Prediction of DNA i-motifs via machine learning.

i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of putative iMs vary dramatically. Much previous research on iM has focused on assessing the iM folding properties using biophysical experiments. However, there are no dedicated computational tools for predicting the folding status and strength of iM structures. Here, we introduce a machine learning pipeline, iM-Seeker, to predict both folding status and structural stability of DNA iMs. The programme iM-Seeker incorporates a Balanced Random Forest classifier trained on genome-wide iMab antibody-based CUT&Tag sequencing data to predict the folding status and an Extreme Gradient Boosting regressor to estimate the folding strength according to both literature biophysical data and our in-house biophysical experiments. iM-Seeker predicts DNA iM folding status with a classification accuracy of 81% and estimates the folding strength with coefficient of determination (R2) of 0.642 on the test set. Model interpretation confirms that the nucleotide composition of the C-rich sequence significantly affects iM stability, with a positive correlation with sequences containing cytosine and thymine and a negative correlation with guanine and adenine.

iM-Seeker: a webserver for DNA i-motifs prediction and scoring via automated machine learning.

DNA, beyond its canonical B-form double helix, adopts various alternative conformations, among which the i-motif, emerging in cytosine-rich sequences under acidic conditions, holds significant biological implications in transcription modulation and telomere biology. Despite recognizing the crucial role of i-motifs, predictive software for i-motif forming sequences has been limited. Addressing this gap, we introduce 'iM-Seeker', an innovative computational platform designed for the prediction and evaluation of i-motifs. iM-Seeker exhibits the capability to identify potential i-motifs within DNA segments or entire genomes, calculating stability scores for each predicted i-motif based on parameters such as the cytosine tracts number, loop lengths, and sequence composition. Furthermore, the webserver leverages automated machine learning (AutoML) to effortlessly fine-tune the optimal i-motif scoring model, incorporating user-supplied experimental data and customised features. As an advanced, versatile approach, 'iM-Seeker' promises to advance genomic research, highlighting the potential of i-motifs in cell biology and therapeutic applications. The webserver is freely available at https://im-seeker.org.

G4Atlas: a comprehensive transcriptome-wide G-quadruplex database.

RNA G-quadruplex (rG4) is a vital RNA tertiary structure motif that involves the base pairs on both Hoogsteen and Watson-Crick faces of guanines. rG4 is of great importance in the post-transcriptional regulation of gene expression. Experimental technologies have advanced to identify in vitro and in vivo rG4s across diverse transcriptomes. Building on these recent advances, here we present G4Atlas, the first transcriptome-wide G-quadruplex database, in which we have collated, classified, and visualized transcriptome rG4 experimental data, generated from rG4-seq, chemical profiling and ligand-binding methods. Our comprehensive database includes transcriptome-wide rG4s generated from 82 experimental treatments and 238 samples across ten species. In addition, we have also included RNA secondary structure prediction information across both experimentally identified and unidentified rG4s to enable users to display any potential competitive folding between rG4 and RNA secondary structures. As such, G4Atlas will enable users to explore the general functions of rG4s in diverse biological processes. In addition, G4Atlas lays the foundation for further data-driven deep learning algorithms to examine rG4 structural features.

Loss of sphingosine kinase 2 promotes the expansion of hematopoietic stem cells by improving their metabolic fitness.

Hematopoietic stem cells (HSCs) have reduced capacities to properly maintain and replenish the hematopoietic system during myelosuppressive injury or aging. Expanding and rejuvenating HSCs for therapeutic purposes has been a long-sought goal with limited progress. Here, we show that the enzyme Sphk2 (sphingosine kinase 2), which generates the lipid metabolite sphingosine-1-phosphate, is highly expressed in HSCs. The deletion of Sphk2 markedly promotes self-renewal and increases the regenerative potential of HSCs. More importantly, Sphk2 deletion globally preserves the young HSC gene expression pattern, improves the function, and sustains the multilineage potential of HSCs during aging. Mechanistically, Sphk2 interacts with prolyl hydroxylase 2 and the Von Hippel-Lindau protein to facilitate HIF1α ubiquitination in the nucleus independent of the Sphk2 catalytic activity. Deletion of Sphk2 increases hypoxic responses by stabilizing the HIF1α protein to upregulate PDK3, a glycolysis checkpoint protein for HSC quiescence, which subsequently enhances the function of HSCs by improving their metabolic fitness; specifically, it enhances anaerobic glycolysis but suppresses mitochondrial oxidative phosphorylation and generation of reactive oxygen species. Overall, targeting Sphk2 to enhance the metabolic fitness of HSCs is a promising strategy to expand and rejuvenate functional HSCs.

