Organ-delimited gene regulatory networks provide high accuracy in candidate transcription factor selection across diverse processes.

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow the reconstruction of organ-level gene regulatory networks (GRNs). However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here, we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, and seed in Arabidopsis thaliana. A GRN inference approach was used to determine the: i. influential transcription factors (TFs) in each organ and, ii. most influential TFs for specific biological processes in that organ. These genome-wide, organ-delimited GRNs (OD-GRNs), recalled many known regulators of organ development and processes operating in those organs. Importantly, many previously unknown TF regulators were uncovered as potential regulators of these processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, an important food and biofuel trait. Of the top 20 predicted TFs, eight are known regulators of seed oil content, e.g., WRI1, LEC1, FUS3. Importantly, we validated our prediction of MybS2, TGA4, SPL12, AGL18, and DiV2 as regulators of seed lipid biosynthesis. We elucidated the molecular mechanism of MybS2 and show that it induces purple acid phosphatase family genes and lipid synthesis genes to enhance seed lipid content. This general approach has the potential to be extended to any species with sufficiently large gene expression datasets to find unique regulators of any trait-of-interest.

The genome of the Wollemi pine, a critically endangered "living fossil" unchanged since the Cretaceous, reveals extensive ancient transposon activity.

We present the genome of the living fossil, Wollemia nobilis, a southern hemisphere conifer morphologically unchanged since the Cretaceous. Presumed extinct until rediscovery in 1994, the Wollemi pine is critically endangered with less than 60 wild adults threatened by intensifying bushfires in the Blue Mountains of Australia. The 12 Gb genome is among the most contiguous large plant genomes assembled, with extremely low heterozygosity and unusual abundance of DNA transposons. Reduced representation and genome re-sequencing of individuals confirms a relictual population since the last major glacial/drying period in Australia, 120 ky BP. Small RNA and methylome sequencing reveal conservation of ancient silencing mechanisms despite the presence of thousands of active and abundant transposons, including some transferred horizontally to conifers from arthropods in the Jurassic. A retrotransposon burst 8-6 my BP coincided with population decline, possibly as an adaptation enhancing epigenetic diversity. Wollemia, like other conifers, is susceptible to Phytophthora, and a suite of defense genes, similar to those in loblolly pine, are targeted for silencing by sRNAs in leaves. The genome provides insight into the earliest seed plants, while enabling conservation efforts.

Chilling stress drives organ-specific transcriptional cascades and dampens diurnal oscillation in tomato.

Improving chilling tolerance in cold-sensitive crops, e.g. tomato, requires knowledge of the early molecular response to low temperature in these under-studied species. To elucidate early responding processes and regulators, we captured the transcriptional response at 30 minutes and 3 hours in the shoots and at 3 hours in the roots of tomato post-chilling from 24°C to 4°C. We used a pre-treatment control and a concurrent ambient temperature control to reveal that majority of the differential expression between cold and ambient conditions is due to severely compressed oscillation of a large set of diurnally regulated genes in both the shoots and roots. This compression happens within 30 minutes of chilling, lasts for the duration of cold treatment, and is relieved within 3 hours of return to ambient temperatures. Our study also shows that the canonical ICE1/CAMTA-to-CBF cold response pathway is active in the shoots, but not in the roots. Chilling stress induces synthesis of known cryoprotectants (trehalose and polyamines), in a CBF-independent manner, and induction of multiple genes encoding proteins of photosystems I and II. This study provides nuanced insights into the organ-specific response in a chilling sensitive plant, as well as the genes influenced by an interaction of chilling response and the circadian clock.

CAND1 is required for pollen viability in Arabidopsis thaliana-a test of the adaptive exchange hypothesis.

The dynamic assembly of SKP1•CUL1•F-box protein (SCF) ubiquitin ligases is important for protein ubiquitination and degradation. This process is enabled by CAND1, which exchanges F-box proteins associated with the common CUL1 scaffold, and thereby, recycles the limited CUL1 core and allows diverse F-box proteins to assemble active SCFs. Previous human cell biological and computational studies have led to the adaptive exchange hypothesis, which suggests that the CAND1-mediated exchange confers plasticity on the SCF system, allowing cells to tolerate large variations in F-box protein expression. Here, we tested this hypothesis using Arabidopsis thaliana, a multicellular organism expressing hundreds of F-box protein genes at variable levels in different tissues. The cand1 null mutant in Arabidopsis is viable but produce almost no seeds. Bioinformatic, cell biological, and developmental analyses revealed that the low fertility in the cand1 mutant is associated with cell death in pollen, where the net expression of F-box protein genes is significantly higher than any other Arabidopsis tissue. In addition, we show that the transmission efficiency of the cand1 null allele was reduced through the male but not the female gametophyte. Our results suggest that CAND1 activity is essential in cells or tissues expressing high levels of F-box proteins. This finding is consistent with the proposed adaptive exchange hypothesis, demonstrating the necessity of the evolutionarily conserved CAND1-mediated exchange system in the development of a multicellular organism.

