Rhizogenic Agrobacterium protein RolB interacts with the TOPLESS repressor proteins to reprogram plant immunity and development.

Rhizogenic Agrobacterium strains comprise biotrophic pathogens that cause hairy root disease (HRD) on hydroponically grown Solanaceae and Cucurbitaceae crops, besides being widely explored agents for the creation of hairy root cultures for the sustainable production of plant-specialized metabolites. Hairy root formation is mediated through the expression of genes encoded on the T-DNA of the root-inducing (Ri) plasmid, of which several, including root oncogenic locus B (rolB), play a major role in hairy root development. Despite decades of research, the exact molecular function of the proteins encoded by the rol genes remains enigmatic. Here, by means of TurboID-mediated proximity labeling in tomato (Solanum lycopersicum) hairy roots, we identified the repressor proteins TOPLESS (TPL) and Novel Interactor of JAZ (NINJA) as direct interactors of RolB. Although these interactions allow RolB to act as a transcriptional repressor, our data hint at another in planta function of the RolB oncoprotein. Hence, by a series of plant bioassays, transcriptomic and DNA-binding site enrichment analyses, we conclude that RolB can mitigate the TPL functioning so that it leads to a specific and partial reprogramming of phytohormone signaling, immunity, growth, and developmental processes. Our data support a model in which RolB manipulates host transcription, at least in part, through interaction with TPL, to facilitate hairy root development. Thereby, we provide important mechanistic insights into this renowned oncoprotein in HRD.

MINI-AC: inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles.

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. Plant GRNs control transcriptional programs involved in growth, development, and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site (TFBS) information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFBS. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.

Transcriptional chronology reveals conserved genes involved in pennate diatom sexual reproduction.

Sexual reproduction is a major driver of adaptation and speciation in eukaryotes. In diatoms, siliceous microalgae with a unique cell size reduction-restitution life cycle and among the world's most prolific primary producers, sex also acts as the main mechanism for cell size restoration through the formation of an expanding auxospore. However, the molecular regulators of the different stages of sexual reproduction and size restoration are poorly explored. Here, we combined RNA sequencing with the assembly of a 55 Mbp reference genome for Cylindrotheca closterium to identify patterns of gene expression during different stages of sexual reproduction. These were compared with a corresponding transcriptomic time series of Seminavis robusta to assess the degree of expression conservation. Integrative orthology analysis revealed 138 one-to-one orthologues that are upregulated during sex in both species, among which 56 genes consistently upregulated during cell pairing and gametogenesis, and 11 genes induced when auxospores are present. Several early, sex-specific transcription factors and B-type cyclins were also upregulated during sex in other pennate and centric diatoms, pointing towards a conserved core regulatory machinery for meiosis and gametogenesis across diatoms. Furthermore, we find molecular evidence that the pheromone-induced cell cycle arrest is short-lived in benthic diatoms, which may be linked to their active mode of mate finding through gliding. Finally, we exploit the temporal resolution of our comparative analysis to report the first marker genes for auxospore identity called AAE1-3 ("Auxospore-Associated Expression"). Altogether, we introduce a multi-species model of the transcriptional dynamics during size restoration in diatoms and highlight conserved gene expression dynamics during different stages of sexual reproduction.

Dicer-like 3a mediates intergenerational resistance against root-knot nematodes in rice via hormone responses.

In a continuously changing and challenging environment, passing down the memory of encountered stress factors to offspring could provide an evolutionary advantage. In this study, we demonstrate the existence of "intergenerational acquired resistance" in the progeny of rice (Oryza sativa) plants attacked by the belowground parasitic nematode Meloidogyne graminicola. Transcriptome analyses revealed that genes involved in defense pathways are generally downregulated in progeny of nematode-infected plants under uninfected conditions but show a stronger induction upon nematode infection. This phenomenon was termed "spring loading" and depends on initial downregulation by the 24-nucleotide (nt) siRNA biogenesis gene dicer-like 3a (dcl3a) involved in the RNA-directed DNA methylation pathway. Knockdown of dcl3a led to increased nematode susceptibility and abolished intergenerational acquired resistance, as well as jasmonic acid/ethylene spring loading in the offspring of infected plants. The importance of ethylene signaling in intergenerational resistance was confirmed by experiments on a knockdown line of ethylene insensitive 2 (ein2b), which lacks intergenerational acquired resistance. Taken together, these data indicate a role for DCL3a in regulating plant defense pathways during both within-generation and intergenerational resistance against nematodes in rice.