Bacterial interactome disturbance in chronic obstructive pulmonary disease clinical stability and exacerbations.

RATIONALE: Our understanding of airway dysbiosis in chronic obstructive pulmonary disease (COPD) remains incomplete, which may be improved by unraveling the complexity in microbial interactome. OBJECTIVES: To characterize reproducible features of airway bacterial interactome in COPD at clinical stability and during exacerbation, and evaluate their associations with disease phenotypes. METHODS: We performed weighted ensemble-based co-occurrence network analysis of 1742 sputum microbiomes from published and new microbiome datasets, comprising two case-control studies of stable COPD versus healthy control, two studies of COPD stability versus exacerbation, and one study with exacerbation-recovery time series data. RESULTS: Patients with COPD had reproducibly lower degree of negative bacterial interactions, i.e. total number of negative interactions as a proportion of total interactions, in their airway microbiome compared with healthy controls. Evaluation of the Haemophilus interactome showed that the antagonistic interaction networks of this established pathogen rather than its abundance consistently changed in COPD. Interactome dynamic analysis revealed reproducibly reduced antagonistic interactions but not diversity loss during COPD exacerbation, which recovered after treatment. In phenotypic analysis, unsupervised network clustering showed that loss of antagonistic interactions was associated with worse clinical symptoms (dyspnea), poorer lung function, exaggerated neutrophilic inflammation, and higher exacerbation risk. Furthermore, the frequent exacerbators (≥ 2 exacerbations per year) had significantly reduced antagonistic bacterial interactions while exhibiting subtle compositional changes in their airway microbiota. CONCLUSIONS: Bacterial interactome disturbance characterized by reduced antagonistic interactions, rather than change in pathogen abundance or diversity, is a reproducible feature of airway dysbiosis in COPD clinical stability and exacerbations, which suggests that we may target interactome rather than pathogen alone for disease treatment.

piRBase: integrating piRNA annotation in all aspects.

Piwi-interacting RNAs are a type of small noncoding RNA that have various functions. piRBase is a manually curated resource focused on assisting piRNA functional analysis. piRBase release v3.0 is committed to providing more comprehensive piRNA related information. The latest release covers >181 million unique piRNA sequences, including 440 datasets from 44 species. More disease-related piRNAs and piRNA targets have been collected and displayed. The regulatory relationships between piRNAs and targets have been visualized. In addition to the reuse and expansion of the content in the previous version, the latest version has additional new content, including gold standard piRNA sets, piRNA clusters, piRNA variants, splicing-junction piRNAs, and piRNA expression data. In addition, the entire web interface has been redesigned to provide a better experience for users. piRBase release v3.0 is free to access, browse, search, and download at http://bigdata.ibp.ac.cn/piRBase.

RSVdb: a comprehensive database of transcriptome RNA structure.

RNA fulfills a crucial regulatory role in cells by folding into a complex RNA structure. To date, a chemical compound, dimethyl sulfate (DMS), has been developed to probe the RNA structure at the transcriptome level effectively. We proposed a database, RSVdb (https://taolab.nwafu.edu.cn/rsvdb/), for the browsing and visualization of transcriptome RNA structures. RSVdb, including 626 225 RNAs with validated DMS reactivity from 178 samples in eight species, supports four main functions: information retrieval, research overview, structure prediction and resource download. Users can search for species, studies, transcripts and genes of interest; browse the quality control of sequencing data and statistical charts of RNA structure information; preview and perform online prediction of RNA structures in silico and under DMS restraint of different experimental treatments and download RNA structure data for species and studies. Together, RSVdb provides a reference for RNA structure and will support future research on the function of RNA structure at the transcriptome level.

Programmed genome editing by a miniature CRISPR-Cas12f nuclease.

