Advances in alternative splicing identification: deep learning and pantranscriptome.

In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing.

Comparative genomics reveals a unique nitrogen-carbon balance system in Asteraceae.

The Asteraceae (daisy family) is one of the largest families of plants. The genetic basis for its high biodiversity and excellent adaptability has not been elucidated. Here, we compare the genomes of 29 terrestrial plant species, including two de novo chromosome-scale genome assemblies for stem lettuce, a member of Asteraceae, and Scaevola taccada, a member of Goodeniaceae that is one of the closest outgroups of Asteraceae. We show that Asteraceae originated ~80 million years ago and experienced repeated paleopolyploidization. PII, the universal regulator of nitrogen-carbon (N-C) assimilation present in almost all domains of life, has conspicuously lost across Asteraceae. Meanwhile, Asteraceae has stepwise upgraded the N-C balance system via paleopolyploidization and tandem duplications of key metabolic genes, resulting in enhanced nitrogen uptake and fatty acid biosynthesis. In addition to suggesting a molecular basis for their ecological success, the unique N-C balance system reported for Asteraceae offers a potential crop improvement strategy.

Insights into the convergent evolution of fructan biosynthesis in angiosperms from the highly characteristic chicory genome.

Fructans in angiosperms play essential roles in physiological functions and environmental adaptations. As a major source of industrial fructans (especially inulin-type), chicory (Cichorium intybus L.) is a model species for studying fructan biosynthesis. However, the genes underlying this process and their evolutionary history in angiosperms remain elusive. We combined multiple sequencing technologies to assemble and annotate the chicory genome and scan its (epi)genomic features, such as genomic components, DNA methylation, and three-dimensional (3D) structure. We also performed a comparative genomics analysis to uncover the associations between key traits and gene families. We achieved a nearly complete chicory genome assembly and found that continuous bursts of a few highly active retrotransposon families largely shaped the (epi)genomic characteristics. The highly methylated genome with its unique 3D structure potentially influences critical biological processes. Our comprehensive comparative genomics analysis deciphered the genetic basis for the rich sesquiterpene content in chicory and indicated that the fructan-accumulating trait resulted from convergent evolution in angiosperms due to shifts in critical sites of fructan-active enzymes. The highly characterized chicory genome provides insight into Asteraceae evolution and fructan biosynthesis in angiosperms.

Plant MicroRNA Identification and Annotation Using Deep Sequencing Data.

MicroRNAs (miRNAs) are endogenous non-coding small RNAs, which regulate gene expression at the post-transcriptional level. A large number of studies have revealed that they play key roles in diverse life activities, such as growth and development. In the last decade, deep sequencing technology has generated substantial small RNA sequencing (sRNA-Seq) data. Meanwhile, numerous tools have been developed to identify miRNAs from these sRNA-Seq data, resulting in a surge of miRNA annotations. Among these tools, the series of miRDeep-P and miRDeep-P2 have been widely used in plant miRNA annotation. Here, we employed miRDeep-P2 to demonstrate the plant miRNA annotation processes step by step using the deep sequencing data.

LettuceGDB: The community database for lettuce genetics and omics.

As a globally popular leafy vegetable and a representative plant of the Asteraceae family, lettuce has great economic and academic significance. In the last decade, high-throughput sequencing, phenotyping, and other multi-omics data in lettuce have accumulated on a large scale, thus increasing the demand for an integrative lettuce database. Here, we report the establishment of a comprehensive lettuce database, LettuceGDB (https://www.lettucegdb.com/). As an omics data hub, the current LettuceGDB includes two reference genomes with detailed annotations; re-sequencing data from over 1000 lettuce varieties; a collection of more than 1300 worldwide germplasms and millions of accompanying phenotypic records obtained with manual and cutting-edge phenomics technologies; re-analyses of 256 RNA sequencing datasets; a complete miRNAome; extensive metabolite information for representative varieties and wild relatives; epigenetic data on the genome-wide chromatin accessibility landscape; and various lettuce research papers published in the last decade. Five hierarchically accessible functions (Genome, Genotype, Germplasm, Phenotype, and O-Omics) have been developed with a user-friendly interface to enable convenient data access. Eight built-in tools (Assembly Converter, Search Gene, BLAST, JBrowse, Primer Design, Gene Annotation, Tissue Expression, Literature, and Data) are available for data downloading and browsing, functional gene exploration, and experimental practice. A community forum is also available for information sharing, and a summary of current research progress on different aspects of lettuce is included. We believe that LettuceGDB can be a comprehensive functional database amenable to data mining and database-driven exploration, useful for both scientific research and lettuce breeding.

