transcription factor thesis

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• Published: 26 June 2024

TnpB homologues exapted from transposons are RNA-guided transcription factors

• Tanner Wiegand 1 ,
• Florian T. Hoffmann   ORCID: orcid.org/0000-0003-0301-4259 1 ,
• Matt W. G. Walker   ORCID: orcid.org/0000-0003-3345-8248 2 ,
• Stephen Tang   ORCID: orcid.org/0000-0001-5492-9796 1 ,
• Egill Richard 1 ,
• Hoang C. Le 1 ,
• Chance Meers   ORCID: orcid.org/0000-0003-2554-3987 1 &
• Samuel H. Sternberg   ORCID: orcid.org/0000-0001-8240-9114 1  

Nature ( 2024 ) Cite this article

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• Bacteriophages
• Gene regulation
• Molecular evolution

Transposon-encoded tnpB and iscB genes encode RNA-guided DNA nucleases that promote their own selfish spread through targeted DNA cleavage and homologous recombination 1 , 2 , 3 , 4 . These widespread gene families were repeatedly domesticated over evolutionary timescales, leading to the emergence of diverse CRISPR-associated nucleases including Cas9 and Cas12 (refs. 5 , 6 ). We set out to test the hypothesis that TnpB nucleases may have also been repurposed for novel, unexpected functions other than CRISPR–Cas adaptive immunity. Here, using phylogenetics, structural predictions, comparative genomics and functional assays, we uncover multiple independent genesis events of programmable transcription factors, which we name TnpB-like nuclease-dead repressors (TldRs). These proteins use naturally occurring guide RNAs to specifically target conserved promoter regions of the genome, leading to potent gene repression in a mechanism akin to CRISPR interference technologies invented by humans 7 . Focusing on a TldR clade found broadly in Enterobacteriaceae , we discover that bacteriophages exploit the combined action of TldR and an adjacently encoded phage gene to alter the expression and composition of the host flagellar assembly, a transformation with the potential to impact motility 8 , phage susceptibility 9 , and host immunity 10 . Collectively, this work showcases the diverse molecular innovations that were enabled through repeated exaptation of transposon-encoded genes, and reveals the evolutionary trajectory of diverse RNA-guided transcription factors.

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Bridge RNAs direct programmable recombination of target and donor DNA

Structural mechanism of bridge RNA-guided recombination

Identification of RNA structures and their roles in RNA functions

Data availability.

Next-generation sequencing data generated in this study were deposited in the NCBI SRA (BioProject accession PRJNA1029663 ) and GEO ( GSE245749 ). The published genome used for ChIP–seq analyses was obtained from NCBI (GenBank NC_000913.3 ). Publicly available RNA-seq data analysed for TldR–gRNA expression are in the NCBI SRA ( ERR6044061 ) and GEO ( GSE115009 ) databases. The published genomes used for bioinformatics analyses were obtained from NCBI (Supplementary Table 4 ). The ISfinder database can be accessed at https://www-is.biotoul.fr/index.php .

Code availability

Custom scripts used for bioinformatics, TAM library analyses, and ChIP–seq data analyses are available on request. The R script describing initial steps to discover TldRs is available at https://github.com/sternberglab/Wiegand_etal_2024 .

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Acknowledgements

We thank S. R. Pesari and Z. Akhtar for laboratory support; G. D. Lampe for suggesting the TldR moniker; A. Bernheim for helpful discussions; F. Tesson, A. Bernheim, A. M. Earl and D. Gray for sharing E. coli and Enterobacter strains; C. Lu for Covaris sonicator access; R. K. Soni for mass spectrometry support; L. F. Landweber for qPCR instrument access; and the JP Sulzberger Columbia Genome Center for next-generation sequencing support. S.T. was supported by a Medical Scientist Training Program grant (5T32GM145440-02) from the NIH. M.W.G.W. was supported by a National Science Foundation Graduate Research Fellowship. C.M. was supported by the NIH Postdoctoral Fellowship F32 GM143924-01A1. S.H.S. was supported by the NSF Faculty Early Career Development Program (CAREER) Award 2239685, a Pew Biomedical Scholarship, an Irma T. Hirschl Career Scientist Award, and a startup package from the Columbia University Irving Medical Center Dean’s Office and the Vagelos Precision Medicine Fund.

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Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA

Tanner Wiegand, Florian T. Hoffmann, Stephen Tang, Egill Richard, Hoang C. Le, Chance Meers & Samuel H. Sternberg

Department of Biological Sciences, Columbia University, New York, NY, USA

Matt W. G. Walker

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Contributions

T.W., C.M., and S.H.S. conceived and designed the project. T.W. performed all of the bioinformatics experiments and aided in the design of the experimental assays. F.T.H. performed plasmid interference, ChIP–seq, and the RFP repression assays. M.W.G.W. designed and generated the E. coli strains and plasmids for the RFP repression assays, fragments for Enterobacter recombineering, conducted the motility assays and isolated flagella for liquid chromatography with tandem mass spectrometry. S.T. performed and analysed the RNA-seq and RIP-seq experiments. E.R. cultured Enterobacter strains, extracted RNA for RNA-seq, and performed the RT–qPCR and recombineering experiments. C.M. performed the preliminary TnpB bioinformatics and neighbourhood analyses, together with H.C.L., and helped design the ChIP–seq and RFP repression assays. T.W. and S.H.S. discussed the data and wrote the manuscript, with input from all authors.

Corresponding author

Correspondence to Samuel H. Sternberg .

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Competing interests.

Columbia University has filed a patent application related to this work. M.W.G.W. is a co-founder of Can9 Bioengineering. S.H.S. is a co-founder and scientific advisor to Dahlia Biosciences, a scientific advisor to CrisprBits and Prime Medicine, and an equity holder in Dahlia Biosciences and CrisprBits. All other authors declare no competing interests.