The RNA-guided CRISPR-associated (Cas) nucleases are versatile tools for genome editing in various organisms. The large sizes of the commonly used Cas9 and Cas12a nucleases restrict their flexibility in therapeutic applications that use the cargo-size-limited adeno-associated virus delivery vehicle. More compact systems would thus offer more therapeutic options and functionality for this field. Here, we report a miniature class 2 type V-F CRISPR-Cas genome-editing system from Acidibacillus sulfuroxidans (AsCas12f1, 422 amino acids). AsCas12f1 is an RNA-guided endonuclease that recognizes 5' T-rich protospacer adjacent motifs and creates staggered double-stranded breaks to target DNA. We show that AsCas12f1 functions as an effective genome-editing tool in both bacteria and human cells using various delivery methods, including plasmid, ribonucleoprotein and adeno-associated virus. The small size of AsCas12f1 offers advantages for cellular delivery, and characterizations of AsCas12f1 may facilitate engineering more compact genome-manipulation technologies.

The comprehension of relative clauses in Mandarin Children with suspected specific language impairment.

This paper investigates the comprehension of Relative Clauses (RCs) in 15 Mandarin children with suspected Specific Language Impairment (SLI) (aged between 4; 5 and 6; 0) and 29 typically developing (TD) controls. Results from a Character Picture Matching Task indicate that (i) the subject RC was better understood than the object RC in children with SLI, but there was no asymmetry in the comprehension of the two RCs in TD children; (ii) the performance of children with SLI was significantly worse than that of their TD peers; (iii) children with SLI were prone to committing thematic role reversal errors and middle errors. In order to overcome the shortcomings of previous accounts, we therefore put forward the Edge Feature Underspecification Hypothesis, which can not only explain the asymmetry of comprehension seen in children with SLI but also shed light on the nature of errors committed by them in the task.

[Role of Liquid-Liquid Phase Separation in Cell Fate Transition and Diseases].

Liquid-liquid phase separation (LLPS), a novel mechanism of the organization and formation of cellular structures, plays a vital role in regulating cell fate transitions and disease pathogenesis and is gaining widespread attention. LLPS may lead to the assemblage of cellular structures with liquid-like fluidity, such as germ granules, stress granules, and nucleoli, which are classic membraneless organelles. These structures are typically formed through the high-concentration liquid aggregation of biomacromolecules driven by weak multivalent interactions. LLPS is involved in regulating various intracellular life activities and its dysregulation may cause the disruption of cellular functions, thereby contributing to the pathogenesis and development of neurodegenerative diseases, infectious diseases, cancers, etc. Herein, we summarized published findings on the LLPS dynamics of membraneless organelles in physiological and pathological cell fate transition, revealing their crucial roles in cell differentiation, development, and various pathogenic processes. This paper provides a fresh theoretical framework and potential therapeutic targets for LLPS-related studies, opening new avenues for future research.

A cytosolic pentatricopeptide repeat protein is essential for tapetal plastid development by regulating OsGLK1 transcript levels in rice.

Most plant pentatricopeptide repeat (PPR) proteins localize to and function inside plastids and mitochondria. However, the function of PPRs that only localize to the cytoplasm remains unknown. Here, we demonstrated that the rice (Oryza sativa) PPR protein CYTOPLASM-LOCALIZED PPR1 (OsCPPR1) contributes to pollen development and localizes to the cytoplasm. Knocking down OsCPPR1 led to abnormal plastid development in tapetal cells, prolonged tapetal programmed cell death (PCD) and tapetum degradation, and significantly reduced pollen fertility. Transcriptome analysis revealed that the transcript level of OsGOLDEN-LIKE1 (OsGLK1), which encodes a transcription factor that regulates plastid development and maintenance, was significantly higher in the OsCPPR1 knockdown plants compared to wild-type plants. We further determined that OsCPPR1 downregulates OsGLK1 transcription by directly binding to the single-stranded regions of OsGLK1 mRNAs. Overexpression of OsGLK1 resulted in abnormal tapetum and plastid development, similar to that seen in OsCPPR1 knockdown plants, and suppression of OsGLK1 partially restored pollen fertility in the OsCPPR1 knockdown plants. We therefore conclude that OsCPPR1 suppresses OsGLK1 in the regulation of plastid development and PCD in the tapetum. Our work revealed novel functions for a cytosolic PPR, demonstrating the diverse roles of PPRs in plants and identifying a new regulatory mechanism for regulating pollen development in rice.

Prediction of clinically relevant pancreatic fistula after pancreatic surgery using preoperative CT scan: A systematic review and meta-analysis.

