Dynamic transcriptome landscape of oat grain development

doi:10.21203/rs.3.rs-5311808/v1

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Dynamic transcriptome landscape of oat grain development

https://doi.org/10.21203/rs.3.rs-5311808/v1

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Background Oats are widely consumed throughout the world because of their nutritive value, with their yield and quality being associated with the developmental process of grain development. However, the underlying molecular mechanisms of the transcriptional dynamics of this process have not yet been fully elucidated. In this study, RNA-seq was performed to investigate the transcriptional dynamics and identify the key genes involved in the development of the oat grain at four different developmental stages.

Results A total of 33,197 differentially expressed genes (DEGs), including 1,308 differentially expressed transcription factors (TFs) wereidentified. The main concern of this study was to include those genes associated with hormone signaling, and the sucrose and starch metabolism pathways.

Conclusions The results of this study provide valuable insights into the genetic resources affecting the molecular mechanism underlying the development of the oat grain, as well as establishing a strong theoretical foundation for its improvement.

oats

grain development

RNA-Seq

DEGs

starch

hormone

The common oat is an allohexaploid species, which is a global food and feed crop with important economic value. The two types of oat grain, according to their morphology, are hulled and naked [1]. The seeds with their high nutritional value, including dietary fiber, and their unique flavor have long been cherished by consumers [2, 3]. However, the planting area and total yield are significantly lower than those of other staple food crops such as maize, wheat, and rice. Therefore, attention should be paid to improving oat yield and quality. Recently, with the rapid development of high-throughput sequencing technology and genome assembly technology, information on the genome sequence of high-quality diploid, tetraploid and hexaploid oats is now available, leading to improvements in the understanding of the basic biology of oats [4, 5]. These advancements have provided valuable resources for improving the genetics and yield of oats.

Grain development is related to seed setting, grain weight, yield, and quality [6]. This process is influenced by various factors such as the delivery of photosynthetic products, transportation of stored substances, transport tissues and physiological activities of the grains themselves, regulation of various plant hormones, restriction of various environmental factors, and regulation of related genes [7–11]. Transcriptome sequencing has become an effective approach to study the dynamic changes in gene expression during grain development in different plant species [12–14] such as tree peony [15], buckwheat [16], maize [17], soybean [14], Brassica napus [14] and Euryale ferox Salisb. [18] and has identified large numbers of related regulatory and functional genes. However, the formation mechanism during grain ripening has not been extensively studied, especially the changes in the transcription networks between the grain-filling stage and the maturity stage of oats.

Starch is recognized as a pivotal factor influencing both the yield and quality of cereal grains [19]. The development of grains represents a crucial phase in the accumulation of nutrients, predominantly occurring in the starchy endosperm and the aleurone layer [20]. During seed development, the accumulation of nutrients involves various enzymes, such as sucrose synthase (SUS), alpha trehalose phosphate synthase (TPS), trehalose phosphate phosphatase (TPP), alpha-amylase isozyme (AMY), and starch-branching enzyme (SBE). These enzymes play distinct roles at different stages of seed development, contributing to the metabolic pathways that lead to the accumulation of sugars such as sucrose, and starch [21, 22]. Studies have shown that the low activity of crucial enzymes participating in sucrose-to-starch conversion within the kernels inhibits the grain-filling process [23].

Phytohormones are important signals in controlling seed development, maturation, and the accumulation of nutrients [24]. Nine phytohormones are known: auxin, gibberellin (GA), cytokinins (CTK), abscisic acid (ABA), ethylene, brassinosteroid (BR), jasmonic acid (JA), salicylic acid (SA), and strigolactones (SL) [25]. Increasing ethylene levels in developing seeds inhibits the accumulation and activities of starch synthesis-related enzymes, and further decreases the grain-filling rate [26]. ABA also regulates the sink activity during grain filling [27] and polyamines significantly promote the grain filling of inferior grain in wheat [28]. Studies have also identified 633 DEGs related to eight hormones in seed development, including 132 auxin [24]. From the analysis of five different developmental stages of buckwheat, 227 DEGs were identified, 185 of those being related to indole-3-acetic acid (IAA) [16]. Poor filling in the inferior spikelets was reported to be mainly caused by the lower auxin (IAA) concentrations in rice grains [29]. Overall, the intricate interplay of phytohormones is essential for optimal seed development and grain filling, with each hormone contributing uniquely to the process.