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Extended data figures and tables

Extended data fig. 1 phylogeny and ruvc nuclease domain analysis of oppf -associated tldrs..

a , Phylogenetic tree of oppF- associated TldR proteins from Fig. 2a , together with closely related TnpB proteins that contain intact RuvC active sites. The rings indicate RuvC DED active site intactness (inner) and TldR/TnpB domain composition (outer). Homologs marked with an orange square (TnpB) or green circle (TldR) were tested in heterologous experiments. b , Multiple sequence alignment of representative TnpB and TldR sequences from a , highlighting deterioration of RuvC active site motifs (shaded in red) and loss of the C-terminal zinc-finger (ZnF)/RuvC domain. Highly conserved residues are shaded in grey. c , Empirical ( Dra TnpB) and predicted AlphaFold structures of TnpB and TldR homologs marked with an asterisk in b , showing progressive loss of the active site catalytic triad.

Extended Data Fig. 2 Diverse prophages encode fliC P -associated tldR genes .

a , Genomic architecture of representative prophage elements whose boundaries could be identified by comparison to closely related isogenic strains. In each example, the prophage-containing strain is shown above the prophage-lacking strain, with species/strain names and NCBI genomic accession IDs indicated. Sequences flanking the left (5′) and right (3′) ends are highlighted in purple and yellow, respectively, together with their percentage sequence identities calculated using BLASTn. b , Alignment of distinct prophage elements, constructed using Mauve. Empty boxes represent open reading frames, and windows show sequence conservation for regions compared between prophage genomes with lines. Putative gene functions are shown below sequence conservation windows for the fliC P - tldR -encoding prophage from Enterobacter AR_163 (bottom). c , DNA sequence identities between the prophages in a , calculated with BLASTn. Identities were calculated as total matching nucleotides across the two genomes being compared, divided by the length of the query prophage genome.

Extended Data Fig. 3 RIP-seq reveals that some oppF -associated TldR proteins use short, 9–11-nt guides.

a , RNA immunoprecipitation sequencing (RIP-seq) data for an oppF- associated TldR homolog from Enterococcus faecalis ( Efa1 TldR) reveals the boundaries of a mature gRNA containing a 9-nt guide sequence. Reads were mapped to the TldR-gRNA expression plasmid; an input control is shown. b , Published RNA-seq data for Enterococcus faecalis V583 reveals similar gRNA boundaries, including an approximately 11-nt guide. c , RIP-seq data as in a for a second biological replicate of Efa1 TldR, further corroborating the observed 9–11-nt guide length.

Extended Data Fig. 4 oppF -associated TldRs target conserved genomic sequences that overlap with promoter elements driving oppA expression .

a , Schematic of original (left) and improved (right) search strategy to identify putative targets of gRNAs used by oppF -associated TldRs. Key insights resulted from the use of TAM and a shorter, 9-nt guide. b , Analysis of the guide sequence from the Efa1 TldR-associated gRNA in Extended Data Fig. 3 revealed a putative genomic target near the predicted promoter of oppA encoded within the same ABC transporter operon immediately adjacent to the tldR gene. The magnified schematics at the bottom show the predicted TAM and gRNA-target DNA base-pairing interactions for two representatives ( Efa1 TldR and Ece TldR), in which the gRNAs target opposite strands. Promoter elements predicted with BPROM are shown as brown squares. c , WebLogos of predicted guides and genomic targets associated with diverse oppF -associated TldRs highlighted in Extended Data Fig. 1 . d , Schematic of the oppF - tldR genomic locus (left) alongside the predicted function of OppA as a solute binding protein that facilitates transport of polypeptide substrates from the periplasm to the cytoplasm, in complex with the remainder of the ABC transporter apparatus. e , Published RNA-seq data for Enterococcus faecium AUS0004 45 , highlighting the oppA transcription start site (TSS). The predicted gRNA guide sequence (grey) is shown beneath the putative TAM (yellow) and target (purple) sequences, with guide-target complementarity represented by grey circles.

Extended Data Fig. 5 oppF -associated TldR homologs may target additional sites across the genome.

Schematic of Enterococcus cecorum genome and inset showing the oppF - tldR locus (top), with additional putative targets of the gRNA, other than the oppA promoter, numbered and highlighted in yellow along the genomic coordinate. A magnified view for each numbered target is shown below, with TAMs in yellow, prospective targets in purple, and TldR gRNA guide sequences in grey. Grey circles (right) represent positions of expected guide-target complementarity.

Extended Data Fig. 6 Genome-wide binding data from ChIP-seq experiments suggest a high mismatch tolerance for some TldR homologs.

a , Genome-wide ChIP–seq profiles for the indicated fliC P -associated TldR homologs, normalized to the highest peak within each dataset. The magnified insets at the bottom show the off-target sequences (grey) compared to the intended (engineered) on-target sequence (purple), with TAMs in yellow. Off-target #3 has no clear TAM-flanked off-target sequence but is intriguingly located at a tRNA locus, and binding was observed for diverse fliC P - and oppF- associated TldRs that recognized distinct TAMs. The phylogenetic tree at right indicates the relatedness of the tested and labeled homologs. b , Results for the indicated oppF -associated TldR homologs, shown as in a .

Extended Data Fig. 7 Plasmid interference assays confirm that TldR homologs lack detectable nuclease activity.

a , Schematic of E. coli -based plasmid interference assay using pEffector and pTarget. b , Representative dilution spot assays for Gst TnpB3 and synthetically inactivated RuvC mutant (D196A), showing the entire plate (left) and the magnified area of plating. Transformants were serially diluted, plated on selective media, and cultured at 37 °C for 16 h. Colony visibility was enhanced by inverting the colors and increasing contrast/brightness. c , Dilution spot assays for the indicated fliC -associated TldR homologs (left) and closely related TnpB homologs (right). Non-targeting (NT) gRNA controls are shown at the bottom, and the phylogenetic tree indicates the relatedness of the tested proteins. d , Results for the indicated oppF -associated TldR and TnpB homologs, shown as in c .

Extended Data Fig. 8 RFP repression assays reveal variable abilities of TldR homologs to block transcription elongation.

a , RFP repression activity was measured (right) as in Fig. 4f,g using modified gRNAs exhibiting variable complementarity to the target site, as schematized in the grid (left). A gRNA was also tested that lacked the extra 5′ sequence which was absent in RIP-seq reads of mature gRNAs (20 nt no 5′ seq). Bars indicate mean ± s.d. (n = 3 biological replicates). b , Schematic of RFP repression assay in which gRNAs were designed to target either the top or bottom strand within the 5′ UTR of RFP , downstream of the promoter. The phylogenetic trees (right) indicate the relatedness of the tested and labeled homologs. c , Bar graphs plotting normalized RFP fluorescence for the indicated conditions and TldR homologs. EV, empty vector; NT, non-targeting guide. Results with nuclease-dead dCas12 and dCas9 are shown for comparison. Bars indicate mean ± s.d. (n = 3 biological replicates for TldR; n = 6 biological replicates for dCas12/dCas9).