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience.

Current crop yield of the best ideotypes is stagnating and threatened by climate change. In this scenario, understanding wild plant adaptations in extreme ecosystems offers an opportunity to learn about new mechanisms for resilience. Previous studies have shown species specificity for metabolites involved in plant adaptation to harsh environments. Here, we combined multispecies ecological metabolomics and machine learning-based generalized linear model predictions to link the metabolome to the plant environment in a set of 24 species belonging to 14 families growing along an altitudinal gradient in the Atacama Desert. Thirty-nine common compounds predicted the plant environment with 79% accuracy, thus establishing the plant metabolome as an excellent integrative predictor of environmental fluctuations. These metabolites were independent of the species and validated both statistically and biologically using an independent dataset from a different sampling year. Thereafter, using multiblock predictive regressions, metabolites were linked to climatic and edaphic stressors such as freezing temperature, water deficit and high solar irradiance. These findings indicate that plants from different evolutionary trajectories use a generic metabolic toolkit to face extreme environments. These core metabolites, also present in agronomic species, provide a unique metabolic goldmine for improving crop performances under abiotic pressure.

Plant ecological genomics at the limits of life in the Atacama Desert.

The Atacama Desert in Chile-hyperarid and with high-ultraviolet irradiance levels-is one of the harshest environments on Earth. Yet, dozens of species grow there, including Atacama-endemic plants. Herein, we establish the Talabre-Lejía transect (TLT) in the Atacama as an unparalleled natural laboratory to study plant adaptation to extreme environmental conditions. We characterized climate, soil, plant, and soil-microbe diversity at 22 sites (every 100 m of altitude) along the TLT over a 10-y period. We quantified drought, nutrient deficiencies, large diurnal temperature oscillations, and pH gradients that define three distinct vegetational belts along the altitudinal cline. We deep-sequenced transcriptomes of 32 dominant plant species spanning the major plant clades, and assessed soil microbes by metabarcoding sequencing. The top-expressed genes in the 32 Atacama species are enriched in stress responses, metabolism, and energy production. Moreover, their root-associated soils are enriched in growth-promoting bacteria, including nitrogen fixers. To identify genes associated with plant adaptation to harsh environments, we compared 32 Atacama species with the 32 closest sequenced species, comprising 70 taxa and 1,686,950 proteins. To perform phylogenomic reconstruction, we concatenated 15,972 ortholog groups into a supermatrix of 8,599,764 amino acids. Using two codon-based methods, we identified 265 candidate positively selected genes (PSGs) in the Atacama plants, 64% of which are located in Pfam domains, supporting their functional relevance. For 59/184 PSGs with an Arabidopsis ortholog, we uncovered functional evidence linking them to plant resilience. As some Atacama plants are closely related to staple crops, these candidate PSGs are a "genetic goldmine" to engineer crop resilience to face climate change.

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships.

Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we address in this study. We applied an evolutionarily informed machine learning approach to predict phenotypes based on transcriptome responses shared both within and across species. Specifically, we exploited the phenotypic diversity in nitrogen use efficiency and evolutionarily conserved transcriptome responses to nitrogen treatments across Arabidopsis accessions and maize varieties. We demonstrate that using evolutionarily conserved nitrogen responsive genes is a biologically principled approach to reduce the feature dimensionality in machine learning that ultimately improved the predictive power of our gene-to-trait models. Further, we functionally validated seven candidate transcription factors with predictive power for NUE outcomes in Arabidopsis and one in maize. Moreover, application of our evolutionarily informed pipeline to other species including rice and mice models underscores its potential to uncover genes affecting any physiological or clinical traits of interest across biology, agriculture, or medicine.

A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants.