The present study aims to provide a comprehensive analysis of the transcriptome dynamics during the four key phases of oat seed development: the Filling Stage, the Milk Stage, the Dough Stage, and the Maturity Stage. By profiling the gene expression at these critical developmental intervals, we hope to uncover a multitude of gene activities and identify several gene sets with distinct spatial and temporal expressions. Our study focuses on transcription factors, hormone metabolic pathways, and the metabolism of starch and sucrose, which are crucial for understanding the underlying mechanisms of gene regulation during seed development. We will outline the dynamic regulatory network of grain development to offer insights into the molecular control of seed maturation and nutrient accumulation in oats.

Plant materials

Oats, of the Neiyou-6 (NY6) cultivar, were obtained from the Inner Mongolia Southern Breeding Base in Ledong County, Hainan Province, China. In February 2023, during ripening, when the grain color changed from green to yellow, we collected samples at different stages of ripening to include the Grain Filling Stage (T1), Milk Stage (T2), Dough Stage (T3), and Maturity Stage (T4) (Fig. 1A). The lemma and palea were dissected at a suitable development time and the berries were collected using clean tweezers, placed in Eppendorf tubes then immediately frozen in liquid nitrogen (1.5 g per replicate). Three biological replicates were taken at each stage for RNA-Seq analysis in this study. Each repeat comprised at least 150 berries collected from at least 15 plants. All samples were stored at −80 °C until use.

RNA extraction and Library preparation

The samples were extracted by Wuhan Metville Biotechnology Co., Ltd. (Wuhan, China). The total RNA of the samples was extracted using an RNAprep Pure Plant kit (DP441, Tiangen Biotech, Beijing, China). RNA degradation and contamination were monitored on 1%-agarose gels. The RNA purity was checked using the Nano Photometer spectrophotometer (Implen Inc., CA, USA).

A total amount of l ug RNA per sample was used as the input material for the RNA sample preparations. Sequencing libraries were generated using the NEBNextR UltraT MRNA Library Prep Kit for lllumina R (New England Biolabs, Ipswich, MA, USA) following the manufacturer's recommendations with index codes being added to the attribute sequences of each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEBNext First Strand Synthesis Reaction Buffer (5×). The First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H-). The Second strand cDNA synthesis was subsequently performed using DNA Polymerase l and RNase H. The remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of the 3' ends of the DNA fragments，NEBNext Adaptor with hairpin loop structure were ligated to prepare for hybridization. To preferentially select cDNA fragments 250~300 bp in length, the library fragments were purified using the AMPure XP system (Beckman Coulter, Beverly, MA, USA). Three µL of USER Enzyme (New England Biolabs) were used with size-selected, adaptor-ligated cDNA at 37 °C for 15 min followed by 5 min at 95 °C before PCR. PCR was performed using Phusion High Fidelity DNA polymerase, Universal PCR primers and Index (X) Primer. Finally, the PCR products were purified using the AMPure XP system with the library quality being assessed on the Bioanalyzer 2100 system (Agilent, Santa Clara, CA, USA).

The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (lllumina, San Diego, CA, USA) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an lllumina platform and 150 bp paired-end reads were generated.

RNA-seq data analysis

The data quality control used fastp to filter the original data, mainly to remove reads with adapters. When the N content in any sequencing reads exceeded 10% of the base number of the reads, the paired reads were removed. When any sequencing reads where the number of low-quality (Q <= 20) bases exceeded 50% of the bases of the reads, the paired reads were removed. All subsequent analyses were thus based on clean reads.

HISAT was used to construct the index, and compare the clean reads with the oat OT3098 reference genome (https://wheat.pw.usda.gov/GG3/graingenes-downloads/pepsico-oat-ot3098-v2-files-2021). StringTie was used for new gene prediction. FeatureCounts was used to calculate the gene alignment, and then to calculate the FPKM (Fragments Per Kilobase of transcript per Million mapped reads) of each gene based on the gene length. FPKM is currently the most commonly used method to estimate gene expression levels.