BACKGROUND: Body composition analysis has emerged as a practical tool for predicting outcomes following pancreatic surgery. However, the impact of body composition disorders on clinically relevant postoperative pancreatic fistula (CR-POPF) remains inconclusive. The aim of this study was to review and analyse whether radiographically assessed body composition is predictive of CR-POPF. METHODS: PubMed, MEDLINE, Web of Science, and the Cochrane Library databases were searched up to January 2020 to identify relevant studies. CR-POPF was defined according to the definition and grading system proposed by the International Study Group on Pancreatic Surgery (ISGPS). Pooled odds ratios (OR) for CR-POPF were calculated to evaluate the predictive values of radiographically assessed body composition. RESULTS: Fifteen studies published between 2008 and 2019 with a total of 3136 patients were included. There was a significant increase in the incidence of CR-POPF in patients with visceral obesity (OR 2.97, 95% CI 2.05-4.29, P < 0.00001) and sarcopenic obesity (OR 2.88, 95% CI 1.31-6.34, P = 0.009). Conversely, the impact of sarcopenia (OR 0.91, 95% CI 0.65-1.28, P = 0.59) and low muscle attenuation (MA) on CR-POPF did not reach statistical significance. CONCLUSION: Preoperative visceral obesity and sarcopenic obesity are more effective at predicting CR-POPF than decreased muscle quantity and quality. This finding may lead to appropriate management and early intervention of patients at risk of CR-POPF.

A network-based variable selection approach for identification of modules and biomarker genes associated with end-stage kidney disease.

AIMS: Intervention for end-stage kidney disease (ESKD), which is associated with adverse prognoses and major economic burdens, is challenging due to its complex pathogenesis. The study was performed to identify biomarker genes and molecular mechanisms for ESKD by bioinformatics approach. METHODS: Using the Gene Expression Omnibus dataset GSE37171, this study identified pathways and genomic biomarkers associated with ESKD via a multi-stage knowledge discovery process, including identification of modules of genes by weighted gene co-expression network analysis, discovery of important involved pathways by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, selection of differentially expressed genes by the empirical Bayes method, and screening biomarker genes by the least absolute shrinkage and selection operator (Lasso) logistic regression. The results were validated using GSE70528, an independent testing dataset. RESULTS: Three clinically important gene modules associated with ESKD, were identified by weighted gene co-expression network analysis. Within these modules, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed important biological pathways involved in ESKD, including transforming growth factor-ß and Wnt signalling, RNA-splicing, autophagy and chromatin and histone modification. Furthermore, Lasso logistic regression was conducted to identify five final genes, namely, CNOT8, MST4, PPP2CB, PCSK7 and RBBP4 that are differentially expressed and associated with ESKD. The accuracy of the final model in distinguishing the ESKD cases and controls was 96.8% and 91.7% in the training and validation datasets, respectively. CONCLUSION: Network-based variable selection approaches can identify biological pathways and biomarker genes associated with ESKD. The findings may inform more in-depth follow-up research and effective therapy.

Identification and Characterization of the Small Heat Shock Protein Hsp20 from Oenococcus oeni SD-2a.

Oenococcus oeni can exert its function in hostile wine conditions during the malolactic fermentation process. Therefore, it is an important microbial resource for exploring resistance genes. Hsp20 is an important small heat shock protein from O. oeni. The conserved consensus motif "A-x-x-x-x-G-x-L" of Hsp20 announced its role as a member of the small heat shock protein family. The hsp20 gene from O. oeni SD-2a was cloned to create the recombinant plasmid pTriEx-Hsp20. The recombinant plasmid was transformed into Escherichia coli BL21(DE3) competent cells, and the Hsp20 protein was induced by isopropyl-ß-D-thiogalactoside (IPTG). The hsp20 gene from O. oeni SD-2a was successfully expressed, and a 20-kDa fusion protein was identified by SDS-PAGE. The purified Hsp20 protein was obtained using Ni-affinity chromatography. Additionally, BL21(DE3)/Hsp20 and BL21(DE3)/Ctrl were treated at high temperatures of 42 and 52 °C, at pH values of 2.0-12.0, under oxidative shock with 0.1% (v/v) and 0.2% (v/v) H2O2, and under an osmotic shock of 430 and 860 mM NaCl to compare the effects of heterologous expression of the Hsp20 protein from O. oeni SD-2a for stress resistance. Notably, Hsp20 overexpression showed enhanced resistance than the control strain did when confronted with different elevated stress conditions. The results demonstrated heterologous expression of the hsp20 gene from O. oeni SD-2a significantly improved the resistance of the host E. coli bacteria against stress conditions.

