Genome mining of metabolic gene clusters in the Rubiaceae family.

The Rubiaceae plant family, comprising 3 subfamilies and over 13,000 species, is known for producing significant bioactive compounds such as caffeine and monoterpene indole alkaloids. Despite an increase in available genomes from the Rubiaceae family over the past decade, a systematic analysis of the metabolic gene clusters (MGCs) encoded by these genomes has been lacking. In this study, we aim to identify and analyze metabolic gene clusters within complete Rubiaceae genomes through a comparative analysis of eight species. Applying two bioinformatics pipelines, we identified 2372 candidate MGCs, organized into 549 gene cluster families (GCFs). To enhance the reliability of these findings, we developed coexpression networks and conducted orthology analyses. Using genomic data from Solanum lycopersicum (Solanaceae) for comparative purposes, we provided a detailed view of predicted metabolic enzymes, pathways, and coexpression networks. We bring some examples of MGCs and GCFs involved in biological pathways of terpenes, saccharides and alkaloids. Such insights lay the groundwork for discovering new compounds and associated MGCs within the Rubiaceae family, with potential implications in developing more robust crop species and expanding the understanding of plant metabolism. This large-scale exploration also provides a new perspective on the evolution and structure-function relationship of these clusters, offering opportunities for the highly efficient utilization of these unique metabolites. The outcome of this study contributes to a broader comprehension of the biosynthetic pathways, elucidating multiple aspects of specialized metabolism and offering innovative avenues for biotechnological applications.

Genome-Wide Analysis of Lipoxygenase (LOX) Genes in Angiosperms.

Lipoxygenases (LOXs) are enzymes that catalyze the addition of an oxygen molecule to unsaturated fatty acids, thus forming hydroperoxides. In plants, these enzymes are encoded by a multigene family found in several organs with varying activity patterns, by which they are classified as LOX9 or LOX13. They are involved in several physiological functions, such as growth, fruit development, and plant defense. Despite several studies on genes of the LOX family in plants, most studies are restricted to a single species or a few closely related species. This study aimed to analyze the diversity, evolution, and expression of LOX genes in angiosperm species. We identified 247 LOX genes among 23 species of angiosperms and basal plants. Phylogenetic analyses identified clades supporting LOX13 and two main clades for LOX9: LOX9_A and LOX9_B. Eudicot species such as Tarenaya hassleriana, Capsella rubella, and Arabidopsis thaliana did not present LOX9_B genes; however, LOX9_B was present in all monocots used in this study. We identified that there were potential new subcellular localization patterns and conserved residues of oxidation for LOX9 and LOX13 yet unexplored. In summary, our study provides a basis for the further functional and evolutionary study of lipoxygenases in angiosperms.

Genome-wide association study for resistance to Pseudomonas syringae pv. garcae in Coffea arabica.

Bacteria halo blight (BHB), a coffee plant disease caused by Pseudomonas syringae pv. garcae, has been gaining importance in producing mountain regions and mild temperatures areas as well as in coffee nurseries. Most Coffea arabica cultivars are susceptible to this disease. In contrast, a great source of genetic diversity and resistance to BHB are found in C. arabica Ethiopian accessions. Aiming to identify quantitative trait nucleotides (QTNs) associated with resistance to BHB and the influence of these genomic regions during the domestication of C. arabica, we conducted an analysis of population structure and a Genome-Wide Association Study (GWAS). For this, we used genotyping by sequencing (GBS) and phenotyping for resistance to BHB of a panel with 120 C. arabica Ethiopian accessions from a historical FAO collection, 11 C. arabica cultivars, and the BA-10 genotype. Population structure analysis based on single-nucleotide polymorphisms (SNPs) markers showed that the 132 accessions are divided into 3 clusters: most wild Ethiopian accessions, domesticated Ethiopian accessions, and cultivars. GWAS, using the single-locus model MLM and the multi-locus models mrMLM, FASTmrMLM, FASTmrEMMA, and ISIS EM-BLASSO, identified 11 QTNs associated with resistance to BHB. Among these QTNs, the four with the highest values of association for resistance to BHB are linked to g000 (Chr_0_434_435) and g010741 genes, which are predicted to encode a serine/threonine-kinase protein and a nucleotide binding site leucine-rich repeat (NBS-LRR), respectively. These genes displayed a similar transcriptional downregulation profile in a C. arabica susceptible cultivar and in a C. arabica cultivar with quantitative resistance, when infected with P. syringae pv. garcae. However, peaks of upregulation were observed in a C. arabica cultivar with qualitative resistance, for both genes. Our results provide SNPs that have potential for application in Marker Assisted Selection (MAS) and expand our understanding about the complex genetic control of the resistance to BHB in C. arabica. In addition, the findings contribute to increasing understanding of the C. arabica domestication history.