DESeq2 was used to analyze the differential expression between two groups, and the P value was corrected using the Benjamini & Hochberg method. The corrected P value and |log2foldchange| were used as the threshold for expressing a significant difference. The enrichment analysis was performed based on the hypergeometric test. For KEGG (Kyoto Encyclopedia of Genes and Genome), the hypergeometric distribution test was performed with the unit of pathway; for GO (Gene Ontology), it was performed based on the GO term. PCA (Principal component analysis), Hierarchical cluster, GO, and KEGG pathway enrichment analysis were performed using the Metware cloud analysis tools (https://cloud.metware.cn )

RNA-Seq analysis of oat grains at different stages of ripeness.

To gain insights into the dynamic changes occurring in gene expression during the stages of oat grain development, 12 libraries were constructed for RNA-Seq from the four developmental stages: Grain Filling Stage (T1), Milk Stage (T2), Dough Stage (T3), and Maturity Stage (T4) (Fig. 1A). The detailed sequencing data are shown in Supplemental Table S1. After removing the adaptor sequences and low-quality sequence reads, the clean reads of the 12 samples ranged from 39.63 to 70.35 million. Approximately 94.26% of the reads were mapped to the oat reference genome, and 74.33% of the reads could be mapped uniquely to the reference genome. The Q30 scores of all samples were > 94%. These data indicated that the quantity and quality of reads were sufficient to perform quantitative analyses of gene expression.

To understand the relationships between different groups, we used PCA on the full data set, to visually demonstrate the transcriptional features and developmental similarities (Fig. 1B): PC1 explained 41.82% of the total variance, and PC2, 17.54%. To evaluate the global gene expression profiles of the different samples, gene expression levels were assessed using FPKM, based on normalized read counts. Across these four stages, a total of 80,804 genes, 17,144 of which were new, were measured with different expression patterns during the four developmental stages of oats (Fig. 1C, Supplemental Table S2). On the basis of their expression levels, we classified these genes into four groups (Fig. 1D).

Identification and analysis of differentially expressed genes (DEGs)

We screened the DEGs at each stage, using the screening conditions of |log2Fold Change| ≥ 1 and FDR < 0.05. A total of 40,703 DEGs were identified then the expression level of each gene at the four developmental stages was compared (Fig. 2A, Supplemental Table S3). The largest number of DEGs was observed in T1 vs. T4, with a total of 33,197 DEGs, while the lowest number (7,286) was detected in T2 vs. T3. Generally, the further apart the stages were, the more DEGs they had [30].

A Venn diagram was created to identify the unique DEGs of each comparison. Fig. 2B shows a comparison of the DEGs among the 5 sets where 4,244, 312, 1,526, 2,032, and 362 unique DEGs were identified in the T1 vs. T4, T2 vs. T3, T3 vs. TT4, T2 vs. T4, and T1 vs. T2 comparison sets, respectively, with 890 DEGs being present in all comparison sets. These results suggested a temporal shift in transcript abundance for many expressed genes as the seeds developed, which might reflect the preceding morphological and/or metabolic changes during seed development.

When subjected to a KEGG pathway analysis for DEGs, the significantly enriched 20 pathways are shown in Fig. 2C. where the main pathways included starch and sucrose metabolism, galactose metabolism, fatty acid biosynthesis, and fatty acid metabolism. Substantial and significant enrichments were observed in both the metabolic pathways and the biosynthesis of secondary metabolites. These metabolic pathways shed light on the metabolic processes occurring during the development of oat grains, which is consistent with the results of previous studies [31].

Analysis of the temporal expression patterns of DEGs

Gene expression profile clustering was used to explore the temporal expression patterns of the identified DEGs during the grain filling of oats. The expression trends of all DEGs were sorted into 4 profiles (Fig. 3A-D): profile 1 (8,756 genes), profile 2 (16,427 genes), profile 3 (3,820 genes), and profile 4 (11,700 genes). Each profile represents a set of genes with a similar expression pattern during grain filling.