Transcription factors KANADI 1, MYB DOMAIN PROTEIN 44, and PHYTOCHROME INTERACTING FACTOR 4 regulate long intergenic noncoding RNAs expressed in Arabidopsis roots.

Thousands of long intergenic noncoding RNAs (lincRNAs) have been identified in plant genomes. While some lincRNAs have been characterized as important regulators in different biological processes, little is known about the transcriptional regulation for most plant lincRNAs. Through the integration of 8 annotation resources, we defined 6,599 high-confidence lincRNA loci in Arabidopsis (Arabidopsis thaliana). For lincRNAs belonging to different evolutionary age categories, we identified major differences in sequence and chromatin features, as well as in the level of conservation and purifying selection acting during evolution. Spatiotemporal gene expression profiles combined with transcription factor (TF) chromatin immunoprecipitation (ChIP) data were used to construct a TF-lincRNA regulatory network containing 2,659 lincRNAs and 15,686 interactions. We found that properties characterizing lincRNA expression, conservation, and regulation differ between plants and animals. Experimental validation confirmed the role of 3 TFs, KANADI 1, MYB DOMAIN PROTEIN 44, and PHYTOCHROME INTERACTING FACTOR 4, as key regulators controlling root-specific lincRNA expression, demonstrating the predictive power of our network. Furthermore, we identified 58 lincRNAs, regulated by these TFs, showing strong root cell type-specific expression or chromatin accessibility, which are linked with genome-wide association studies genetic associations related to root system development and growth. The multilevel genome-wide characterization covering chromatin state information, promoter conservation, and chromatin immunoprecipitation-based TF binding, for all detectable lincRNAs across 769 expression samples, permits rapidly defining the biological context and relevance of Arabidopsis lincRNAs through regulatory networks.

Plant lineage-specific PIKMIN1 drives APC/CCCS52A2 E3-ligase activity-dependent cell division.

The anaphase-promoting complex/cyclosome (APC/C) marks key cell cycle proteins for proteasomal breakdown, thereby ensuring unidirectional progression through the cell cycle. Its target recognition is temporally regulated by activating subunits, one of which is called CELL CYCLE SWITCH 52 A2 (CCS52A2). We sought to expand the knowledge on the APC/C by using the severe growth phenotypes of CCS52A2-deficient Arabidopsis (Arabidopsis thaliana) plants as a readout in a suppressor mutagenesis screen, resulting in the identification of the previously undescribed gene called PIKMIN1 (PKN1). PKN1 deficiency rescues the disorganized root stem cell phenotype of the ccs52a2-1 mutant, whereas an excess of PKN1 inhibits the growth of ccs52a2-1 plants, indicating the need for control of PKN1 abundance for proper development. Accordingly, the lack of PKN1 in a wild-type background negatively impacts cell division, while its systemic overexpression promotes proliferation. PKN1 shows a cell cycle phase-dependent accumulation pattern, localizing to microtubular structures, including the preprophase band, the mitotic spindle, and the phragmoplast. PKN1 is conserved throughout the plant kingdom, with its function in cell division being evolutionarily conserved in the liverwort Marchantia polymorpha. Our data thus demonstrate that PKN1 represents a novel, plant-specific protein with a role in cell division that is likely proteolytically controlled by the CCS52A2-activated APC/C.

Arabidopsis transcription factor ANAC102 predominantly expresses a nuclear protein and acts as a negative regulator of methyl viologen-induced oxidative stress responses.