Identification of Species-Specific MicroRNAs Provides Insights into Dynamic Evolution of MicroRNAs in Plants.

MicroRNAs (miRNAs) are an important class of regulatory small RNAs that program gene expression, mainly at the post-transcriptional level. Although sporadic examples of species-specific miRNAs (termed SS-miRNAs) have been reported, a genome-scale study across a variety of distant species has not been assessed. Here, by comprehensively analyzing miRNAs in 81 plant species phylogenetically ranging from chlorophytes to angiosperms, we identified 8048 species-specific miRNAs from 5499 families, representing over 61.2% of the miRNA families in the examined species. An analysis of the conservation from different taxonomic levels supported the high turnover rate of SS-miRNAs, even over short evolutionary distances. A comparison of the intrinsic features between SS-miRNAs and NSS-miRNAs (non-species-specific miRNAs) indicated that the AU content of mature miRNAs was the most striking difference. Our data further illustrated a significant bias of the genomic coordinates towards SS-miRNAs lying close to or within genes. By analyzing the 125,267 putative target genes for the 7966 miRNAs, we found the preferentially regulated functions of SS-miRNAs related to diverse metabolic processes. Collectively, these findings underscore the dynamic evolution of miRNAs in the species-specific lineages.

Miniature Inverted-repeat Transposable Elements Drive Rapid MicroRNA Diversification in Angiosperms.

MicroRNAs (miRNAs) are fast evolving endogenous small RNAs that regulate organism function and behavior in both animals and plants. Although models for de novo miRNA biogenesis have been proposed, the genomic mechanisms driving swift diversification of the miRNA repertoires in plants remain elusive. Here, by comprehensively analyzing 21 phylogenetically representative plant species, ranging from green algae to angiosperms, we systematically identified de novo miRNA events associated with 8,649 miRNA loci. We found that 399 (4.6%), 466 (5.4%), and 1,402 (16.2%) miRNAs were derived from inverted gene duplication events, long terminal repeats of retrotransposons, and miniature inverted-repeat transposable elements (MITEs), respectively. Among the miRNAs of these origins, MITEs, especially those belonging to the Mutator, Tc1/Mariner, and PIF/Harbinger superfamilies, were the predominant genomic source for de novo miRNAs in the 15 examined angiosperms but not in the six non-angiosperms. Our data further illustrated a transposition-transcription process by which MITEs are converted into new miRNAs (termed MITE-miRNAs) whereby properly sized MITEs are transcribed and therefore become potential substrates for the miRNA processing machinery by transposing into introns of active genes. By analyzing the 58,038 putative target genes for the 8,095 miRNAs, we found that the target genes of MITE-miRNAs were preferentially associated with response to environmental stimuli such as temperature, suggesting that MITE-miRNAs are pertinent to plant adaptation. Collectively, these findings demonstrate that molecular conversion of MITEs is a genomic mechanism leading to rapid and continuous changes to the miRNA repertoires in angiosperm.

The Construction and Exploration of a Comprehensive MicroRNA Centered Regulatory Network in Foxtail Millet (Setaria italica L.).

MicroRNA (miRNA) is an essential endogenous post-transcriptional regulatory factor, and foxtail millet (Setaria italica L.) is an ideal C4 model cereal that is a highly valuable crop in semiarid and arid areas. The Research on comprehensive and high confidence identification and annotation of foxtail millet miRNAs needs to be strengthened, and to our knowledge, there is no information on the regulatory network of foxtail millet miRNA. In this study, 136 high confidence miRNAs were identified through high-throughput sequencing of the small RNAs in seven tissues at the shooting and grain filling stages of foxtail millet. A total of 2,417 target genes were obtained by combining computational biology software and degradome sequencing methods. Furthermore, an analysis using transcriptome sequencing revealed the relationships between miRNAs and their target genes and simultaneously explored key regulatory modules in panicles during the grain filling stage. An miRNA regulatory network was constructed to explore the functions of miRNA in more detail. This network, centered on miRNAs and combining upstream transcriptional factors and downstream target genes, is primarily composed of feed forward loop motifs, which greatly enhances our knowledge of the potential functions of miRNAs and uncovers numerous previously unknown regulatory links. This study provides a solid foundation for research on the function and regulatory network of miRNAs in foxtail millet.