After KEGG pathway analysis, the 20 significantly enriched pathways are shown in Fig. 3E-H. In profile 1, the DNA replication, Glycosylphosphatidylinositol (GPI)-anchor biosynthesis, Plant hormone signal transduction, ABC transporters, and Starch and sucrose metabolism were the five dominant pathways. In profile 2, the Ribosome, Ribosome biogenesis in eukaryotes, Glutathione metabolism, Valine, leucine and isoleucine degradation, and Spliceosome were the five dominant pathways. In profile 3, the Phenylpropanoid biosynthesis, Starch and sucrose metabolism, Biosynthesis of various plant secondary metabolites, ABC transporters, Cyanoamino acid metabolism were the five dominant pathways. In profile 4, the Metabolic pathway, Carbon metabolism, Biosynthesis of secondary metabolism, Photosynthesis-antenna proteins and Fatty acid biosynthesis were the five dominant pathways.

Multiple TFs involved in oat grain development.

The expression dynamics of TFs during grain development were investigated. In at least one developmental stage, 2,790 TFs were detected, belonging to 65 families and other categories of TFs with 1,308 Differentially expressed TFs being identified (Fig. 4, Supplemental Table S4). The top five largest DEGs TF families were APETALA2/Ethylene Responsive Element Binding Factor (AP2/ERF-ERF)(100), FAR-RED IMPAIRED RESPONSE1(FAR1)(81), NAM-ATAF1-2-CUC2 (NAC) (81), v-myb avian myeloblastosis viral oncogene homolog-related (MYB-related)(76), and basic helix-loop-helix (bHLH) (65).

At the T1 stage, 392 TFs (transcription factors) were significantly highly expressed compared with the remaining three stages, with NAC accounting for 8.5%, MYB-related TF for 6.3%, bHLH for 4.3%, and bZIP for 43%, These TFs were assigned as T1 stage preferential genes. Only 36 TFs were significantly highly expressed at the T2 stage and were designated as milk stage predominantly expressed genes, with NAC accounting for 17.1%, and bHLH for 14.2%. At the T3 stage, 112 TFs were significantly highly expressed, with MYB-related accounting for 11.7%, MYB for 8.1%, and AP2/ERF-ERF for 7.2%. At the T4 stage, 454 TFs were significantly highly expressed, with AP2/ERF-ERF accounting for 13.4%, MYB-related for 7.9%, and WRKY for 5%, with these genes being designated as the main TFs expressed in this stage.

Genes enriched in the hormone signaling pathway during oat grain development.

Hormone signals play an important role in plant growth and development. Our results identified 398 DEGs associated with plant hormone signal transduction, including auxin, CTK, GA, JA, ABA, BR signaling pathways and others (Supplemental Table S5). These differentially expressed hormone-related genes suggest that the specific process of seed development for oats might be governed by the regulation of complex phytohormone signal pathways.

Of the phytohormones, auxin with 96 DEGs plays a crucial role in seed development [32]. Therefore, we focused primarily on those genes related to auxin signal transduction, including those participating in auxin biosynthesis, polar transport, and response [21]. Plasma membrane influx and efflux transporters mediate polar auxin transport, including eight LAX genes (Fig. 5A), The influx carrier genes AsLAXs was found to be up-regulated at the R stage, which agreed with previous studies [21]. It is worth noting that the tryptophan-dependent pathway is the primary pathway responsible for the production of IAA [33]. Our transcriptome data showed that of the 29 IAAs genes, 25 were preferentially expressed at the T1 stage, and 10 at the T2 stage (Fig. 5B). The Auxin response factor (ARF) [34] and Small Auxin-Up RNA (SAUR) families [35] are the most important family of auxin-responsive proteins, potentially playing an important role in the regulation of foxtail millet grain development and its response to abiotic stress. In the present study, 43 ARFs and 3 SAURs genes were found to be enriched during oat grain development (Fig. 5C, D). Three GH3s genes were markedly down-regulated at the T2 stage, while the expression of one GH3s gene gradually increased during oat grain development (Fig. 5E). The auxin gene exhibited higher expression levels during the T1 and T2 stages of seed development, which aligned with the faster cell division and expansion during these phases to form seeds of larger dimensions.