Plants, being sessile organisms, constantly need to respond to environmental stresses, often leading to the accumulation of reactive oxygen species (ROS). While ROS can be harmful, they also act as second messengers guiding plant growth and stress responses. Because chloroplasts are sensitive to environmental changes and are both a source and a target of ROS during stress conditions, they are important in conveying environmental changes to the nucleus, where acclimation responses are coordinated to maintain organellar and overall cellular homeostasis. ANAC102 has previously been established as a regulator of ß-cyclocitral-mediated chloroplast-to-nucleus signaling, protecting plants against photooxidative stress. However, debates persist about where ANAC102 is located-in chloroplasts or in the nucleus. Our study, utilizing the genomic ANAC102 sequence driven by its native promoter, establishes ANAC102 primarily as a nuclear protein, lacking a complete N-terminal chloroplast-targeting peptide. Moreover, our research reveals the sensitivity of plants overexpressing ANAC102 to severe superoxide-induced chloroplast oxidative stress. Transcriptome analysis unraveled a dual role of ANAC102 in negatively and positively regulating genome-wide transcriptional responses to chloroplast oxidative stress. Through the integration of published data and our own study, we constructed a comprehensive transcriptional network, which suggests that ANAC102 exerts direct and indirect control over transcriptional responses through downstream transcription factor networks, providing deeper insights into the ANAC102-mediated regulatory landscape during oxidative stress.

Application of orthology and network biology to infer gene functions in non-model plants.

Approximately 60% of the genes and gene products in the model species Arabidopsis thaliana have been functionally characterized. In non-model plant species, the functional annotation of the gene space is largely based on homology, with the assumption that genes with shared common ancestry have conserved functions. However, the wide variety in possible morphological, physiological, and ecological differences between plant species gives rise to many species- and clade-specific genes, for which this transfer of knowledge is not possible. Other complications, such as difficulties with genetic transformation, the absence of large-scale mutagenesis methods, and long generation times, further lead to the slow characterization of genes in non-model species. Here, we discuss different resources that integrate plant gene function information. Different approaches that support the functional annotation of gene products, based on orthology or network biology, are described. While sequence-based tools to characterize the functional landscape in non-model species are maturing and becoming more readily available, easy-to-use network-based methods inferring plant gene functions are not as prevalent and have limited functionality.

An Improved Chromosome-scale Genome Assembly and Population Genetics resource for Populus tremula.

Aspen (Populus tremula L.) is a keystone species and a model system for forest tree genomics. We present an updated resource comprising a chromosome-scale assembly, population genetics and genomics data. Using the resource, we explore the genetic basis of natural variation in leaf size and shape, traits with complex genetic architecture. We generated the genome assembly using long-read sequencing, optical and high-density genetic maps. We conducted whole-genome resequencing of the Umeå Aspen (UmAsp) collection. Using the assembly and re-sequencing data from the UmAsp, Swedish Aspen (SwAsp) and Scottish Aspen (ScotAsp) collections we performed genome-wide association analyses (GWAS) using Single Nucleotide Polymorphisms (SNPs) for 26 leaf physiognomy phenotypes. We conducted Assay of Transposase Accessible Chromatin sequencing (ATAC-Seq), identified genomic regions of accessible chromatin, and subset SNPs to these regions, improving the GWAS detection rate. We identified candidate long non-coding RNAs in leaf samples, quantified their expression in an updated co-expression network, and used this to explore the functions of candidate genes identified from the GWAS. A GWAS found SNP associations for seven traits. The associated SNPs were in or near genes annotated with developmental functions, which represent candidates for further study. Of particular interest was a ~177-kbp region harbouring associations with several leaf phenotypes in ScotAsp. We have incorporated the assembly, population genetics, genomics, and GWAS data into the PlantGenIE.org web resource, including updating existing genomics data to the new genome version, to enable easy exploration and visualisation. We provide all raw and processed data to facilitate reuse in future studies.

PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants.