Extended Data Fig. 9 Enterobacter RNA-seq data confirm the native expression of gRNAs from fliC P - tldR loci.

a , RNA-seq read coverage from three Enterobacter strains that natively encode fliC P - tldR loci, revealing clear peaks associated with mature gRNAs containing ~95–97-nt scaffolds and 16-nt guides. Data from three biological replicates are overlaid. b , Predicted secondary structure and sequence of the gRNA associated with Eho TldR. c , Multiple sequence alignment of the DNA encoding gRNA scaffold sequences for representative fliC P -associated TldRs, with conserved positions colored in darker blue.

Extended Data Fig. 10 FliC P is expressed and incorporated into Enterobacter flagella, concomitantly with host FliC repression.

a , RNA-seq read coverage across the tldR -encoding prophage of Enterobacter sp. BIDMC93, demonstrating strong expression of fliC P , tldR , and the gRNA, alongside other genes involved in lysogeny maintenance (e.g. CI). b , Motility assays (left) with wild-type (WT) and Enterobacter deletion strains reveal similar motility phenotypes, as visualized with LB-agar plate images (middle) and a bar graph quantifying motility via halo size (right). Plate images and bar graphs represent three biological replicates; bars indicate mean ± s.d. c , Schematic representation of FliC/FliC P homologs encoded by Enterobacter sp. BIDMC93, with relative genomic positions indicated. FliC 2 is a second host flagellin gene copy encoded at an alternate flagellar assembly locus within this strain, which is not targeted by TldR and not commonly present in other Enterobacter strains. d , Results from liquid chromatography with tandem mass spectrometry (LC–MS/MS) analyses performed on digested peptides from purified flagellar filaments, isolated from the three indicated Enterobacter sp. BIDMC93 strains. The WT ( + CmR) strain encodes the cmR gene downstream of the tldR-gRNA locus (as in Fig. 5e ). Data represent the label free quantification (LFQ) intensities reflecting the variable D2-3 regions of FliC, FliC P , or FliC 2 . Although the FliC 2 appears to be the most dominant flagellin component, the relevant amounts of host FliC and FliC P demonstrate that prophage-encoded FliC P readily assembles into extracellular flagellar filaments, and that host FliC production is de-repressed upon prophage deletion. e , Quantification of changes in the expression profiles of Enterobacter FliC homologs, measured from RNA-seq data of three biological replicates depicted in Fig. 5f,g . TPM, transcripts per million. f , Alignment of fliC / fliC P / fliC 2 promoters indicates that guide RNA-target DNA mismatches prevent TldR-targeting of fliC 2 and fliC P in Enterobacter sp. BIDMC93. g , RNA-seq read coverage in the host fliC promoter/5′-UTR region overlayed for three biological replicates of four Enterobacter strains, with labeled TAM and target sequences highlighted upstream of the TSS. Strain AR136 (top) does not encode a fliC P - tldR locus; note the distinct expression levels, measured via relative counts per million (CPM). h , Alignment of host fliC promoter regions for the strains shown in g compared to E. coli K12, with percent sequence identities indicated on the right. Reported FliA/σ 28 promoter elements from E. coli K12 are shown below the alignment. i , RNA-seq read coverage in the prophage-encoded fliC P promoter/5′-UTR region overlayed for three biological replicates of two representative Enterobacter strains, confirming the predicted TSS. j , Schematic of multiple sequence alignment of the promoter region driving fliC P gene expression, across six verified prophages described in Extended Data Fig. 2 , highlighting the region that was queried for MEME motif detection.

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Wiegand, T., Hoffmann, F.T., Walker, M.W.G. et al. TnpB homologues exapted from transposons are RNA-guided transcription factors. Nature (2024). https://doi.org/10.1038/s41586-024-07598-4

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The characterization of a novel prmads11 transcription factor from pinus radiata induced early in bent pine stem.

1. Introduction

2.1. characterization of prmads11, 2.2. differential gene expression of prmads11 in young pine seedlings, 2.3. gene modulation in arabidopsis plants over-expressing prmads11, 2.4. rt-qpcr on selected genes, 2.5. protein–protein interactions using string, 2.6. protein–dna interaction analysis using emsa assays, 3. discussion, 4. materials and methods, 4.1. pine seedlings subjected to inclination stimuli, 4.2. gene cloning and vector construction, 4.3. phylogenetic analysis, 4.4. stable transformation of arabidopsis with truncated prmads11, 4.5. electrophoretic mobility shift assay (emsa), 4.6. rna extraction and quantitative rt-pcr (rt-qpcr), 4.7. arabidopsis promotor analysis, 4.8. lignin quantitation, 4.9. microarray data, 4.10. functional classification based on mapman, 4.11. string interaction network, 5. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Méndez, T.; Guajardo, J.; Cruz, N.; Gutiérrez, R.A.; Norambuena, L.; Vega, A.; Moya-León, M.A.; Herrera, R. The Characterization of a Novel PrMADS11 Transcription Factor from Pinus radiata Induced Early in Bent Pine Stem. Int. J. Mol. Sci. 2024 , 25 , 7245. https://doi.org/10.3390/ijms25137245

Méndez T, Guajardo J, Cruz N, Gutiérrez RA, Norambuena L, Vega A, Moya-León MA, Herrera R. The Characterization of a Novel PrMADS11 Transcription Factor from Pinus radiata Induced Early in Bent Pine Stem. International Journal of Molecular Sciences . 2024; 25(13):7245. https://doi.org/10.3390/ijms25137245

Méndez, Tamara, Joselin Guajardo, Nicolás Cruz, Rodrigo A. Gutiérrez, Lorena Norambuena, Andrea Vega, María A. Moya-León, and Raúl Herrera. 2024. "The Characterization of a Novel PrMADS11 Transcription Factor from Pinus radiata Induced Early in Bent Pine Stem" International Journal of Molecular Sciences 25, no. 13: 7245. https://doi.org/10.3390/ijms25137245

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Transcription factors in megakaryocytes and platelets

Hengjie yuan.