Upon sensing developmental or environmental cues, epigenetic regulators transform the chromatin landscape of a network of genes to modulate their expression and dictate adequate cellular and organismal responses. Knowledge of the specific biological processes and genomic loci controlled by each epigenetic regulator will greatly advance our understanding of epigenetic regulation in plants. To facilitate hypothesis generation and testing in this domain, we present EpiNet, an extensive gene regulatory network (GRN) featuring epigenetic regulators. EpiNet was enabled by (i) curated knowledge of epigenetic regulators involved in DNA methylation, histone modification, chromatin remodeling, and siRNA pathways; and (ii) a machine-learning network inference approach powered by a wealth of public transcriptome datasets. We applied GENIE3, a machine-learning network inference approach, to mine public Arabidopsis transcriptomes and construct tissue-specific GRNs with both epigenetic regulators and transcription factors as predictors. The resultant GRNs, named EpiNet, can now be intersected with individual transcriptomic studies on biological processes of interest to identify the most influential epigenetic regulators, as well as predicted gene targets of the epigenetic regulators. We demonstrate the validity of this approach using case studies of shoot and root apical meristem development.

Transient genome-wide interactions of the master transcription factor NLP7 initiate a rapid nitrogen-response cascade.

Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq). The transient TF-target interactions captured uncover the early mode-of-action of NIN-LIKE PROTEIN 7 (NLP7), a master regulator of the nitrogen signaling pathway in plants. These transient NLP7 targets captured in root cells using temporal TF perturbation account for 50% of NLP7-regulated genes not detectably bound by NLP7 in planta. Rapid and transient NLP7 binding activates early nitrogen response TFs, which we validate to amplify the NLP7-initiated transcriptional cascade. Our approaches to capture transient TF-target interactions genome-wide can be applied to validate dynamic GRN models for any pathway or organism of interest.

Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions.

Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF1-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF2 targets, which in turn regulate 76% and 87% of TF1 indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system.

Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO3- uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine.

"Hit-and-Run" transcription: de novo transcription initiated by a transient bZIP1 "hit" persists after the "run".

BACKGROUND: Dynamic transcriptional regulation is critical for an organism's response to environmental signals and yet remains elusive to capture. Such transcriptional regulation is mediated by master transcription factors (TF) that control large gene regulatory networks. Recently, we described a dynamic mode of TF regulation named "hit-and-run". This model proposes that master TF can interact transiently with a set of targets, but the transcription of these transient targets continues after the TF dissociation from the target promoter. However, experimental evidence validating active transcription of the transient TF-targets is still lacking. RESULTS: Here, we show that active transcription continues after transient TF-target interactions by tracking de novo synthesis of RNAs made in response to TF nuclear import. To do this, we introduced an affinity-labeled 4-thiouracil (4tU) nucleobase to specifically isolate newly synthesized transcripts following conditional TF nuclear import. Thus, we extended the TARGET system (Transient Assay Reporting Genome-wide Effects of Transcription factors) to include 4tU-labeling and named this new technology TARGET-tU. Our proof-of-principle example is the master TF Basic Leucine Zipper 1 (bZIP1), a central integrator of metabolic signaling in plants. Using TARGET-tU, we captured newly synthesized mRNAs made in response to bZIP1 nuclear import at a time when bZIP1 is no longer detectably bound to its target. Thus, the analysis of de novo transcripomics demonstrates that bZIP1 may act as a catalyst TF to initiate a transcriptional complex ("hit"), after which active transcription by RNA polymerase continues without the TF being bound to the gene promoter ("run"). CONCLUSION: Our findings provide experimental proof for active transcription of transient TF-targets supporting a "hit-and-run" mode of action. This dynamic regulatory model allows a master TF to catalytically propagate rapid and broad transcriptional responses to changes in environment. Thus, the functional read-out of de novo transcripts produced by transient TF-target interactions allowed us to capture new models for genome-wide transcriptional control.

"Hit-and-Run" leaves its mark: catalyst transcription factors and chromatin modification.

Understanding how transcription factor (TF) binding is related to gene regulation is a moving target. We recently uncovered genome-wide evidence for a "Hit-and-Run" model of transcription. In this model, a master TF "hits" a target promoter to initiate a rapid response to a signal. As the "hit" is transient, the model invokes recruitment of partner TFs to sustain transcription over time. Following the "run", the master TF "hits" other targets to propagate the response genome-wide. As such, a TF may act as a "catalyst" to mount a broad and acute response in cells that first sense the signal, while the recruited TF partners promote long-term adaptive behavior in the whole organism. This "Hit-and-Run" model likely has broad relevance, as TF perturbation studies across eukaryotes show small overlaps between TF-regulated and TF-bound genes, implicating transient TF-target binding. Here, we explore this "Hit-and-Run" model to suggest molecular mechanisms and its biological relevance.

From milliseconds to lifetimes: tracking the dynamic behavior of transcription factors in gene networks.