Computational Analysis of Transposable Elements and CircRNAs in Plants.

This chapter provides two main contributions: (1) a description of computational tools and databases used to identify and analyze transposable elements (TEs) and circRNAs in plants; and (2) data analysis on public TE and circRNA data. Our goal is to highlight the primary information available in the literature on circular noncoding RNAs and transposable elements in plants. The exploratory analysis performed on publicly available circRNA and TEs data help discuss four sequence features. Finally, we investigate the association on circRNAs:TE in plants in the model organism Arabidopsis thaliana.

TERL: classification of transposable elements by convolutional neural networks.

Transposable elements (TEs) are the most represented sequences occurring in eukaryotic genomes. Few methods provide the classification of these sequences into deeper levels, such as superfamily level, which could provide useful and detailed information about these sequences. Most methods that classify TE sequences use handcrafted features such as k-mers and homology-based search, which could be inefficient for classifying non-homologous sequences. Here we propose an approach, called transposable elements pepresentation learner (TERL), that preprocesses and transforms one-dimensional sequences into two-dimensional space data (i.e., image-like data of the sequences) and apply it to deep convolutional neural networks. This classification method tries to learn the best representation of the input data to classify it correctly. We have conducted six experiments to test the performance of TERL against other methods. Our approach obtained macro mean accuracies and F1-score of 96.4% and 85.8% for superfamilies and 95.7% and 91.5% for the order sequences from RepBase, respectively. We have also obtained macro mean accuracies and F1-score of 95.0% and 70.6% for sequences from seven databases into superfamily level and 89.3% and 73.9% for the order level, respectively. We surpassed accuracy, recall and specificity obtained by other methods on the experiment with the classification of order level sequences from seven databases and surpassed by far the time elapsed of any other method for all experiments. Therefore, TERL can learn how to predict any hierarchical level of the TEs classification system and is about 20 times and three orders of magnitude faster than TEclass and PASTEC, respectively https://github.com/muriloHoracio/TERL. Contact:murilocruz@alunos.utfpr.edu.br.

The urea transporter DUR3 is differentially regulated by abiotic and biotic stresses in coffee plants.

The high costs of N fertilizers in the coffee production emphasizes the need to optimize fertilization practices and improve nitrogen use efficiency. Urea is widespread in nature, characterizing itself as a significant source of nitrogen for the growth and development of several organisms. Thus, the characterization of genes involved in urea transport in coffee plants is an important research topic for the sustainable production of this valuable cash crop. In the current study, we evaluated the expression of the DUR3 gene under abiotic and biotic stresses in coffee plants. Here, we show that the expression of a high-affinity urea transporter gene (CaDUR3) was up-regulated by N starvation in leaves and roots of two out of three C. arabica cultivars examined. Moreover, the CaDUR3 gene was differentially expressed in coffee plants under different abiotic and biotic stresses. In plants of cv. IAPAR59, CaDUR3 showed an increased expression in leaves after exposure to water deficit and heat stress, while it was downregulated in plants under salinity. Upon infection with H. vastatrix (coffee rust), the CaDUR3 was markedly up-regulated at the beginning of the infection process in the disease susceptible Catuaí Vermelho 99 in comparison with the resistant cultivar. These results indicate that besides urea acquisition and N-remobilization, CaDUR3 gene may be closely involved in the response to various stresses.

An Atlas of Plant Transposable Elements.

