) and is regulated by the microRNA miR396c in vivo. The mutation in OsGRF4 perturbs the OsmiR396 target regulation of OsGRF4, generating a larger grain size and enhanced grain yield. We also demonstrate that OsGIF1 (GRF‐interacting factors 1) directly interacts with OsGRF4, and increasing its expression improves grain size. Our results suggest that the miR396c‐OsGRF4‐OsGIF1 regulatory module plays an important role in grain size determination and holds implications for rice yield improvement.

Summary Genome editing has become a routine tool for functionally characterizing plant and animal genomes. However, stable genome editing in plants remains limited by the time‐ and labour‐intensive process of generating transgenic plants, as well as by the efficient isolation of desired heritable edits. In this study, we evaluated the impact of the morphogenic regulator GRF‐GIF on plant regeneration and genome editing outcomes in tomato. We demonstrate that expressing a tomato GRF‐GIF chimera reliably accelerates the onset of shoot regeneration from callus tissue culture by approximately one month and nearly doubles the number of recovered transgenic plants. Consequently, the GRF‐GIF chimera enables the recovery of a broader range of edited haplotypes and simplifies the isolation of mutants harbouring heritable edits, but without markedly interfering with plant growth and development. Based on these findings, we outline strategies that employ basic or advanced diagnostic pipelines for efficient isolation of single‐ and higher‐order mutants in tomato. Our work represents a technical advantage for tomato transformation and genome editing, with potential applications across other Solanaceae species.

Transcription factors are key regulators of gene expression and play pivotal roles in all aspects of living organisms. Therefore, identification and functional characterization of transcription factors is a prerequisite step toward understanding life. This article reviews molecular and biological functions of the two transcription regulator families, GROWTH-REGULATING FACTOR (GRF) and GRF-INTERACTING FACTOR (GIF), which have only recently been recognized. A myriad of experimental evidence clearly illustrates that GRF and GIF are bona fide partner proteins and form a plant-specific transcriptional complex. One of the most conspicuous outcomes from this research field is that the GRF–GIF duo endows the primordial cells of vegetative and reproductive organs with a meristematic specification state, guaranteeing the supply of cells for organogenesis and successful reproduction. It has recently been shown that GIF1 proteins, also known as ANGUSTIFOLIA3, recruit chromatin remodelling complexes to target genes, and that AtGRF expression is directly activated by the floral identity factors, APETALA1 and SEPALLATA3, providing an important insight into understanding of the action of GRF–GIF. Moreover, GRF genes are extensively subjected to post-transcriptional control by microRNA396, revealing the presence of a complex regulatory circuit in regulation of plant growth and development by the GRF–GIF duo.

Ground reaction force (GRF) during jumping, which is an outcome of the complex cellular and molecular biomechanical processes within the lower limb, reflects the interaction of the lower limb with the ground. Previous studies, however, have been restricted to analyzing only the peak kinetics, overlooking the moment when the peak occurs and other essential details beyond the peak. Thus, the objective of our study was to explore the relationship between the full time series of GRF and jump height during volleyball spike jumps, considering the underlying cellular and molecular biomechanical mechanisms. Data on the kinematics and kinetics of 22 elite male (mean age: 21.56 years) collegiate volleyball players’ spike jumps were gathered via a motion capture system comprising 13 high-speed cameras and 2 force plates. Then, we analyzed the association between the full ground reaction force time series and jump height using statistical parameter mapping (SPM) regression. The results of the study demonstrated that the horizontal GRF of the dominant foot was significantly related to jump height in the 23%–80% interval of dominant foot contact (DFC) with the force plate to take-off (TO). This association is likely due to the coordinated activation and contraction of specific muscle cells and molecular signaling pathways within the lower limb muscles that govern force generation and transmission. The vertical GRF of the dominant foot was significantly associated with jump height in the 29%–35% and 80%–94% intervals of DFC to TO, which could be attributed to the differential recruitment and activity of muscle fibers at the cellular and molecular levels. Similarly, the non-dominant foot was significantly associated with jump height in the 48%–63% interval of non-dominant foot contact (NFC) with the force plate to TO. These data emphasize the significance of enhancing lower limb muscle capacity through interventions that target the cellular and molecular biomechanical aspects, in order to improve jumping technique and overall performance.

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Plant leaves undergo a series of developmental changes from leaf primordium initiation through growth and maturation to senescence throughout their life span. Although the mechanisms underlying leaf senescence have been intensively elucidated, our knowledge of the interrelationship between early leaf development and senescence is still fragmentary. We isolated the oresara15-1Dominant (ore15-1D) mutant, which had an extended leaf longevity and an enlarged leaf size, from activation-tagged lines of Arabidopsis. Plasmid rescue identified that ORE15 encodes a PLANT A/T-RICH SEQUENCE- AND ZINC-BINDING PROTEIN family transcription factor. Phenotypes of ore15-1D and ore15-2, a loss-of-function mutant, were evaluated through physiological and anatomical analyses. Microarray, quantitative reverse transcription polymerase chain reaction, and chromatin immunoprecipitation as well as genetic analysis were employed to reveal the molecular mechanism of ORE15 in the regulation of leaf growth and senescence. ORE15 enhanced leaf growth by promoting the rate and duration of cell proliferation in the earlier stage and suppressed leaf senescence in the later stage by modulating the GROWTH-REGULATING FACTOR (GRF)/GRF-INTERACTING FACTOR regulatory pathway. Our study highlighted a molecular conjunction through ORE15 between growth and senescence, which are two temporally separate developmental processes during leaf life span.