Modeling dynamic gene regulatory networks (GRNs) is a new frontier in systems biology. It has special implications for plants, whose survival requires rapid deployment of GRNs in response to environmental changes. However, capturing and dissecting transient interactions of transcription factors (TFs) and their targets in GRNs remains a considerable experimental challenge. Here we review recent progress in understanding GRNs as a function of time and discuss the relevance of these findings in plants to studies in other eukaryotes. We cover progress in profiling and modeling time-course transcriptome changes across plant species and the insights they have provided into the regulatory mechanisms underlying these temporal transcriptional responses, with a focus on the dynamic behavior of TFs. Lastly, we review state-of-the-art techniques to monitor the single-molecule dynamics of TFs in vivo. Together, these advances have helped develop new models for dynamic transcriptional control with relevance across eukaryotes.

Comparative phylogenomics uncovers the impact of symbiotic associations on host genome evolution.

Mutualistic symbioses between eukaryotes and beneficial microorganisms of their microbiome play an essential role in nutrition, protection against disease, and development of the host. However, the impact of beneficial symbionts on the evolution of host genomes remains poorly characterized. Here we used the independent loss of the most widespread plant-microbe symbiosis, arbuscular mycorrhization (AM), as a model to address this question. Using a large phenotypic approach and phylogenetic analyses, we present evidence that loss of AM symbiosis correlates with the loss of many symbiotic genes in the Arabidopsis lineage (Brassicales). Then, by analyzing the genome and/or transcriptomes of nine other phylogenetically divergent non-host plants, we show that this correlation occurred in a convergent manner in four additional plant lineages, demonstrating the existence of an evolutionary pattern specific to symbiotic genes. Finally, we use a global comparative phylogenomic approach to track this evolutionary pattern among land plants. Based on this approach, we identify a set of 174 highly conserved genes and demonstrate enrichment in symbiosis-related genes. Our findings are consistent with the hypothesis that beneficial symbionts maintain purifying selection on host gene networks during the evolution of entire lineages.

Hit-and-run transcriptional control by bZIP1 mediates rapid nutrient signaling in Arabidopsis.

The dynamic nature of gene regulatory networks allows cells to rapidly respond to environmental change. However, the underlying temporal connections are missed, even in kinetic studies, as transcription factor (TF) binding within at least one time point is required to identify primary targets. The TF-regulated but unbound genes are dismissed as secondary targets. Instead, we report that these genes comprise transient TF-target interactions most relevant to rapid signal transduction. We temporally perturbed a master TF (Basic Leucine Zipper 1, bZIP1) and the nitrogen (N) signal it transduces and integrated TF regulation and binding data from the same cell samples. Our enabling approach could identify primary TF targets based solely on gene regulation, in the absence of TF binding. We uncovered three classes of primary TF targets: (i) poised (TF-bound but not TF-regulated), (ii) stable (TF-bound and TF-regulated), and (iii) transient (TF-regulated but not TF-bound), the largest class. Unexpectedly, the transient bZIP1 targets are uniquely relevant to rapid N signaling in planta, enriched in dynamic N-responsive genes, and regulated by TF and N signal interactions. These transient targets include early N responders nitrate transporter 2.1 and NIN-like protein 3, bound by bZIP1 at 1-5 min, but not at later time points following TF perturbation. Moreover, promoters of these transient targets are uniquely enriched with cis-regulatory motifs coinherited with bZIP1 binding sites, suggesting a recruitment role for bZIP1. This transient mode of TF action supports a classic, but forgotten, "hit-and-run" transcription model, which enables a "catalyst TF" to activate a large set of targets within minutes of signal perturbation.

A survey of the small RNA population during far-red light-induced apical hook opening.

Photomorphogenesis is a mechanism employed by plants to regulate their architecture and developmental program in response to light conditions. As they emerge into light for the first time, dark-grown seedlings employ a rapid and finely-controlled photomorphogenic signaling network. Small RNAs have increasingly been revealed to play an important role in regulating multiple aspects of plant development, by modulating the stability of mRNAs. The rapid alteration of the mRNA transcriptome is a known hallmark of the de-etiolation response, thus we investigated the small RNA transcriptome during this process in specific seedling tissues. Here we describe a survey of the small RNA expression profile in four tissues of etiolated soybean seedlings, the cotyledons, hypocotyl and the convex and concave sides of the apical hook. We also investigate how this profile responds to a 1-h far-red light treatment. Our data suggests that miRNAs show a different global profile between these tissues and treatments, suggesting a possible role for tissue- and treatment-specific expression in the differential morphology of the seedling on de-etiolation. Further evidence for the role of miRNA in light-regulated development is given by the de-etiolation responses of a hypomorphic ago1 mutant, which displays reduced and delayed photomorphogenic responses in apical hook and cotyledon angle to far-red light.