1 Tianjin Institute of Neurology, Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China

2 BloodWorks Research Institute, Seattle, WA, United States

Jianning Zhang

Jing-fei dong.

3 Division of Hematology, Department of Medicine, University of Washington, School of Medicine, Seattle, WA, United States

Zilong Zhao

Transcription factors bind promoter or regulatory sequences of a gene to regulate its rate of transcription. However, they are also detected in anucleated platelets. The transcription factors RUNX1, GATA1, STAT3, NFκB, and PPAR have been widely reported to play key roles in the pathophysiology of platelet hyper-reactivity, thrombosis, and atherosclerosis. These non-transcriptional activities are independent of gene transcription or protein synthesis but their underlying mechanisms of action remain poorly defined. Genetic and acquired defects in these transcription factors are associated with the production of platelet microvesicles that are known to initiate and propagate coagulation and to promote thrombosis. In this review, we summarize recent developments in the study of transcription factors in platelet generation, reactivity, and production of microvesicles, with a focus on non-transcriptional activities of selected transcription factors.

1. Introduction

Transcription factors (TFs) are a group of mediators that bind the promoter or regulatory sequence of a gene to control its rate of transcribing genetic information from DNA to messenger RNA ( 1 ). This transcription control is key to ensuring an adequate level of expression of a given protein in targeted cells at a particular developmental stage. It not only directs the processes of proliferation, growth, and death of a cell, but also controls the rate of cell migration and organizational development during embryonic development, as well as regulating cellular response to the extracellular matrices. Thus far, more than 1600 transcription factors have so far been identified ( 2 , 3 ), and they work in a coordinated fashion to down- as well as up-regulate target genes. The activation of a given gene can be regulated by multiple transcriptional factors and one transcription factor can regulate multiple genes. Such a multivalent activity is possible because of the modular structure of a transcriptional factor, which typically includes a DNA-binding domain, signal-sensing domain that contains binding sites for transcription co-regulators, and an optional transactivation domain, which senses external signals and transmits them to the rest of the transcription complex ( 4 , 5 ). Because of their roles in regulating gene transcription, the activation and suppression of transcription factors is extensively reported in cancer development ( 6 ).

Paradoxically, multiple transcription factors have been reported to express and be active in platelets ( Table 1 ), the anucleated offspring of megakaryocytes with a very limited capacity for protein synthesis ( 7 ). An obvious question is whether these transcription factors are merely leftover from parental megakaryocytes or have unique activities in platelets. Reports from studies on platelet transcription factors have been scarce in the literature, but increasing evidence suggests that transcription factors in platelets have unique activities of their own independent of their transcriptional activities ( 8 – 10 ). However, past research on transcription factors in platelets is often limited to reporting their presence and activation status, without further investigation of their activities in regulating platelet functions and, more importantly the underlying mechanism of their regulatory activities.

Table 1

Roles of transcription factors in platelets.

AML, acute myeloid leukemia; MDS, myelodysplastic syndrome.

Platelets circulate along the vessel wall and act to stop bleeding at sites of vessel injury. This hemostatic process requires multiple ligand-receptor interactions to tether, activate, and aggregate platelets. The tightly controlled platelet activation and aggregation that occurs at the site of vascular injury during hemostasis can become dysregulated in pathological conditions, promoting thrombosis and inflammation. For example, platelets promote arterial thrombosis or thromboembolism when activated either on the surface of a ruptured atherosclerotic plaque or by pathological levels of high fluid shear stress in the area of arterial stenosis, leading to acute thrombotic events such as ischemic stroke and myocardial infarction ( 11 ). Emerging evidence further suggests that platelets also act as a cellular mediator in a variety of pathophysiological conditions such as cancer, rheumatoid arthritis, atherosclerosis, trauma, and immune response ( 12 – 14 ). How transcription factors regulate platelet production from megakaryocytes has been extensively reported, but their non-transcriptional activities (i.e., activity independent of gene regulations) have only begun to be recognized. Here, we discuss several transcription factors that have been reported to regulate platelet production and function.

2. Transcription factors in platelet production

2.1. runt-related transcription factor 1.

In 1969, Weiss, et al. identified a family with an autosomal dominant inherited thrombocytopenia, caused primarily by decreased dense granule contents ( 15 ). A heterozygous Y260X mutation in the RUNX1 gene was subsequently shown to be the genetic basis of this inherited platelet defect ( 15 , 16 ). To date, more than 200 families with RUNX1 variants have been reported ( 17 ). RUNX1/AML1 (also known as CBFA2 and PEBP2αB) is a member of the Runt family, which has three known transcription factors (RUNX1, RUNX2, and RUNX3), which share the Runt homology domain near the N-terminus. This domain interacts with CBFb to bind specific sequences of DNA to regulate its transcription ( 18 ).

RUNX1 regulates several genes that control platelet production, structure, function, and intracellular signaling. One report found that 22 patients in a family with autosomal dominant thrombocytopenia had mutations in the RUNX1 gene ( 19 ) and 6 of them developed hematologic malignancies ( 20 ). RUNX1-deficient mice die in uterus due to defective hematopoiesis and resultant severe bleeding ( 21 , 22 ). Mice with the conditional knockout survive but have an impaired megakaryocyte maturation with a significant reduction in megakaryocyte polyploidization ( 23 ). Variations in the RUNX1 gene often result in bleeding diathesis, primarily because of defective platelet granules ( 15 , 16 ), which reduce platelet activation and aggregation ( 24 ). For example, mice carrying the RUNX1 p.Leu43Ser variant (equivalent to human p.Leu56Ser) exhibit a prolonged bleeding time because of defective α-granule secretion and platelet spreading ( 25 ). RUNX1 deficiency can result in pallidin dysregulation and deficient dense granules in platelets ( 26 ) as well as the Ras-related protein RAB31-mediated early endosomal trafficking of von Willebrand factor (VWF) and epidermal growth factor receptor (EGFR) in megakaryocytes ( 27 ). RUNX1 regulates the development of platelet granules through interaction with genes involved in the biogenesis of platelet granules such as the nuclear factor erythroid 2 (NF-E2).