Quantitative phenotyping and evaluation for lettuce leaves of multiple semantic components.

BACKGROUND: Classification and phenotype identification of lettuce leaves urgently require fine quantification of their multi-semantic traits. Different components of lettuce leaves undertake specific physiological functions and can be quantitatively described and interpreted using their observable properties. In particular, petiole and veins determine mechanical support and material transport performance of leaves, while other components may be closely related to photosynthesis. Currently, lettuce leaf phenotyping does not accurately differentiate leaf components, and there is no comparative evaluation for positive-back of the same lettuce leaf. In addition, a few traits of leaf components can be measured manually, but it is time-consuming, laborious, and inaccurate. Although several studies have been on image-based phenotyping of leaves, there is still a lack of robust methods to extract and validate multi-semantic traits of large-scale lettuce leaves automatically. RESULTS: In this study, we developed an automated phenotyping pipeline to recognize the components of detached lettuce leaves and calculate multi-semantic traits for phenotype identification. Six semantic segmentation models were constructed to extract leaf components from visible images of lettuce leaves. And then, the leaf normalization technique was used to rotate and scale different leaf sizes to the "size-free" space for consistent leaf phenotyping. A novel lamina-based approach was also utilized to determine the petiole, first-order vein, and second-order veins. The proposed pipeline contributed 30 geometry-, 20 venation-, and 216 color-based traits to characterize each lettuce leaf. Eleven manually measured traits were evaluated and demonstrated high correlations with computation results. Further, positive-back images of leaves were used to verify the accuracy of the proposed method and evaluate the trait differences. CONCLUSIONS: The proposed method lays an effective strategy for quantitative analysis of detached lettuce leaves' fine structure and components. Geometry, color, and vein traits of lettuce leaf and its components can be comprehensively utilized for phenotype identification and breeding of lettuce. This study provides valuable perspectives for developing automated high-throughput phenotyping application of lettuce leaves and the improvement of agronomic traits such as effective photosynthetic area and vein configuration.

PmiREN2.0: from data annotation to functional exploration of plant microRNAs.

Nearly 200 plant genomes have been sequenced over the last two years, and new functions of plant microRNAs (miRNAs) have been revealed. Therefore, timely update of the plant miRNA databases by incorporating miRNAs from the newly sequenced species and functional information is required to provide useful resources for advancing plant miRNA research. Here we report the update of PmiREN2.0 (https://pmiren.com/) with an addition of 19 363 miRNA entries from 91 plants, doubling the amount of data in the original version. Meanwhile, abundant regulatory information centred on miRNAs was added, including predicted upstream transcription factors through binding motifs scanning and elaborate annotation of miRNA targets. As an example, a genome-wide regulatory network centred on miRNAs was constructed for Arabidopsis. Furthermore, phylogenetic trees of conserved miRNA families were built to expand the understanding of miRNA evolution across the plant lineages. These data are helpful to deduce the regulatory relationships concerning miRNA functions in diverse plants. Beside the new data, a suite of design tools was incorporated to facilitate experimental practice. Finally, a forum named 'PmiREN Community' was added for discussion and resource and new discovery sharing. With these upgrades, PmiREN2.0 should serve the community better and accelerate miRNA research in plants.

Genome-Wide Characterization of SPL Gene Family in Codonopsis pilosula Reveals the Functions of CpSPL2 and CpSPL10 in Promoting the Accumulation of Secondary Metabolites and Growth of C. pilosula Hairy Root.

SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) transcription factors play critical roles in regulating diverse aspects of plant growth and development, including vegetative phase change, plant architecture, anthocyanin accumulation, lateral root growth, etc. In the present study, 15 SPL genes were identified based on the genome data of Codonopsis pilosula, a well-known medicinal plant. Phylogenetic analysis clustered CpSPLs into eight groups (G1-G8) along with SPLs from Arabidopsis thaliana, Solanum lycopersicum, Oryza sativa and Physcomitrella patens. CpSPLs in the same group share similar gene structure and conserved motif composition. Cis-acting elements responding to light, stress and phytohormone widely exist in their promoter regions. Our qRT-PCR results indicated that 15 CpSPLs were differentially expressed in different tissues (root, stem, leaf, flower and calyx), different developmental periods (1, 2 and 3 months after germination) and various conditions (NaCl, MeJA and ABA treatment). Compared with the control, overexpression of CpSPL2 or CpSPL10 significantly promoted not only the growth of hairy roots, but also the accumulation of total saponins and lobetyolin. Our results established a foundation for further investigation of CpSPLs and provided novel insights into their biological functions. As far as we know, this is the first experimental research on gene function in C. pilosula.