Advances in genomic sequencing have recently offered vast opportunities for biological exploration, unraveling the evolution and improving our understanding of Earth biodiversity. Due to distinct plant species characteristics in terms of genome size, ploidy and heterozygosity, transposable elements (TEs) are common characteristics of many genomes. TEs are ubiquitous and dispersed repetitive DNA sequences that frequently impact the evolution and composition of the genome, mainly due to their redundancy and rearrangements. For this study, we provided an atlas of TE data by employing an easy-to-use portal ( APTE website ). To our knowledge, this is the most extensive and standardized analysis of TEs in plant genomes. We evaluated 67 plant genomes assembled at chromosome scale, recovering a total of 49,802,023 TE records, representing a total of 47,992,091,043 (~47,62%) base pairs (bp) of the total genomic space. We observed that new types of TEs were identified and annotated compared to other data repositories. By establishing a standardized catalog of TE annotation on 67 genomes, new hypotheses, exploration of TE data and their influences on the genomes may allow a better understanding of their function and processes. All original code and an example of how we developed the TE annotation strategy is available on GitHub ( Extended data).

Low-Copy Genes in Terpenoid Metabolism: The Evolution and Expression of MVK and DXR Genes in Angiosperms.

Terpenoids are a diverse class of metabolites that impact plant metabolism in response to environmental cues. They are synthesized either via a predominantly cytosolic (MVA) pathway or a plastidic pathway (MEP). In Arabidopsis, several enzymes from the MVA and MEP pathways are encoded by gene families, excluding MVK and DXR, which are single-copy genes. In this study, we assess the diversity, evolution and expression of DXR and MVK genes in selected angiosperms and Coffea arabica in particular. Evolutionary analysis revealed that DXR and MVK underwent purifying selection, but the selection effect for DXR was stronger than it was for MVK. Digital gene expression (DGE) profile analysis of six species revealed that expression levels of MVK in flowers and roots were high, whereas for DXR peak values were observed in leaves. In C. arabica, both genes were highly expressed in flowers, and CaDXR was upregulated in response to methyl jasmonate. C. arabica DGE data were validated by assessing gene expression in selected organs, and by plants treated with hexanoic acid (Hx) using RT-qPCR. MVK expression was upregulated in roots treated with Hx. CaDXR was downregulated in leaves by Hx treatment in a genotype-specific manner, indicating a differential response to priming.

Population structure and genetic relationships between Ethiopian and Brazilian Coffea arabica genotypes revealed by SSR markers.

Information about population structure and genetic relationships within and among wild and brazilian Coffea arabica L. genotypes is highly relevant to optimize the use of genetic resources for breeding purposes. In this study, we evaluated genetic diversity, clustering analysis based on Jaccard's coefficient and population structure in 33 genotypes of C. arabica and of three diploid Coffea species (C. canephora, C. eugenioides and C. racemosa) using 30 SSR markers. A total of 206 alleles were identified, with a mean of 6.9 over all loci. The set of SSR markers was able to discriminate all genotypes and revealed that Ethiopian accessions presented higher genetic diversity than commercial varieties. Population structure analysis indicated two genetic groups, one corresponding to Ethiopian accessions and another corresponding predominantly to commercial cultivars. Thirty-four private alleles were detected in the group of accessions collected from West side of Great Rift Valley. We observed a lower average genetic distance of the C. arabica genotypes in relation to C. eugenioides than C. canephora. Interestingly, commercial cultivars were genetically closer to C. eugenioides than C. canephora and C. racemosa. The great allelic richness observed in Ethiopian Arabica coffee, especially in Western group showed that these accessions can be potential source of new alleles to be explored by coffee breeding programs.

Decarboxylation mechanisms of C4 photosynthesis in Saccharum spp.: increased PEPCK activity under water-limiting conditions.

BACKGROUND: C4 plants have been classified into three subtypes based on the enzymes used to decarboxylate C4 acids in the bundle sheath cells (NADP-ME, NAD-ME and PEPCK pathways). Evidences indicate that, depending on environmental factors, C4 plants may exhibit a certain degree of flexibility in the use of the decarboxylation mechanisms. In this context, the objective was to extend the knowledge on the degree of flexibility between the pathways of decarboxylation in sugarcane, a NADP-ME species, at different levels of water deficit. RESULTS: An experiment was carried out with two cultivars - RB92579 (tolerant to water deficit) and SP80-3280 (susceptible to water deficit) subjected to moderate level (- 1.5 to - 1.8 MPa), severe level (below - 2.0 MPa) and recovery (48 h after rehydration) and changes in the activities of the enzymes involved in the three C4 mechanisms and in gene expression were investigated. Our results showed that sugarcane uses the PEPCK pathway as a decarboxylation mechanism in addition to the NADP-ME, which was more evident under water deficit conditions for both cultivars. CONCLUSIONS: The results obtained here, show that sugarcane increases the use of the PEPCK pathway as a decarboxylation mechanism, in addition to the NADP-ME pathway, under conditions of water deficit, particularly in the tolerant cultivar.

mirtronDB: a mirtron knowledge base.