In addition, RUNX1 can also regulate genes related to platelet functions. For example, it regulates the transcription of the non-muscle myosin IIA (MYH9) and IIB (MYH10) genes, which encode non-muscle myosin II heavy chains; RUNX1 mutations are associated with dysregulated expression of MYH10 in platelets ( 28 ); and the expression level of non-muscle myosin is used as a marker for changes in transcriptional activity of RUNX1 as well as friend leukemia integration 1 transcription factor (FLI1) ( 29 ). RUNX1 also regulates the expression of the arachidonate 12-lipoxygenase gene (ALOX12) ( 30 ), which encodes the enzyme that acts on polyunsaturated fatty acid substrates to generate bioactive lipid mediators to regulate platelet function ( 30 ). PCTP (phosphatidylcholine transfer protein) regulates the intermembrane transfer of phosphatidylcholine and its upregulation by RUNX1 sensitizes platelet response to thrombin through protease-activated receptor 4 ( 31 ). RUNX1 also regulates the expression of platelet factor 4 through coordination with transcription factors in the ETS family that share a conserved winged helix-turn-helix DNA binding domain that recognizes unique DNA sequences containing GGAA/T ( 32 ). Platelet factor 4 belongs to the CXC chemokine family and is released from α-granules of activated platelets to promote coagulation and to participate in heparin-induced thrombocytopenia ( 33 , 34 ). A recent report shows that RUNX-1 haploinsufficiency inhibits the differentiation of hematopoietic progenitor cells (HPCs) into megakaryocytes ( 35 ).

2.2. GATA-binding protein 1

GATA-binding protein 1 (GATA1) is a transcription factor that contains two zinc finger domains: a C-terminal zinc finger that binds the (T/A) GATA(A/G) motif of DNA and an N-terminal zinc finger that is required for stabilizing the C-terminal structure and also interacts with a nuclear co-factor protein called friend for GATA1 (FOG1), which stabilizes GATA1 binding ( 36 , 37 ). GATA plays a pivotal role in hematopoietic development and is found in megakaryocytes ( 38 ). GATA1-deficient mice die before birth at approximately embryonic day 10, primarily because of severe anemia ( 39 ). However, mutations in the N-terminal zinc finger domain, which reduces the transcriptional activation of GATA1 ( 36 , 40 ), are found in patients with myeloproliferative disorders and acute megakaryoblastic leukemia ( 41 ), suggesting that GATA1-FOG1 interaction is essential for the development and maturation of megakaryocytes, the parental cells of platelets. Decreased GATA-1 expression has also been reported in patients with myelodysplastic syndrome ( 42 ).

Embryonic stem cells from GATA1-deficient mice are smaller and show low expression of megakaryocytic markers, but have a high rate of proliferation ( 43 ). Complementation of these cells with a wild-type GATA1 gene allows megakaryocytes and erythrocytes to develop in response to a variety of cytokines. Additionally, cell division is attenuated in the megakaryocytic progenitor G1ME cells that overexpress GATA1. A recent report further shows that impaired MYH10 silencing causes GATA1-related polyploidization defect during megakaryocyte differentiation ( 44 ).

Furthermore, platelet aggregation induced by collagen is inhibited in GATA1 - deficient mice ( 45 ), primarily due to reduced expression of the collagen receptor GPVI. Platelet adhesion and aggregation induced by shear stress are also reduced in GATA1 - deficient mice ( 45 ). How a GATA1 deficiency causes these changes in platelet reactivity remains unknown, but these phenotypic changes in the mice provide the first indication that transcription factors could perform non-transcriptional activities in anucleated platelets.

3. Non-transcriptional activity in platelets

3.1. signal transducer and activator of transcription 3.

STAT includes a family of transcription factors critical for inflammatory and acute-phase reactions ( 46 , 47 ). They also play vital roles in cancer development and hematopoiesis ( 48 ). The homologous STAT1, STAT3, and STAT5 are expressed in human platelets and are reported to regulate platelet reactivity through residual or mitochondrial transcriptional activity in platelets. For example, STAT3 affects mitochondrial transcription by binding to the regulatory D-loop region of mitochondrial DNA upon platelet activation ( 49 ).

However, STAT3 can also be activated (phosphorylated) and dimerized in platelets stimulated with thrombopoietin ( 49 , 50 ), suggesting that STAT3 can also regulate platelet reactivity through non-transcriptional means. We have shown that STAT3 is activated and dimerized in collagen-stimulated platelets to serve as a protein scaffold that facilitates the catalytic interaction between spleen tyrosine kinase (Syk) and its substrate, PLCγ to enhance collagen-induced calcium mobilization and platelet activation ( 8 ). More importantly, STAT3 is activated to form dimers by a complex of IL-6 with its soluble receptor IL-6Rα, which activates JAK2 ( 51 ). The pharmacological inhibition of platelet STAT3 reduces collagen-induced platelet aggregation and thrombus formation on the collagen matrix ( 8 , 52 ). Platelets from STAT3-deficient mice or mice infused with a STAT3 inhibitor have reduced collagen-induced aggregation. This non-transcriptional activity of STAT3 may be critical for the development of platelet hyper-reactivity, which has been widely associated with inflammation, especially that related to the activity of the proinflammatory cytokine IL-6 ( 8 ). We have also shown that the piper longum derivative piperlongumine (PL) blocks collagen-induced platelet reactivity in a dose-dependent manner by targeting STAT3 ( 53 ). Consistent with our observations, the small molecular STAT3 inhibitor SC99 has been shown to reduce platelet activation and aggregation induced by collagen and thrombin ( 54 ). These findings offer a new pathway for reducing platelet hyper-reactivity in conditions of inflammation and in prothrombotic states associated with trauma, cancer, autoimmune diseases, and severe infection.