PLAZA is a platform for comparative, evolutionary, and functional plant genomics. It makes a broad set of genomes, data types and analysis tools available to researchers through a user-friendly website, an API, and bulk downloads. In this latest release of the PLAZA platform, we are integrating a record number of 134 high-quality plant genomes, split up over two instances: PLAZA Dicots 5.0 and PLAZA Monocots 5.0. This number of genomes corresponds with a massive expansion in the number of available species when compared to PLAZA 4.0, which offered access to 71 species, a 89% overall increase. The PLAZA 5.0 release contains information for 5 882 730 genes, and offers pre-computed gene families and phylogenetic trees for 5 274 684 protein-coding genes. This latest release also comes with a set of new and updated features: a new BED import functionality for the workbench, improved interactive visualizations for functional enrichments and genome-wide mapping of gene sets, and a fully redesigned and extended API. Taken together, this new version offers extended support for plant biologists working on different families within the green plant lineage and provides an efficient and versatile toolbox for plant genomics. All PLAZA releases are accessible from the portal website: https://bioinformatics.psb.ugent.be/plaza/.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Diatom adhesive trail proteins acquired by horizontal gene transfer from bacteria serve as primers for marine biofilm formation.

Biofilm-forming benthic diatoms are key primary producers in coastal habitats, where they frequently dominate sunlit intertidal substrata. The development of gliding motility in raphid diatoms was a key molecular adaptation that contributed to their evolutionary success. However, the structure-function correlation between diatom adhesives utilized for gliding and their relationship to the extracellular matrix that constitutes the diatom biofilm is unknown. Here, we have used proteomics, immunolocalization, comparative genomics, phylogenetics and structural homology analysis to investigate the evolutionary history and function of diatom adhesive proteins. Our study identified eight proteins from the adhesive trails of Craspedostauros australis, of which four form a new protein family called Trailins that contain an enigmatic Choice-of-Anchor A (CAA) domain, which was acquired through horizontal gene transfer from bacteria. Notably, the CAA-domain shares a striking structural similarity with one of the most widespread domains found in ice-binding proteins (IPR021884). Our work offers new insights into the molecular basis for diatom biofilm formation, shedding light on the function and evolution of diatom adhesive proteins. This discovery suggests that there is a transition in the composition of biomolecules required for initial surface colonization and those utilized for 3D biofilm matrix formation.

Identification of growth regulators using cross-species network analysis in plants.

With the need to increase plant productivity, one of the challenges plant scientists are facing is to identify genes that play a role in beneficial plant traits. Moreover, even when such genes are found, it is generally not trivial to transfer this knowledge about gene function across species to identify functional orthologs. Here, we focused on the leaf to study plant growth. First, we built leaf growth transcriptional networks in Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and aspen (Populus tremula). Next, known growth regulators, here defined as genes that when mutated or ectopically expressed alter plant growth, together with cross-species conserved networks, were used as guides to predict novel Arabidopsis growth regulators. Using an in-depth literature screening, 34 out of 100 top predicted growth regulators were confirmed to affect leaf phenotype when mutated or overexpressed and thus represent novel potential growth regulators. Globally, these growth regulators were involved in cell cycle, plant defense responses, gibberellin, auxin, and brassinosteroid signaling. Phenotypic characterization of loss-of-function lines confirmed two predicted growth regulators to be involved in leaf growth (NPF6.4 and LATE MERISTEM IDENTITY2). In conclusion, the presented network approach offers an integrative cross-species strategy to identify genes involved in plant growth and development.

TRAPID 2.0: a web application for taxonomic and functional analysis of de novo transcriptomes.