Deciphering the rules of mRNA structure differentiation in Saccharomyces cerevisiae in vivo and in vitro with deep neural networks.

The structure of mRNA in vivo is unwound to some extent in response to multiple factors involved in the translation process, resulting in significant differences from the structure of the same mRNA in vitro. In this study, we have proposed a novel application of deep neural networks, named DeepDRU, to predict the degree of mRNA structure unwinding in vivo by fitting five quantifiable features that may affect mRNA folding: ribosome density (RD), minimum folding free energy (MFE), GC content, translation initiation ribosome density (INI) and mRNA structure position (POS). mRNA structures with adjustment of the simulated structural features were designed and then fed into the trained DeepDRU model. We found unique effect regions of these five features on mRNA structure in vivo. Strikingly, INI is the most critical factor affecting the structure of mRNA in vivo, and structural sequence features, including MFE and GC content, have relatively smaller effects. DeepDRU provides a new paradigm for predicting the unwinding capability of mRNA structure in vivo. This improved knowledge about the mechanisms of factors influencing the structural capability of mRNA to unwind will facilitate the design and functional analysis of mRNA structure in vivo.

The Molecular Mechanism of Ethylene-Mediated Root Hair Development Induced by Phosphate Starvation.

Enhanced root hair production, which increases the root surface area for nutrient uptake, is a typical adaptive response of plants to phosphate (Pi) starvation. Although previous studies have shown that ethylene plays an important role in root hair development induced by Pi starvation, the underlying molecular mechanism is not understood. In this work, we characterized an Arabidopsis mutant, hps5, that displays constitutive ethylene responses and increased sensitivity to Pi starvation due to a mutation in the ethylene receptor ERS1. hps5 accumulates high levels of EIN3 protein, a key transcription factor involved in the ethylene signaling pathway, under both Pi sufficiency and deficiency. Pi starvation also increases the accumulation of EIN3 protein. Combined molecular, genetic, and genomic analyses identified a group of genes that affect root hair development by regulating cell wall modifications. The expression of these genes is induced by Pi starvation and is enhanced in the EIN3-overexpressing line. In contrast, the induction of these genes by Pi starvation is suppressed in ein3 and ein3eil1 mutants. EIN3 protein can directly bind to the promoter of these genes, some of which are also the immediate targets of RSL4, a key transcription factor that regulates root hair development. Based on these results, we propose that under normal growth conditions, the level of ethylene is low in root cells; a group of key transcription factors, including RSL4 and its homologs, trigger the transcription of their target genes to promote root hair development; Pi starvation increases the levels of the protein EIN3, which directly binds to the promoters of the genes targeted by RSL4 and its homologs and further increase their transcription, resulting in the enhanced production of root hairs. This model not only explains how ethylene mediates root hair responses to Pi starvation, but may provide a general mechanism for how ethylene regulates root hair development under both stress and non-stress conditions.

Transcriptome Association Identifies Regulators of Wheat Spike Architecture.

The architecture of wheat (Triticum aestivum) inflorescence and its complexity is among the most important agronomic traits that influence yield. For example, wheat spikes vary considerably in the number of spikelets, which are specialized reproductive branches, and the number of florets, which are spikelet branches that produce seeds. The large and repetitive nature of the three homologous and highly similar subgenomes of wheat has impeded attempts at using genetic approaches to uncover beneficial alleles that can be utilized for yield improvement. Using a population-associative transcriptomic approach, we analyzed the transcriptomes of developing spikes in 90 wheat lines comprising 74 landrace and 16 elite varieties and correlated expression with variations in spike complexity traits. In combination with coexpression network analysis, we inferred the identities of genes related to spike complexity. Importantly, further experimental studies identified regulatory genes whose expression is associated with and influences spike complexity. The associative transcriptomic approach utilized in this study allows rapid identification of the genetic basis of important agronomic traits in crops with complex genomes.

Identification of hub genes with diagnostic values in pancreatic cancer by bioinformatics analyses and supervised learning methods.