3.2. Nuclear factor kappa β

Nuclear factor kappa β (NFκB) is a well-defined redox-sensitive transcription factor that regulates the immune response and inflammation by controlling the expression of multiple genes activated by inflammatory mediators ( 55 – 57 ). Blocking NFκB can therefore improve outcomes of inflammatory diseases ( 58 ). NFκB is composed of p50 and p65 subunits, normally as an inactive cytoplasmic complex. The inhibitory proteins of the IκB family tightly bind the subunits of NFκB ( 59 ). Upon activation, the IκK complex phosphorylates IκBα, thus activating NFκB by detaching it from IkBα ( 60 – 62 ). Three IκK family members, α, β, and γ, are expressed in platelets, with β being the most abundant, and are reported to regulate platelet reactivity through non-transcriptional activity ( 9 , 10 , 63 ). For example, the pharmacological inhibition of IκKβ leads to reduced agonist-induced platelet activation, increased bleeding time, and prolonged thrombus formation in a mouse model ( 64 ). NF-κB has also been reported to be partially involved in the regulation of SERCA activity to regulate calcium homeostasis in platelets ( 65 ). IκKβ-deficient platelets lose the ability to shed the ectodomain of GP Ibα in response to ADP or collagen stimulations ( 66 ) but preserve thrombin-induced GP Ibα shedding ( 67 ). Collagen-induced p65 and IκKβ phosphorylation is blocked by inhibition of MAP kinase, but not by inhibition of ERK in platelets ( 68 ). The thrombin-induced GP Ibα shedding requires p38 mitogen-activated protein kinase (MAPK) and extracellular signal-regulated kinase (ERK) as its upstream and downstream molecules ( 68 , 69 ).

3.3. Peroxisome proliferator-activated receptors

The peroxisome proliferator-activated receptors (PPARs) are ligand-activated receptors in the nuclear hormone receptor family. They contain three subtypes (PPARα, PPARβ/δ, and PPARγ), which are essential in the regulation of cell differentiation, development, and metabolism ( 70 – 72 ). All PPARs heterodimerize with retinoid X receptor (RXR) and subsequently bind to a specific region of target genes called a peroxisome proliferator response element (PPRE) ( 73 ). PPARγ plays a transcription factor role in regulating platelet production from megakaryocytes, but the PPARγ ligand thiazolidinedione inhibits platelet aggregation induced by ADP under hydrostatic pressure and in diabetic mice ( 74 – 76 ). Similarly, activating PPARβ/δ also reduces platelet reactivity to ADP, thrombin, and collagen ( 77 , 78 ). However, PPARα is also required for platelet activation and thrombus formation, in which it regulates the dense granule secretion of platelets in hyperlipidemic mice ( 79 ). The reason for this apparent contradiction remains to be further investigated. PPARγ is recruited and phosphorylated by Syk to promote the recruitment of the protein called Linker for the Activation of T cells (LAT), which is necessary for collagen-induced platelet activation through glycoprotein VI ( 80 ).

While transcription factors are critically involved in megakaryocyte development and platelet production, they may also regulate platelet reactivity to conventional and specific platelet agonists ( Figure 1 ). The latter is independent of transcriptional activity, for which it is present but at a residual level. This non-transcriptional activity remains poorly understood and requires further investigation because it helps understanding how platelets are activated either by conventional agonists for hemostasis or as complications found in patients treated with drugs that block transcriptional activity of cells (e.g., cancer treatments). Such research will also play an important role in developing new therapeutics targeting these transcription factors to enhance or reduce platelet reactivity.

Transcription factors regulate platelet aggregation through non-transcriptional activities. (A) PPARγ is recruited and phosphorylated by Syk to promote the recruitment of LAT and enhance platelet aggregation; (B) NFκB is activated by upstream p38 mitogen-activated protein kinase (MAPK) and promotes platelet aggregation by regulating downstream extracellular signal-regulated kinase (ERK); (C) A complex of IL-6 with its soluble receptor IL-6R activates JAK2 to phosphorylate and dimerize STAT3, then the activated STAT3 serves as a protein scaffold to facilitate the catalytic interaction between the spleen tyrosine kinase (Syk) and its substrate PLCγ2 to promote platelet aggregation.

4. Transcription factors in extracellular vesicles released from platelets

Extracellular vesicles (EVs) are shed membrane fragments, intracellular organelles, and nuclear components from cells undergoing active microvesiculation ( 81 – 84 ) or apoptosis ( 85 – 87 ). The former is triggered by the activation of the cysteine protease calpain, which disrupts the membrane-cytoskeleton association ( 88 – 91 ). Platelets are the primary source of EVs circulating in blood, accounting for approximately 80% of total EVs ( 92 – 94 ). The subcellular size of EVs allows them to travel to areas where parental cells are unable to go. In additional to inherent functions from their parental cells, EVs also perform unique activities of their own because of molecules expressed on their surface and carried by them, the latter of which include transcription factors such as STAT3, STAT5, and PPARγ ( 95 ) as well as regulators of transcription factors ( 96 , 97 ). This EV-derived transcriptional activity has been scarcely reported but hold greats potential for influencing biological activities of target cells. For example, PPARγ in platelet EVs is taken up by monocytic THP-1 cells, where it induces the expression of fatty acid-binding protein-4 (FABP4). Monocytes receiving PPARγ-containing platelet EVs produce less inflammatory mediators and become more adherent through increased fibronectin production ( 95 ). Although reports on platelet-derived transcription factors remain very limited, a large body of evidence in the literature shows that platelet-derived EVs, especially EV-carried microRNAs, can change transcriptional activities, thus regulating the function of target cells. Platelet EV-carried NLR family pyrin domain containing 3 (NLRP3) stimulates endothelial cells to undergo pyroptosis through the NLRP3/nuclear factor (NF)-κB pathway ( 98 ). EVs from platelets stimulated with bacteria provoke proinflammatory activity of monocytes through the TRAF6/NFκB pathway ( 99 ). MicroRNA-142-3p carried by platelet-derived EVs promotes the proliferation of endothelial cells ( 100 ), whereas microRNA-126-3p-carrying platelet EVs can be internalized by macrophages to dose-dependently downregulate expression of target mRNA ( 101 ). These observations mostly pertain to phenotypic characterization with less information regarding the underlying pathways involved. Systemic studies of EV-carrying transcription factors and related mediators are therefore urgently needed.