MicroRNA annotation in plants: current status and challenges.

Last two decades, the studies on microRNAs (miRNAs) and the numbers of annotated miRNAs in plants and animals have surged. Herein, we reviewed the current progress and challenges of miRNA annotation in plants. Via the comparison of plant and animal miRNAs, we pinpointed out the difficulties on plant miRNA annotation and proposed potential solutions. In terms of recalling the history of methods and criteria in plant miRNA annotation, we detailed how the major progresses made and evolved. By collecting and categorizing bioinformatics tools for plant miRNA annotation, we surveyed their advantages and disadvantages, especially for ones with the principle of mimicking the miRNA biogenesis pathway by parsing deeply sequenced small RNA (sRNA) libraries. In addition, we summarized all available databases hosting plant miRNAs, and posted the potential optimization solutions such as how to increase the signal-to-noise ratio (SNR) in these databases. Finally, we discussed the challenges and perspectives of plant miRNA annotations, and indicated the possibilities offered by an all-in-one tool and platform according to the integration of artificial intelligence.

Elucidation of the MicroRNA Transcriptome in Western Corn Rootworm Reveals Its Dynamic and Evolutionary Complexity.

Diabrotica virgifera virgifera (western corn rootworm, WCR) is one of the most destructive agricultural insect pests in North America. It is highly adaptive to environmental stimuli and crop protection technologies. However, little is known about the underlying genetic basis of WCR behavior and adaptation. More specifically, the involvement of small RNAs (sRNAs), especially microRNAs (miRNAs), a class of endogenous small non-coding RNAs that regulate various biological processes, has not been examined, and the datasets of putative sRNA sequences have not previously been generated for WCR. To achieve a comprehensive collection of sRNA transcriptomes in WCR, we constructed, sequenced, and analyzed sRNA libraries from different life stages of WCR and northern corn rootworm (NCR), and identified 101 conserved precursor miRNAs (pre-miRNAs) in WCR and other Arthropoda. We also identified 277 corn rootworm specific pre-miRNAs. Systematic analyses of sRNA populations in WCR revealed that its sRNA transcriptome, which includes PIWI-interacting RNAs (piRNAs) and miRNAs, undergoes a dynamic change throughout insect development. Phylogenetic analysis of miRNA datasets from model species reveals that a large pool of species-specific miRNAs exists in corn rootworm; these are potentially evolutionarily transient. Comparisons of WCR miRNA clusters to other insect species highlight conserved miRNA-regulated processes that are common to insects. Parallel Analysis of RNA Ends (PARE) also uncovered potential miRNA-guided cleavage sites in WCR. Overall, this study provides a new resource for studying the sRNA transcriptome and miRNA-mediated gene regulation in WCR and other Coleopteran insects.

H2AK121ub in Arabidopsis associates with a less accessible chromatin state at transcriptional regulation hotspots.

Although it is well established that the Polycomb Group (PcG) complexes maintain gene repression through the incorporation of H2AK121ub and H3K27me3, little is known about the effect of these modifications on chromatin accessibility, which is fundamental to understand PcG function. Here, by integrating chromatin accessibility, histone marks and expression analyses in different Arabidopsis PcG mutants, we show that PcG function regulates chromatin accessibility. We find that H2AK121ub is associated with a less accessible but still permissive chromatin at transcriptional regulation hotspots. Accessibility is further reduced by EMF1 acting in collaboration with PRC2 activity. Consequently, H2AK121ub/H3K27me3 marks are linked to inaccessible although responsive chromatin. In contrast, only-H3K27me3-marked chromatin is less responsive, indicating that H2AK121ub-marked hotspots are required for transcriptional responses. Nevertheless, despite the loss of PcG activities leads to increased chromatin accessibility, this is not necessarily accompanied by transcriptional activation, indicating that accessible chromatin is not always predictive of gene expression.

Comprehensive Annotation and Functional Exploration of MicroRNAs in Lettuce.