MOTIVATION: Mirtrons arise from short introns with atypical cleavage by using the splicing mechanism. In the current literature, there is no repository centralizing and organizing the data available to the public. To fill this gap, we developed mirtronDB, the first knowledge database dedicated to mirtron, and it is available at http://mirtrondb.cp.utfpr.edu.br/. MirtronDB currently contains a total of 1407 mirtron precursors and 2426 mirtron mature sequences in 18 species. RESULTS: Through a user-friendly interface, users can now browse and search mirtrons by organism, organism group, type and name. MirtronDB is a specialized resource that provides free and user-friendly access to knowledge on mirtron data. AVAILABILITY AND IMPLEMENTATION: MirtronDB is available at http://mirtrondb.cp.utfpr.edu.br/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pattern recognition analysis on long noncoding RNAs: a tool for prediction in plants.

MOTIVATION: Long noncoding RNAs (lncRNAs) correspond to a eukaryotic noncoding RNA class that gained great attention in the past years as a higher layer of regulation for gene expression in cells. There is, however, a lack of specific computational approaches to reliably predict lncRNA in plants, which contrast the variety of prediction tools available for mammalian lncRNAs. This distinction is not that obvious, given that biological features and mechanisms generating lncRNAs in the cell are likely different between animals and plants. Considering this, we present a machine learning analysis and a classifier approach called RNAplonc (https://github.com/TatianneNegri/RNAplonc/) to identify lncRNAs in plants. RESULTS: Our feature selection analysis considered 5468 features, and it used only 16 features to robustly identify lncRNA with the REPTree algorithm. That was the base to create the model and train it with lncRNA and mRNA data from five plant species (thale cress, cucumber, soybean, poplar and Asian rice). After an extensive comparison with other tools largely used in plants (CPC, CPC2, CPAT and PLncPRO), we found that RNAplonc produced more reliable lncRNA predictions from plant transcripts with 87.5% of the best result in eight tests in eight species from the GreeNC database and four independent studies in monocotyledonous (Brachypodium) and eudicotyledonous (Populus and Gossypium) species.

PlaNC-TE: a comprehensive knowledgebase of non-coding RNAs and transposable elements in plants.

Transposable elements (TEs) play an essential role in the genetic variability of eukaryotic species. In plants, they may comprise up to 90% of the total genome. Non-coding RNAs (ncRNAs) are known to control gene expression and regulation. Although the relationship between ncRNAs and TEs is known, obtaining the organized data for sequenced genomes is not straightforward. In this study, we describe the PlaNC-TE (http://planc-te.cp.utfpr.edu.br), a user-friendly portal harboring a knowledgebase created by integrating and analysing plant ncRNA-TE data. We identified a total of 14 350 overlaps between ncRNAs and TEs in 40 plant genomes. The database allows users to browse, search and download all ncRNA and TE data analysed. Overall, PlaNC-TE not only organizes data and provides insights about the relationship between ncRNA and TEs in plants but also helps improve genome annotation strategies. Moreover, this is the first database to provide resources to broadly investigate functions and mechanisms involving TEs and ncRNAs in plants.

Functional annotation and distribution overview of RNA families in 27 Streptococcus agalactiae genomes.

BACKGROUND: Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a Gram-positive bacterium that colonizes the gastrointestinal and genitourinary tract of humans. This bacterium has also been isolated from various animals, such as fish and cattle. Non-coding RNAs (ncRNAs) can act as regulators of gene expression in bacteria, such as Streptococcus pneumoniae and Streptococcus pyogenes. However, little is known about the genomic distribution of ncRNAs and RNA families in S. agalactiae. RESULTS: Comparative genome analysis of 27 S. agalactiae strains showed more than 5 thousand genomic regions identified and classified as Core, Exclusive, and Shared genome sequences. We identified 27 to 89 RNA families per genome distributed over these regions, from these, 25 were in Core regions while Shared and Exclusive regions showed variations amongst strains. We propose that the amount and type of ncRNA present in each genome can provide a pattern to contribute in the identification of the clonal types. CONCLUSIONS: The identification of RNA families provides an insight over ncRNAs, sRNAs and ribozymes function, that can be further explored as targets for antibiotic development or studied in gene regulation of cellular processes. RNA families could be considered as markers to determine infection capabilities of different strains. Lastly, pan-genome analysis of GBS including the full range of functional transcripts provides a broader approach in the understanding of this pathogen.

ceRNAs in plants: computational approaches and associated challenges for target mimic research.