5. Conclusion

Platelets lack a nucleus and de novo transcription, but a number of transcription factors are found in platelets and may have non-transcriptional activities that regulate platelet function. Transferring transcription factors between platelets and target cells through platelet EVs could also be a novel regulatory mechanism of cell-cell communications and a potential therapeutic target for a variety of pathologies.

Author contributions

HY and YL performed the literature search and compiled all the information from the researched articles and wrote the manuscript. ZZ, J-FD and JZ formulated, proposed, guided and wrote the manuscript. All authors contributed to the article and approved the submitted version.

Funding Statement

This study is supported by Young Scientists Award 82022020 from the National Natural Science Foundation of China (ZZ), National Natural Science Foundation of China 81971176 (ZZ), 81271361, 81271359 (JZ), 81102447 (HY), National Natural Science Foundation of China State Key Program Grant 81330029, National Natural Science Foundation of China Major International Joint Research Project 81720108015 (JZ), and Postdoctoral Science Foundation of China Grants 2013M541190 (HY).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Greta Friar | Whitehead Institute

July 7, 2023.

Transcription factors could be the Swiss Army knives of gene regulation; they are versatile proteins containing multiple specialized regions. On one end they have a region that can bind to DNA. On the other end they have a region that can bind to proteins. Transcription factors help to regulate gene expression—turning genes on or off and dialing up or down their level of activity—often in partnership with the proteins that they bind. They anchor themselves and their partner proteins to DNA at binding sites in genetic regulatory sequences, bringing together the components that are needed to make gene expression happen.

Transcription factors are a well-known family of proteins, but new research from Whitehead Institute Member Richard Young and colleagues shows that the picture we have had of them is incomplete. In a  paper published in  Molecular Cell  on July 3 , Young and postdocs Ozgur Oksuz and Jonathan Henninger reveal that along with DNA and protein, many transcription factors can also bind RNA. The researchers found that RNA binding keeps transcription factors near their DNA binding sites for longer, helping to fine tune gene expression. This rethinking of how transcription factors work may lead to a better understanding of gene regulation, and may provide new targets for RNA-based therapeutics.

“It’s as if, after carrying around a Swiss Army knife all your life for its blade and scissors, you suddenly realize that the odd, small piece in the back of the knife is a screwdriver,” Young says. “It’s been staring you in the face this whole time, and now that you finally see it, it becomes clear how many more uses there are for the knife than you had realized.”

How transcription factors’ RNA binding went overlooked

A few papers, including one from Young’s lab, had previously identified individual transcription factors as being able to bind RNA, but researchers thought that this was a quirk of the specific transcription factors. Instead, Young, Oksuz, Henninger and collaborators have shown that RNA-binding is in fact a common feature present in at least half of transcription factors.

“We show that RNA binding by transcription factors is a general phenomenon,” Oksuz says. “Individual examples in the past were thought to be exceptions to the rule. Other studies dismissed signs of RNA binding in transcription factors as an artifact—an accident of the experiment rather than a real finding. The clues have been there all along, but I think earlier work was so focused on the DNA and protein interactions that they didn’t consider RNA.”

The reason that researchers had not recognized transcription factors’ RNA binding region as such is because it is not a typical RNA binding domain. Typical RNA binding domains form stable structures that researchers can detect or predict with current technologies. Transcription factors do not contain such structures, and so standard searches for RNA binding domains had not identified them in transcription factors.

Young, Oksuz and Henninger got their biggest clue that researchers might be overlooking something from the human immunodeficiency virus (HIV), which produces a transcription factor-like protein called Tat. Tat increases the transcription of HIV’s RNA genome by binding to the virus’ RNA and then recruiting cellular machinery to it. However, Tat does not contain a structured RNA binding site; instead, it binds RNA from a region called an arginine-rich motif (ARM) that is unstructured but has a high affinity for RNA. When the ARM binds to HIV RNA, the two molecules form a more stable structure together.

The researchers wondered if Tat might be more similar to human transcription factors than anyone had realized. They went through the list of transcription factors, and instead of looking for structured RNA binding domains, they looked for ARMs. They found them in abundance; the majority of human transcription factors contain an ARM-like region between their DNA and protein binding regions, and these sequences were conserved across animal species. Further testing confirmed that many transcription factors do in fact use their ARMs to bind RNA.

RNA binding fine tunes gene expression

Next, the researchers tested to see if RNA binding affected the transcription factors’ function. When transcription factors had their ARMs mutated so they couldn’t bind RNA, those transcription factors were less effective in finding their target sites, remaining at those sites and regulating genes. The mutations did not prevent transcription factors from functioning altogether, suggesting that RNA binding contributes to fine-tuning of gene regulation.

Further experiments confirmed the importance of RNA binding to transcription factor function. The researchers mutated the ARM of a transcription factor important to embryonic development, and found that this led to developmental defects in zebrafish. Additionally, they looked through a list of genetic mutations known to contribute to cancer and heritable diseases, and found that a number of these occur in the RNA binding regions of transcription factors. All of these findings point to RNA binding playing an important role in transcription factors’ regulation of gene expression.

They may also provide therapeutic opportunities. The transcription factors studied by the researchers were found to bind RNA molecules that are produced in the regulatory regions of the genome where the transcription factors bind DNA. This set of transcription factors includes factors that can increase or decrease gene expression. “With evidence that RNAs can tune gene expression through their interaction with positive and negative transcription factors,” says Henninger, “we can envision using existing RNA-based technologies to target RNA molecules, potentially increasing or decreasing expression of specific genes in disease settings.”

Ozgur Oksuz, Jonathan E. Henninger, Robert Warneford-Thomson, Ming M. Zheng, Hailey Erb, Adrienne Vancura, Kalon J. Overholt, Susana Wilson Hawken, Salman F. Banani, Richard Lauman, Lauren N. Reich, Anne L. Robertson, Nancy M. Hannett, Tong I. Lee, Leonard I. Zon, Roberto Bonasio, Richard A. Young. “Transcription factors interact with RNA to regulate genes.”  Molecular Cell , July 3, 2023.  https://doi.org/10.1016/j.molcel.2023.06.012 .

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The AP2/ERF transcription factor SmERF1L1 regulates the biosynthesis of tanshinones and phenolic acids in Salvia miltiorrhiza

Affiliations.