Sucrose and starch metabolism in oats during grain development

The conversion of sucrose to starch is the key process that affects grain development in crops[22]. In the present study, we identified 111 DEGs associated with starch and sucrose metabolism (Fig. 6), which included 18 SUS , 25 TPS , 12 TPP , 10 AMY , seven GLGB (1,4-alpha-glucan branching enzyme), four SSG (granule-bound starch synthase), 13 SSY (starch synthase), 10 GLGL/GLGS(glucose-1-phosphate adenylyltransferase), and four UGP2(UTP--glucose-1-phosphate uridylyltransferase). Of these, ten SUS, nine TPS, one TPP, seven AMY, six GLGB, four SSY, three SSG, ten GLGL/GLGS and three UGP2 were expressed with the highest levels at the T1 stage, and five SUS, six TPS, eight TPP, three SSY, and three SSG at the T4 stage. The expression of six SUS, eleven TPS, three TPP, nine AMY, six GLGB, three SSG, four SSY, ten GLGL/GLGS, and three UGP2 decreased during the development stage, while only the expression of five TPS and one SSY increased. A previous study has reported a programmed increase in methylation levels during seed development [36], possibly because the increased methylation level is related to the reduction in the seed transcriptome.

We have used transcriptome profiling to characterize four key stages of the seed development of the oat grain and presented a high-resolution global atlas of the transcriptional dynamics of oat seed development from grain filling to maturity. We have also elucidated the dynamic mechanisms of TFs, plant hormone signaling, and starch and sugar metabolism pathways. These findings suggest that different genes play different roles during grain development. These data will advance our understanding of seed spatiotemporal gene expression patterns and their regulation and hold the potential for supporting the identification of new targets for molecular breeding to improve oat seed yield and quality.

Research on expression regulation during different stages of seed development has achieved certain progress in soybeans [14, 37], millet [21], maize [17], buckwheat [16], wheat [7], sorghum [38], and other crops [15]. However, in comparison, relatively little research has been reported on oats. Although previous studies have analyzed the transcriptome at six developmental time points in oats, their primary focus was on β-glucan biosynthesis and accumulation [39], avenanthramides and lipid biosynthetic genes [40]. The present study has established a time-dynamic transcriptome of grain development in the oat NY6 cultivar and analyzed the integrated dynamic transcriptome of TFs, plant hormone signaling, and starch and sugar metabolism in grain development. This transcriptome provides valuable genetic resources for understanding the genetic control of grain development in oats. This comprehensive analysis also deepens our understanding of the changes in important metabolic pathways during oat grain development.

Seed development is a process governed by intricate and complex gene expression networks which involve numerous genes and regulatory elements that work together to ensure the proper growth and maturation of seeds. Seed development is regulated by numerous TFs, many of which have been extensively reported [21]. For example, transcriptome analyses of developing soybean seeds has revealed hub genes implicated in oil and protein accumulation. Opaque11 (O11), encoding bHLH TFs, is activated after pollination and regulates several biological processes during endosperm development in maize [41]. ZmNAC128 and ZmNAC130 are endosperm-specific TFs that affect starch biosynthesis and 16-kDa γ-zein content [42]. During the grain development process of millet, 509 TFs were identified [21]. In our RNA-Seq analysis, we discovered 1,308 differentially expressed TFs (Fig. 4). Although the roles of most of these seed-specific TFs are yet to be understood, the present study has uncovered enrichment within known regulatory families that are pivotal to seed development, such as NAC, ERF, AP2, MYB, and MYB_related. These findings fit in with previous research on the gene expression profiling during the grain-filling process of foxtail millet [13]. Our dynamic transcriptome analysis of TFs enables us to identify key regulators of seed development, and to gain insights into the mechanisms underlying grain development.