Summary Improving plant biomass yield and/or feedstock quality for highly efficient lignocellulose conversion has been the main research focus in genetic modification of switchgrass (Panicum virgatum L.), a dedicated model plant for biofuel production. Here, we proved that overexpression of miR396 (OE‐miR396) leads to reduced plant height and lignin content mainly by reducing G‐lignin monomer content. We identified nineteen PvGRFs in switchgrass and proved thirteen of them were cleaved by miR396. MiR396‐targeted PvGRF1, PvGRF9 and PvGRF3 showed significantly higher expression in stem. By separately overexpressing rPvGRF1, 3 and 9, in which synonymous mutations abolished the miR396 target sites, and suppression of PvGRF1/3/9 activity via PvGRF1/3/9‐SRDX overexpression in switchgrass, we confirmed PvGRF1 and PvGRF9 played positive roles in improving plant height and G‐lignin content. Overexpression of PvGRF9 was sufficient to complement the defective phenotype of OE‐miR396 plants. MiR396‐PvGRF9 modulates these traits partly by interfering GA and auxin biosynthesis and signalling transduction and cell wall lignin, glucose and xylan biosynthesis pathways. Moreover, by enzymatic hydrolysis analyses, we found that overexpression of rPvGRF9 significantly enhanced per plant sugar yield. Our results suggest that PvGRF9 can be utilized as a candidate molecular tool in modifying plant biomass yield and feedstock quality.

Proteins encoded by the G-box regulating factor (GRF, also called 14-3-3) gene family are involved in protein–protein interactions and mediate signaling transduction, which play important roles in plant growth, development, and stress responses. However, there were no detailed investigations of the GRF gene family in pear at present. In this study, we identified 25 GRF family members in the pear genome. Based on a phylogenetic analysis, the 25 GRF genes were clustered into two groups; the ε group and the non-ε group. Analyses of the exon–intron structures and motifs showed that the gene structures were conserved within each of the ε and non-ε groups. Gene duplication analysis indicated that most of the PbGRF gene expansion that occurred in both groups was due to WGD/segmental duplication. Phosphorylation sites analysis showed that the main phosphorylation sites of PbGRF proteins were serine residues. For gene expression, five PbGRF genes (PbGRF7, PbGRF11, PbGRF16, PbGRF21, and PbGRF23) were highly expressed in fruits, and PbGRF18 was highly expressed in all tissues. Further analysis revealed that eight PbGRF genes were significantly differentially expressed after treatment with different sugars; the expression of PbGRF7, PbGRF8, and PbGRF11 significantly increased, implying the involvement of these genes in sugar signaling. In addition, subcellular localization studies showed that the tested GRF proteins localize to the plasma membrane, and transgenic analysis showed that PbGRF18 can increase the sugar content in tomato leaves and fruit. The results of our research establish a foundation for functional determination of PbGRF proteins, and will help to promote a further understanding of the regulatory network in pear fruit development.

Prunus avium is a woody plant of economic importance within the genus Prunus, the family Rosaceae, which is affected by various environmental factors during its long growth period. Growth-regulating factors (GRFs) and GRF-interacting factors (GIFs) are essential in regulating plant growth and development, responding to environmental stresses, and responding to exogenous hormone induction. Genome-wide analysis showed 13 GRF genes on eight chromosomes and three GIF genes on three chromosomes in P. avium, clustered into three and two branches, respectively. Cis-acting element analysis indicated that the PavGRF promoters contained regulatory elements associated with hormones, light stress, and growth development. Therefore, we evaluated the effects of gibberellin and light stress on the GRF and GIF genes in P. avium at different stages. Transcriptome data revealed that five PavGRFs exhibited elevated expression levels during the green ripening and color conversion stages in P. avium, PavGRF9 and PavGIF1 displayed higher expression during the full red stage, and gibberellin treatment led to the upregulation of these five PavGRFs and PavGIF1 during the full red stage. However, light stress did not significantly impact the expression of PavGRFs and PavGIFs. Additionally, miR396 could bind to the PavGRFs, thereby regulating the expression level of PavGIF after transcription. This study revealed the potential roles of the GRF and GIF transcription factor families in P. avium fruit growth and development, exogenous hormone treatment, and light stress, laying the foundation for further research on the roles of the GRF and GIF gene families in P. avium.

The three Ground Reaction Force (GRF) components can be estimated using pressure insole sensors. In this paper, we compare the accuracy of estimating GRF components for both feet using six methods: three Deep Learning (DL) methods (Artificial Neural Network, Long Short-Term Memory, and Convolutional Neural Network) and three Supervised Machine Learning (SML) methods (Least Squares, Support Vector Regression, and Random Forest (RF)). Data were collected from nine subjects across six activities: normal and slow walking, static with and without carrying a load, and two Manual Material Handling activities. This study has two main contributions: first, the estimation of GRF components (Fx, Fy, and Fz) during the six activities, two of which have never been studied; second, the comparison of the accuracy of GRF component estimation between the six methods for each activity. RF provided the most accurate estimation for static situations, with mean RMSE values of RMSE_Fx = 1.65 N, RMSE_Fy = 1.35 N, and RMSE_Fz = 7.97 N for the mean absolute values measured by the force plate (reference) RMSE_Fx = 14.10 N, RMSE_Fy = 3.83 N, and RMSE_Fz = 397.45 N. In our study, we found that RF, an SML method, surpassed the experimented DL methods.