• 1 Laboratory of Medicinal Plant Biotechnology, College of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, PR China; Institute of Plant Biotechnology, College of Life and Environment Sciences, Shanghai Normal University, Shanghai 200234, PR China.
• 2 Institute of Plant Biotechnology, College of Life and Environment Sciences, Shanghai Normal University, Shanghai 200234, PR China.
• 3 Laboratory of Medicinal Plant Biotechnology, College of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, PR China.
• 4 Jiangsu Provincial Key Laboratory of Coastal Wetland Biological Resources and Environmental Protection, School of Marine and Biological Engineering, Yancheng Teachers Uninversity, Yancheng, Jiangsu Province 224051, PR China.
• 5 Laboratory of Medicinal Plant Biotechnology, College of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, PR China; Institute of Plant Biotechnology, College of Life and Environment Sciences, Shanghai Normal University, Shanghai 200234, PR China. Electronic address: [email protected].
• PMID: 30372953
• DOI: 10.1016/j.foodchem.2018.08.119

Tanshinones and phenolic acids are two important metabolites synthesized by the traditional Chinese medicinal plant Salvia miltiorrhiza. There is increasing market demand for these compounds. Here, we isolated and functionally characterized SmERF1L1, a novel JA (Jasmonic acid)-responsive gene encoding AP2/ERF transcription factor, from Salvia miltiorrhiza. SmERF1L1 was responsive to methyl jasmonate (MJ), yeast extraction (YE), salicylic acid (SA) and ethylene treatments. Subcellular localization assay indicated that SmERF1L1 located in the nucleus. Overexpression of SmERF1L1 significantly increased tanshinones production in transgenic S. miltiorrhiza hairy roots by comprehensively upregulating tanshinone biosynthetic pathway genes, especially SmDXR. Yeast one-hybrid (Y1H) and electrophoretic mobility shift assay (EMSA) showed that SmERF1L1 binds to the GCC-box of SmDXR promoter while dual luciferase (Dual-LUC) assay showed that SmERF1L1 positively regulated the expression of SmDXR. Our study suggested that the SmERF1L1 may be a good potential target for further metabolic engineering of bioactive component biosynthesis in S. miltiorrhiza.

Keywords: AP2/ERF transcription factor; Biosynthesis; Caffeic acid (PubChem CID: 689043); Cryptotanshinone (PubChem CID: 160254); Dihydrotanshinone (PubChem CID: 11425923); Phenolic acids; Rosmarinic acid (PubChem CID: 5315615); Salvia miltiorrhiza; Salvianolic acid A (PubChem CID: 5281793); Salvianolic acid B (PubChem CID: 11629084); Tanshinone I (PubChem CID: 114917); Tanshinone IIA (PubChem CID: 164676); Tanshinones.

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Lab on a Chip

An integrative temperature-controlled microfluidic system for budding yeast heat shock response analysis at the single-cell level †.

* Corresponding authors

a The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China E-mail: [email protected]

b Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

c Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, China

Cells can respond and adapt to complex forms of environmental change. Budding yeast is widely used as a model system for these stress response studies. In these studies, the precise control of the environment with high temporal resolution is most important. However, there is a lack of single-cell research platforms that enable precise control of the temperature and form of cell growth. This has hindered our understanding of cellular coping strategies in the face of diverse forms of temperature change. Here, we developed a novel temperature-controlled microfluidic platform that integrates a microheater (using liquid metal) and a thermocouple (liquid metal vs. conductive PDMS) on a chip. Three forms of temperature changes (step, gradient, and periodical oscillations) were realized by automated equipment. The platform has the advantages of low cost and a simple fabrication process. Moreover, we investigated the nuclear entry and exit behaviors of the transcription factor Msn2 in yeast in response to heat stress (37 °C) with different heating modes. The feasibility of this temperature-controlled platform for studying the protein dynamic behavior of yeast cells was demonstrated.

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An integrative temperature-controlled microfluidic system for budding yeast heat shock response analysis at the single-cell level

J. Hong, H. He, Y. Xu, S. Wang and C. Luo, Lab Chip , 2024, Advance Article , DOI: 10.1039/D4LC00313F

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Regulatory loops between rice transcription factors OsNAC25 and OsNAC20/26 balance starch synthesis

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Juan Wang, Haiqin Zhang, Yuanjiang Wang, Shanshan Meng, Qing Liu, Qian Li, Zhiwen Zhao, Qiaoquan Liu, Cunxu Wei, Regulatory loops between rice transcription factors OsNAC25 and OsNAC20/26 balance starch synthesis, Plant Physiology , Volume 195, Issue 2, June 2024, Pages 1365–1381, https://doi.org/10.1093/plphys/kiae139

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Several starch synthesis regulators have been identified, but these regulators are situated in the terminus of the regulatory network. Their upstream regulators and the complex regulatory network formed between these regulators remain largely unknown. A previous study demonstrated that NAM, ATAF, and CUC (NAC) transcription factors, OsNAC20 and OsNAC26 (OsNAC20/26), redundantly and positively regulate the accumulation of storage material in rice ( Oryza sativa ) endosperm. In this study, we detected OsNAC25 as an upstream regulator and interacting protein of OsNAC20/26. Both OsNAC25 mutation and OE resulted in a chalky seed phenotype, decreased starch content, and reduced expression of starch synthesis–related genes, but the mechanisms were different. In the osnac25 mutant, decreased expression of OsNAC20 / 26 resulted in reduced starch synthesis; however, in OsNAC25 -overexpressing plants, the OsNAC25–OsNAC20/26 complex inhibited OsNAC20/26 binding to the promoter of starch synthesis–related genes. In addition, OsNAC20/26 positively regulated OsNAC25 . Therefore, the mutual regulation between OsNAC25 and OsNAC20/26 forms a positive regulatory loop to stimulate the expression of starch synthesis–related genes and meet the great demand for starch accumulation in the grain filling stage. Simultaneously, a negative regulatory loop forms among the 3 proteins to avoid the excessive expression of starch synthesis–related genes. Collectively, our findings demonstrate that both promotion and inhibition mechanisms between OsNAC25 and OsNAC20/26 are essential for maintaining stable expression of starch synthesis–related genes and normal starch accumulation.

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