The competing endogenous RNA hypothesis has gained increasing attention as a potential global regulatory mechanism of microRNAs (miRNAs), and as a powerful tool to predict the function of many noncoding RNAs, including miRNAs themselves. Most studies have been focused on animals, although target mimic (TMs) discovery as well as important computational and experimental advances has been developed in plants over the past decade. Thus, our contribution summarizes recent progresses in computational approaches for research of miRNA:TM interactions. We divided this article in three main contributions. First, a general overview of research on TMs in plants is presented with practical descriptions of the available literature, tools, data, databases and computational reports. Second, we describe a common protocol for the computational and experimental analyses of TM. Third, we provide a bioinformatics approach for the prediction of TM motifs potentially cross-targeting both members within the same or from different miRNA families, based on the identification of consensus miRNA-binding sites from known TMs across sequenced genomes, transcriptomes and known miRNAs. This computational approach is promising because, in contrast to animals, miRNA families in plants are large with identical or similar members, several of which are also highly conserved. From the three consensus TM motifs found with our approach: MIM166, MIM171 and MIM159/319, the last one has found strong support on the recent experimental work by Reichel and Millar [Specificity of plant microRNA TMs: cross-targeting of mir159 and mir319. J Plant Physiol 2015;180:45-8]. Finally, we stress the discussion on the major computational and associated experimental challenges that have to be faced in future ceRNA studies.

Genome-wide identification, classification and transcriptional analysis of nitrate and ammonium transporters in Coffea.

Nitrogen (N) is quantitatively the main nutrient required by coffee plants, with acquisition mainly by the roots and mostly exported to coffee beans. Nitrate (NO3-) and ammonium (NH4+) are the most important inorganic sources for N uptake. Several N transporters encoded by different gene families mediate the uptake of these compounds. They have an important role in source preference for N uptake in the root system. In this study, we performed a genome-wide analysis, including in silico expression and phylogenetic analyses of AMT1, AMT2, NRT1/PTR, and NRT2 transporters in the recently sequenced Coffea canephora genome. We analyzed the expression of six selected transporters in Coffea arabica roots submitted to N deficiency. N source preference was also analyzed in C. arabica using isotopes. C. canephora N transporters follow the patterns observed for most eudicots, where each member of the AMT and NRT families has a particular role in N mobilization, and where some of these are modulated by N deficiency. Despite the prevalence of putative nitrate transporters in the Coffea genome, ammonium was the preferential inorganic N source for N-starved C. arabica roots. This data provides an important basis for fundamental and applied studies to depict molecular mechanisms involved in N uptake in coffee trees.

Distribution of Divo in Coffea genomes, a poorly described family of angiosperm LTR-Retrotransposons.

Coffea arabica (the Arabica coffee) is an allotetraploid species originating from a recent hybridization between two diploid species: C. canephora and C. eugenioides. Transposable elements can drive structural and functional variation during the process of hybridization and allopolyploid formation in plants. To learn more about the evolution of the C. arabica genome, we characterized and studied a new Copia LTR-Retrotransposon (LTR-RT) family in diploid and allotetraploid Coffea genomes called Divo. It is a complete and relatively compact LTR-RT element (~5 kb), carrying typical Gag and Pol Copia type domains. Reverse Trancriptase (RT) domain-based phylogeny demonstrated that Divo is a new and well-supported family in the Bianca lineage, but strictly restricted to dicotyledonous species. In C. canephora, Divo is expressed and showed a genomic distribution along gene rich and gene poor regions. The copy number, the molecular estimation of insertion time and the analysis at orthologous locations of insertions in diploid and allotetraploid coffee genomes suggest that Divo underwent a different and recent transposition activity in C. arabica and C. canephora when compared to C. eugenioides. The analysis of this novel LTR-RT family represents an important step toward uncovering the genome structure and evolution of C. arabica allotetraploid genome.