Phytohormones play an extremely crucial role in seed development. Until now, many plant hormone-related genes have been identified, including the auxin, CTK, GA, ABA, and BR signaling pathways. Of these phytohormones, auxin plays crucial roles in ovule and seed development [32]. Our transcriptome data has identified the preferential expression of auxin influx carriers, efflux carriers, and auxin response factors during early oat grain development, specifically at the grain filling and milk stages (Fig. 5). The genes related to auxins have higher expression levels during the early stages of seed development, a finding consistent with previous research [24]. Our research findings align with previous studies, indicating that the expression of most auxin-related genes is higher during the ovule and milk stages. Genes associated with the auxin signaling pathway may be valuable resources for oat molecular breeding.

Starch is the major form of carbohydrate accumulating in mature seeds and is the main nutrient making the seeds and other storage organs expand and enlarge. This involves a sophisticated interplay between sucrose metabolism and various tightly regulated pathways governed by many enzymes [43]. However, the oat starch biosynthesis genes remain largely unknown. In our study, we identified 111 DEGs associated with starch and sucrose metabolism (Fig. 6) with SUS, TPS, TPP, AMY and others being the key genes. SUS enhances hull size and grain weight by regulating cell division and starch accumulation in transgenic rice [44], and is expressed in endosperm tissue during early seed development. AMY, the major form of amylase, is critical for the formation of the storage starch granule during seed maturation and thus directly affects field yield in rice [45]. TPS and TPP play significant roles in starch metabolism in millet seed development [21]. The starch biosynthesis DEGs identified provide the expression patterns for starch biosynthesis genes in the seed development of oats, and would also accelerate their function analysis.

RNA-seq RNA sequencing

DEGs Differentially expressed genes

TFs Transcription factors

SUS Sucrose synthase

TPS Alpha trehalose phosphate synthase

TPP Trehalose alpha-amylase isozyme

SBE Starch-branching enzyme

GA Gibberellin99

CTK Cytokinins

ABA Abscisic acid

BR Brassinosteroid

JA Jasmonic acid

SA Salicylic acid

SL Strigolactones

IAA Indole-3-acetic acid

KEGG Kyoto Encyclopedia of Genes and Genome

GO Gene Ontology

PCA Principal component analysis

FPKM Fragments Per Kilobase of transcript per Million mapped reads

AP2/ERF-ERF APETALA2/Ethylene Responsive Element Binding Factor,

FAR1 FAR-RED IMPAIRED RESPONSE1

NAC NAM-ATAF1-2-CUC2

MYB-related v-myb avian myeloblastosis viral oncogene homolog- related

bHLH Basic helix-loop-helix

AUX/IAA Auxin-responsive protein IAA

ARFs Auxin response factors

GH3 Indole-3-acetic acid-amido synthetase (auxin-responsive GH3 gene family)

SAUR Small auxin up-regulated RNA (SAUR family protein)

LAXs Auxin transporter-like protein.

GLGB 1,4-alpha-glucan branching enzyme

SSG Granule-bound starch synthase

SSY Starch synthase

GLGL/GLGS Glucose-1-phosphate adenylyltransferase

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

Electronic supplementary material

Competing interests

The study authors certify that they have NO affiliations with, or involvement in, any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript.

Funding

This work was supported by the "Recruit Heroes to Tackle Key Tasks" project of the Grassland Science discipline at Inner Mongolia Agricultural University (No. YLXKZX-NND-003), and the Grassland Science Discipline Fund of Inner Mongolia Agricultural University (IMAUCXQJ2024001).

Authors' contributions

TW. Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Software, Writing – original draft, Writing – review & editing. BH. Resources, Validation, Data curation, Conceptualization, Supervision, Validation, Project administration, Funding acquisition.

Acknowledgments

We wish to express our sincere gratitude to the Key Laboratory of Grassland Germplasm Innovation and Sustainable Utilization of Grassland Resources in the Inner Mongolia Autonomous Region, the Key Laboratory of Forage Cultivation, Processing, and High-Efficient Utilization under the Ministry of Agriculture, and the Key Laboratory of Grassland Resources within the Ministry of Education's Integrated Key Research Platform for their invaluable support and significant contributions to this research. We thank Philip Creed, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn/), for editing the English text of a draft of this manuscript.

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Dynamic transcriptome landscape of oat grain development

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