BACKGROUND: Pancreatic cancer is one of the most lethal tumors with poor prognosis, and lacks of effective biomarkers in diagnosis and treatment. The aim of this investigation was to identify hub genes in pancreatic cancer, which would serve as potential biomarkers for cancer diagnosis and therapy in the future. METHODS: Combination of two expression profiles of GSE16515 and GSE22780 from Gene Expression Omnibus (GEO) database was served as training set. Differentially expressed genes (DEGs) with top 25% variance followed by protein-protein interaction (PPI) network were performed to find candidate genes. Then, hub genes were further screened by survival and cox analyses in The Cancer Genome Atlas (TCGA) database. Finally, hub genes were validated in GSE15471 dataset from GEO by supervised learning methods k-nearest neighbor (kNN) and random forest algorithms. RESULTS: After quality control and batch effect elimination of training set, 181 DEGs bearing top 25% variance were identified as candidate genes. Then, two hub genes, MMP7 and ITGA2, correlating with diagnosis and prognosis of pancreatic cancer were screened as hub genes according to above-mentioned bioinformatics methods. Finally, hub genes were demonstrated to successfully differ tumor samples from normal tissues with predictive accuracies reached to 93.59 and 81.31% by using kNN and random forest algorithms, respectively. CONCLUSIONS: All the hub genes were associated with the regulation of tumor microenvironment, which implicated in tumor proliferation, progression, migration, and metastasis. Our results provide a novel prospect for diagnosis and treatment of pancreatic cancer, which may have a further application in clinical.

An organ boundary-enriched gene regulatory network uncovers regulatory hierarchies underlying axillary meristem initiation.

Gene regulatory networks (GRNs) control development via cell type-specific gene expression and interactions between transcription factors (TFs) and regulatory promoter regions. Plant organ boundaries separate lateral organs from the apical meristem and harbor axillary meristems (AMs). AMs, as stem cell niches, make the shoot a ramifying system. Although AMs have important functions in plant development, our knowledge of organ boundary and AM formation remains rudimentary. Here, we generated a cellular-resolution genomewide gene expression map for low-abundance Arabidopsis thaliana organ boundary cells and constructed a genomewide protein-DNA interaction map focusing on genes affecting boundary and AM formation. The resulting GRN uncovers transcriptional signatures, predicts cellular functions, and identifies promoter hub regions that are bound by many TFs. Importantly, further experimental studies determined the regulatory effects of many TFs on their targets, identifying regulators and regulatory relationships in AM initiation. This systems biology approach thus enhances our understanding of a key developmental process.

Suppression of Photosynthetic Gene Expression in Roots Is Required for Sustained Root Growth under Phosphate Deficiency.

Plants cope with inorganic phosphate (Pi) deficiencies in their environment by adjusting their developmental programs and metabolic activities. For Arabidopsis (Arabidopsis thaliana), the developmental responses include the inhibition of primary root growth and the enhanced formation of lateral roots and root hairs. Pi deficiency also inhibits photosynthesis by suppressing the expression of photosynthetic genes. Early studies showed that photosynthetic gene expression was also suppressed in Pi-deficient roots, a nonphotosynthetic organ; however, the biological relevance of this phenomenon remains unknown. In this work, we characterized an Arabidopsis mutant, hypersensitive to Pi starvation7 (hps7), that is hypersensitive to Pi deficiency; the hypersensitivity includes an increased inhibition of root growth. HPS7 encodes a tyrosylprotein sulfotransferase. Accumulation of HPS7 proteins in root tips is enhanced by Pi deficiency. Comparative RNA sequencing analyses indicated that the expression of many photosynthetic genes is activated in roots of hps7. Under Pi deficiency, the expression of photosynthetic genes in hps7 is further increased, which leads to enhanced accumulation of chlorophyll, starch, and sucrose. Pi-deficient hps7 roots also produce a high level of reactive oxygen species. Previous research showed that the overexpression of GOLDEN-like (GLK) transcription factors in transgenic Arabidopsis activates photosynthesis in roots. The GLK overexpressing (GLK OX) lines also exhibit increased inhibition of root growth under Pi deficiency. The increased inhibition of root growth in hps7 and GLK OX lines by Pi deficiency was completely reversed by growing the plants in the dark. Based on these results, we propose that suppression of photosynthetic gene expression is required for sustained root growth under Pi deficiency.