Genome-wide analysis of EgEVE_1, a transcriptionally active endogenous viral element associated to small RNAs in Eucalyptus genomes.

Endogenous viral elements (EVEs) are the result of heritable horizontal gene transfer from viruses to hosts. In the last years, several EVE integration events were reported in plants by the exponential availability of sequenced genomes. Eucalyptus grandis is a forest tree species with a sequenced genome that is poorly studied in terms of evolution and mobile genetic elements composition. Here we report the characterization of E. grandis endogenous viral element 1 (EgEVE_1), a transcriptionally active EVE with a size of 5,664 bp. Phylogenetic analysis and genomic distribution demonstrated that EgEVE_1 is a newly described member of the Caulimoviridae family, distinct from the recently characterized plant Florendoviruses. Genomic distribution of EgEVE_1 and Florendovirus is also distinct. EgEVE_1 qPCR quantification in Eucalyptus urophylla suggests that this genome has more EgEVE_1 copies than E. grandis. EgEVE_1 transcriptional activity was demonstrated by RT-qPCR in five Eucalyptus species and one intrageneric hybrid. We also identified that Eucalyptus EVEs can generate small RNAs (sRNAs),that might be involved in de novo DNA methylation and virus resistance. Our data suggest that EVE families in Eucalyptus have distinct properties, and we provide the first comparative analysis of EVEs in Eucalyptus genomes.

Transcriptome Analysis of Leaves, Flowers and Fruits Perisperm of Coffea arabica L. Reveals the Differential Expression of Genes Involved in Raffinose Biosynthesis.

Coffea arabica L. is an important crop in several developing countries. Despite its economic importance, minimal transcriptome data are available for fruit tissues, especially during fruit development where several compounds related to coffee quality are produced. To understand the molecular aspects related to coffee fruit and grain development, we report a large-scale transcriptome analysis of leaf, flower and perisperm fruit tissue development. Illumina sequencing yielded 41,881,572 high-quality filtered reads. De novo assembly generated 65,364 unigenes with an average length of 1,264 bp. A total of 24,548 unigenes were annotated as protein coding genes, including 12,560 full-length sequences. In the annotation process, we identified nine candidate genes related to the biosynthesis of raffinose family oligossacarides (RFOs). These sugars confer osmoprotection and are accumulated during initial fruit development. Four genes from this pathway had their transcriptional pattern validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, we identified ~24,000 putative target sites for microRNAs (miRNAs) and 134 putative transcriptionally active transposable elements (TE) sequences in our dataset. This C. arabica transcriptomic atlas provides an important step for identifying candidate genes related to several coffee metabolic pathways, especially those related to fruit chemical composition and therefore beverage quality. Our results are the starting point for enhancing our knowledge about the coffee genes that are transcribed during the flowering and initial fruit development stages.

Genome-wide analysis of EgEVE_1, a transcriptionally active endogenous viral element associated to small RNAs in Eucalyptus genomes

Abstract Endogenous viral elements (EVEs) are the result of heritable horizontal gene transfer from viruses to hosts. In the last years, several EVE integration events were reported in plants by the exponential availability of sequenced genomes. Eucalyptus grandis is a forest tree species with a sequenced genome that is poorly studied in terms of evolution and mobile genetic elements composition. Here we report the characterization of E. grandis endogenous viral element 1 (EgEVE_1), a transcriptionally active EVE with a size of 5,664 bp. Phylogenetic analysis and genomic distribution demonstrated that EgEVE_1 is a newly described member of the Caulimoviridae family, distinct from the recently characterized plant Florendoviruses. Genomic distribution of EgEVE_1 and Florendovirus is also distinct. EgEVE_1 qPCR quantification in Eucalyptus urophylla suggests that this genome has more EgEVE_1 copies than E. grandis. EgEVE_1 transcriptional activity was demonstrated by RT-qPCR in five Eucalyptus species and one intrageneric hybrid. We also identified that Eucalyptus EVEs can generate small RNAs (sRNAs),that might be involved in de novo DNA methylation and virus resistance. Our data suggest that EVE families in Eucalyptus have distinct properties, and we provide the first comparative analysis of EVEs in Eucalyptus genomes.