A unified nomenclature of NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER family members in plants.

Members of the plant NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER (NRT1/PTR) family display protein sequence homology with the SLC15/PepT/PTR/POT family of peptide transporters in animals. In comparison to their animal and bacterial counterparts, these plant proteins transport a wide variety of substrates: nitrate, peptides, amino acids, dicarboxylates, glucosinolates, IAA, and ABA. The phylogenetic relationship of the members of the NRT1/PTR family in 31 fully sequenced plant genomes allowed the identification of unambiguous clades, defining eight subfamilies. The phylogenetic tree was used to determine a unified nomenclature of this family named NPF, for NRT1/PTR FAMILY. We propose that the members should be named accordingly: NPFX.Y, where X denotes the subfamily and Y the individual member within the species.

The inheritance pattern of 24 nt siRNA clusters in arabidopsis hybrids is influenced by proximity to transposable elements.

Hybrids often display increased size and growth, and thus are widely cultivated in agriculture and horticulture. Recent discoveries demonstrating the important regulatory roles of small RNAs have greatly improved our understanding of many basic biological questions, and could illuminate the molecular basis for the enhanced growth and size of hybrid plants. We profiled small RNAs by deep sequencing to characterize the inheritance patterns of small RNA levels in reciprocal hybrids of two Arabidopsis thaliana accessions, Columbia and Landsberg erecta. We find 24-nt siRNAs predominate among those small RNAs that are differentially expressed between the parents. Following hybridization, the transposable element (TE)-derived siRNAs are often inherited in an additive manner, whereas siRNAs associated with protein-coding genes are often down-regulated in hybrids to the levels observed for the parent with lower relative siRNA levels. Among the protein-coding genes that exhibit this pattern, genes that function in pathogen defense, abiotic stress tolerance, and secondary metabolism are significantly enriched. Small RNA clusters from protein-coding genes where a TE is present within one kilobase show a different predominant inheritance pattern (additive) from those that do not (low-parent dominance). Thus, down-regulation in the form of low-parent dominance is likely the default pattern of inheritance for genic siRNA, and a different inheritance mechanism for TE siRNA is suggested.

Divergent patterns of endogenous small RNA populations from seed and vegetative tissues of Glycine max.

BACKGROUND: Small non-coding RNAs (smRNAs) are known to have major roles in gene regulation in eukaryotes. In plants, knowledge of the biogenesis and mechanisms of action of smRNA classes including microRNAs (miRNAs), short interfering RNAs (siRNAs), and trans-acting siRNAs (tasiRNAs) has been gained mostly through studies with Arabidopsis. In recent years, high throughput sequencing of smRNA populations has enabled extension of knowledge from model systems to plants with larger, more complex genomes. Soybean (Glycine max) now has many genomics resources available including a complete genome sequence and predicted gene models. Relatively little is known, however, about the full complement of its endogenous smRNAs populations and the silenced genes. RESULTS: Using Illumina sequencing and computational analysis, we characterized eight smRNA populations from multiple tissues and organs of soybean including developing seed and vegetative tissues. A total of 41 million raw sequence reads collapsed into 135,055 unique reads were mapped to the soybean genome and its predicted cDNA gene models. Bioinformatic analyses were used to distinguish miRNAs and siRNAs and to determine their genomic origins and potential target genes. In addition, we identified two soybean TAS3 gene homologs, the miRNAs that putatively guide cleavage of their transcripts, and the derived tasiRNAs that could target soybean genes annotated as auxin response factors. Tissue-differential expression based on the flux of normalized miRNA and siRNA abundances in the eight smRNA libraries was evident, some of which was confirmed by smRNA blotting. Our global view of these smRNA populations also revealed that the size classes of smRNAs varied amongst different tissues, with the developing seed and seed coat having greater numbers of unique smRNAs of the 24-nt class compared to the vegetative tissues of germinating seedlings. The 24-nt class is known to be derived from repetitive elements including transposons. Detailed analysis of the size classes associated with ribosomal RNAs and transposable element families showed greater diversity of smRNAs in the 22- and 24-nt size classes. CONCLUSIONS: The flux of endogenous smRNAs within multiple stages and tissues of seed development was contrasted with vegetative tissues of soybean, one of the dominant sources of protein and oil in world markets. The smRNAs varied in size class, complexity of origins, and possible targets. Sequencing revealed tissue-preferential expression for certain smRNAs and expression differences among closely related miRNA family members.