Advances in high-throughput sequencing have resulted in a massive increase of RNA-Seq transcriptome data. However, the promise of rapid gene expression profiling in a specific tissue, condition, unicellular organism or microbial community comes with new computational challenges. Owing to the limited availability of well-resolved reference genomes, de novo assembled (meta)transcriptomes have emerged as popular tools for investigating the gene repertoire of previously uncharacterized organisms. Yet, despite their potential, these datasets often contain fragmented or contaminant sequences, and their analysis remains difficult. To alleviate some of these challenges, we developed TRAPID 2.0, a web application for the fast and efficient processing of assembled transcriptome data. The initial processing phase performs a global characterization of the input data, providing each transcript with several layers of annotation, comprising structural, functional, and taxonomic information. The exploratory phase enables downstream analyses from the web application. Available analyses include the assessment of gene space completeness, the functional analysis and comparison of transcript subsets, and the study of transcripts in an evolutionary context. A comparison with similar tools highlights TRAPID's unique features. Finally, analyses performed within TRAPID 2.0 are complemented by interactive data visualizations, facilitating the extraction of new biological insights, as demonstrated with diatom community metatranscriptomes.

A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies.

Comparative functional genomics offers a powerful approach to study species evolution. To date, the majority of these studies have focused on the transcriptome in mammalian and yeast phylogenies. Here, we present a novel multi-species proteomic dataset and a computational pipeline to systematically compare the protein levels across multiple plant species. Globally we find that protein levels diverge according to phylogenetic distance but is more constrained than the mRNA level. Module-level comparative analysis of groups of proteins shows that proteins that are more highly expressed tend to be more conserved. To interpret the evolutionary patterns of conservation and divergence, we develop a novel network-based integrative analysis pipeline that combines publicly available transcriptomic datasets to define co-expression modules. Our analysis pipeline can be used to relate the changes in protein levels to different species-specific phenotypic traits. We present a case study with the rhizobia-legume symbiosis process that supports the role of autophagy in this symbiotic association.

Evolution of vascular plants through redeployment of ancient developmental regulators.

Vascular plants provide most of the biomass, food, and feed on earth, yet the molecular innovations that led to the evolution of their conductive tissues are unknown. Here, we reveal the evolutionary trajectory for the heterodimeric TMO5/LHW transcription factor complex, which is rate-limiting for vascular cell proliferation in Arabidopsis thaliana Both regulators have origins predating vascular tissue emergence, and even terrestrialization. We further show that TMO5 evolved its modern function, including dimerization with LHW, at the origin of land plants. A second innovation in LHW, coinciding with vascular plant emergence, conditioned obligate heterodimerization and generated the critical function in vascular development in Arabidopsis In summary, our results suggest that the division potential of vascular cells may have been an important factor contributing to the evolution of vascular plants.

Neoproterozoic origin and multiple transitions to macroscopic growth in green seaweeds.

The Neoproterozoic Era records the transition from a largely bacterial to a predominantly eukaryotic phototrophic world, creating the foundation for the complex benthic ecosystems that have sustained Metazoa from the Ediacaran Period onward. This study focuses on the evolutionary origins of green seaweeds, which play an important ecological role in the benthos of modern sunlit oceans and likely played a crucial part in the evolution of early animals by structuring benthic habitats and providing novel niches. By applying a phylogenomic approach, we resolve deep relationships of the core Chlorophyta (Ulvophyceae or green seaweeds, and freshwater or terrestrial Chlorophyceae and Trebouxiophyceae) and unveil a rapid radiation of Chlorophyceae and the principal lineages of the Ulvophyceae late in the Neoproterozoic Era. Our time-calibrated tree points to an origin and early diversification of green seaweeds in the late Tonian and Cryogenian periods, an interval marked by two global glaciations with strong consequent changes in the amount of available marine benthic habitat. We hypothesize that unicellular and simple multicellular ancestors of green seaweeds survived these extreme climate events in isolated refugia, and diversified in benthic environments that became increasingly available as ice retreated. An increased supply of nutrients and biotic interactions, such as grazing pressure, likely triggered the independent evolution of macroscopic growth via different strategies, including true multicellularity, and multiple types of giant-celled forms.

Multi-omics network-based functional annotation of unknown Arabidopsis genes.