MicroRNA (miRNA) is an important endogenous post-transcriptional regulator, while lettuce (Lactuca sativa) is a leafy vegetable of global economic significance. However, there are few studies on miRNAs in lettuce, and research on miRNA regulatory network in lettuce is absent. In this study, through deep sequencing of small RNAs in different tissues, together with a reference genome, 157 high-confidence miRNA loci in lettuce were comprehensively identified, and their expression patterns were determined. Using a combination of computational prediction and high-throughput experimental verification, a set of reliable lettuce miRNA targets were obtained. Furthermore, through RNA-Seq, the expression profiles of these targets and a comprehensive view of the negative regulatory relationship between miRNAs and their targets was acquired based on a correlation analysis. To further understand miRNA functions, a miRNA regulatory network was constructed, with miRNAs at the core and combining transcription factors and miRNA target genes. This regulatory network, mainly composed of feed forward loop motifs, greatly increases understanding of the potential functions of miRNAs, and many unknown potential regulatory links were discovered. Finally, considering its specific expression pattern, Lsa-MIR408 as a hub gene was employed to illustrate the function of the regulatory network, and genetic experiments revealed its ability to increase the fresh weight and achene size of lettuce. In short, this work lays a solid foundation for the study of miRNA functions and regulatory networks in lettuce.

Image-Based High-Throughput Detection and Phenotype Evaluation Method for Multiple Lettuce Varieties.

The yield and quality of fresh lettuce can be determined from the growth rate and color of individual plants. Manual assessment and phenotyping for hundreds of varieties of lettuce is very time consuming and labor intensive. In this study, we utilized a "Sensor-to-Plant" greenhouse phenotyping platform to periodically capture top-view images of lettuce, and datasets of over 2000 plants from 500 lettuce varieties were thus captured at eight time points during vegetative growth. Here, we present a novel object detection-semantic segmentation-phenotyping method based on convolutional neural networks (CNNs) to conduct non-invasive and high-throughput phenotyping of the growth and development status of multiple lettuce varieties. Multistage CNN models for object detection and semantic segmentation were integrated to bridge the gap between image capture and plant phenotyping. An object detection model was used to detect and identify each pot from the sequence of images with 99.82% accuracy, semantic segmentation model was utilized to segment and identify each lettuce plant with a 97.65% F1 score, and a phenotyping pipeline was utilized to extract a total of 15 static traits (related to geometry and color) of each lettuce plant. Furthermore, the dynamic traits (growth and accumulation rates) were calculated based on the changing curves of static traits at eight growth points. The correlation and descriptive ability of these static and dynamic traits were carefully evaluated for the interpretability of traits related to digital biomass and quality of lettuce, and the observed accumulation rates of static straits more accurately reflected the growth status of lettuce plants. Finally, we validated the application of image-based high-throughput phenotyping through geometric measurement and color grading for a wide range of lettuce varieties. The proposed method can be extended to crops such as maize, wheat, and soybean as a non-invasive means of phenotype evaluation and identification.

Quo vadis microRNAs?

Since 2002, published miRNAs have been collected and named by the online repository miRBase. However, with 11 000 annual publications this has become challenging. Recently, four specialized miRNA databases were published, addressing particular needs for diverse scientific communities. This development provides major opportunities for the future of miRNA annotation and nomenclature.

Selection of suitable reference genes for qRT-PCR expression analysis of Codonopsis pilosula under different experimental conditions.

Codonopsis pilosula is a well-known medicinal plant. Although its transcriptome sequence has been published, suitable reference genes have not been systematically identified for conducting expression analyses via quantitative real-time polymerase chain reaction (qRT-PCR). To screen appropriate genes for use with this species, we applied four different methods-GeNorm, NormFinder, BestKeeper, and RefFinder-to evaluate the stability of 13 candidates: CpiEF1Bb, CpiCACS, CpiF-Box, Cpiß-Tubulin, CpiGAPDH, CpiActin2, CpiAPT1, CpiActin7, CpiActin8, CpiRPL6, CpiHAF1, CpiTubulin6, and CpiUBQ12. Expression was examined by qRT-PCR for various tissue types, chemical treatments, and developmental stages. For all tested samples, CpiGAPDH proved to be the most stable. Comprehensive analysis indicated that the most stable internal reference genes were CpiF-Box and CpiCACS in different tissues and at different developmental stages, respectively. Under NaCl stress, CpiAPT1 was the best internal reference gene. For methyl jasmonate and abscisic acid treatments, CpiGAPDH and CpiF-Box, respectively, presented the highest degree of expression stability. Based on these findings, we chose CpiSPL9 as the target gene for validating the suitability of these selected reference genes. All of these results provide a foundation for accurate quantification of expression levels by genes of interest in C. pilosula.