Unraveling gene function is pivotal to understanding the signaling cascades that control plant development and stress responses. As experimental profiling is costly and labor intensive, there is a clear need for high-confidence computational annotation. In contrast to detailed gene-specific functional information, transcriptomics data are widely available for both model and crop species. Here, we describe a novel automated function prediction method, which leverages complementary information from multiple expression datasets by analyzing study-specific gene co-expression networks. First, we benchmarked the prediction performance on recently characterized Arabidopsis thaliana genes, and showed that our method outperforms state-of-the-art expression-based approaches. Next, we predicted biological process annotations for known (n = 15 790) and unknown (n = 11 865) genes in A. thaliana and validated our predictions using experimental protein-DNA and protein-protein interaction data (covering >220 000 interactions in total), obtaining a set of high-confidence functional annotations. Our method assigned at least one validated annotation to 5054 (42.6%) unknown genes, and at least one novel validated function to 3408 (53.0%) genes with computational annotations only. These omics-supported functional annotations shed light on a variety of developmental processes and molecular responses, such as flower and root development, defense responses to fungi and bacteria, and phytohormone signaling, and help fill the information gap on biological process annotations in Arabidopsis. An in-depth analysis of two context-specific networks, modeling seed development and response to water deprivation, shows how previously uncharacterized genes function within the respective networks. Moreover, our automated function prediction approach can be applied in future studies to facilitate gene discovery for crop improvement.

Diurnal transcript profiling of the diatom Seminavis robusta reveals adaptations to a benthic lifestyle.

Coastal regions contribute an estimated 20% of annual gross primary production in the oceans, despite occupying only 0.03% of their surface area. Diatoms frequently dominate coastal sediments, where they experience large variations in light regime resulting from the interplay of diurnal and tidal cycles. Here, we report on an extensive diurnal transcript profiling experiment of the motile benthic diatom Seminavis robusta. Nearly 90% (23 328) of expressed protein-coding genes and 66.9% (1124) of expressed long intergenic non-coding RNAs showed significant expression oscillations and are predominantly phasing at night with a periodicity of 24 h. Phylostratigraphic analysis found that rhythmic genes are enriched in highly conserved genes, while diatom-specific genes are predominantly associated with midnight expression. Integration of genetic and physiological cell cycle markers with silica depletion data revealed potential new silica cell wall-associated gene families specific to diatoms. Additionally, we observed 1752 genes with a remarkable semidiurnal (12-h) periodicity, while the expansion of putative circadian transcription factors may reflect adaptations to cope with highly unpredictable external conditions. Taken together, our results provide new insights into the adaptations of diatoms to the benthic environment and serve as a valuable resource for the study of diurnal regulation in photosynthetic eukaryotes.

Spatiotemporal expression profile of novel and known small RNAs throughout rice plant development focussing on seed tissues.

BACKGROUND: Small RNAs (sRNAs) regulate numerous plant processes directly related to yield, such as disease resistance and plant growth. To exploit this yield-regulating potential of sRNAs, the sRNA profile of one of the world's most important staple crops - rice - was investigated throughout plant development using next-generation sequencing. RESULTS: Root and leaves were investigated at both the vegetative and generative phase, and early-life sRNA expression was characterized in the embryo and endosperm. This led to the identification of 49,505 novel sRNAs and 5581 tRNA-derived sRNAs (tsRNAs). In all tissues, 24 nt small interfering RNAs (siRNAs) were highly expressed and associated with euchromatic, but not heterochromatic transposable elements. Twenty-one nt siRNAs deriving from genic regions in the endosperm were exceptionally highly expressed, mimicking previously reported expression levels of 24 nt siRNAs in younger endosperm samples. In rice embryos, sRNA content was highly diverse while tsRNAs were underrepresented, possibly due to snoRNA activity. Publicly available mRNA expression and DNA methylation profiles were used to identify putative siRNA targets in embryo and endosperm. These include multiple genes related to the plant hormones gibberellic acid and ethylene, and to seed phytoalexin and iron content. CONCLUSIONS: This work introduces multiple sRNAs as potential regulators of rice yield and quality, identifying them as possible targets for the continuous search to optimize rice production.