U4 snRNP inhibits premature cleavage and polyadenylation of pre-mRNAs.

The essential role of U4 snRNP in pre-messenger RNA (mRNA) splicing has been well established. In this study, we utilized an antisense morpholino oligonucleotide (AMO) specifically targeting U4 snRNA to achieve functional knockdown of U4 snRNP in HeLa cells. Our results showed that this knockdown resulted in global intronic premature cleavage and polyadenylation (PCPA) events, comparable to the effects observed with U1 AMO treatment, as demonstrated by mRNA 3'-seq analysis. Furthermore, our study suggested that this may be a common phenomenon in both human and mouse cell lines. Additionally, we showed that U4 AMO treatment disrupted transcription elongation, as evidenced by chromatin immunoprecipitation sequencing (ChIP-seq) analysis for RNAPII. Collectively, our results identified a unique role for U4 snRNP in the inhibition of PCPA and indicated a model wherein splicing intrinsically inhibits intronic cleavage and polyadenylation in the context of cotranscriptional mRNA processing.

Inhibitor AN3661 reveals biological functions of Arabidopsis CLEAVAGE and POLYADENYLATION SPECIFICITY FACTOR 73.

Cleavage and polyadenylation specificity factor (CPSF) is a protein complex that plays an essential biochemical role in mRNA 3'-end formation, including poly(A) signal recognition and cleavage at the poly(A) site. However, its biological functions at the organismal level are mostly unknown in multicellular eukaryotes. The study of plant CPSF73 has been hampered by the lethality of Arabidopsis (Arabidopsis thaliana) homozygous mutants of AtCPSF73-I and AtCPSF73-II. Here, we used poly(A) tag sequencing to investigate the roles of AtCPSF73-I and AtCPSF73-II in Arabidopsis treated with AN3661, an antimalarial drug with specificity for parasite CPSF73 that is homologous to plant CPSF73. Direct seed germination on an AN3661-containing medium was lethal; however, 7-d-old seedlings treated with AN3661 survived. AN3661 targeted AtCPSF73-I and AtCPSF73-II, inhibiting growth through coordinating gene expression and poly(A) site choice. Functional enrichment analysis revealed that the accumulation of ethylene and auxin jointly inhibited primary root growth. AN3661 affected poly(A) signal recognition, resulted in lower U-rich signal usage, caused transcriptional readthrough, and increased the distal poly(A) site usage. Many microRNA targets were found in the 3' untranslated region lengthened transcripts; these miRNAs may indirectly regulate the expression of these targets. Overall, this work demonstrates that AtCPSF73 plays important part in co-transcriptional regulation, affecting growth, and development in Arabidopsis.

The U1 antisense morpholino oligonucleotide (AMO) disrupts U1 snRNP structure to promote intronic PCPA modification of pre-mRNAs.

Functional depletion of the U1 small nuclear ribonucleoprotein (snRNP) with a 25 nt U1 AMO (antisense morpholino oligonucleotide) may lead to intronic premature cleavage and polyadenylation of thousands of genes, a phenomenon known as U1 snRNP telescripting; however, the underlying mechanism remains elusive. In this study, we demonstrated that U1 AMO could disrupt U1 snRNP structure both in vitro and in vivo, thereby affecting the U1 snRNP-RNAP polymerase II interaction. By performing chromatin immunoprecipitation sequencing for phosphorylation of Ser2 and Ser5 of the C-terminal domain of RPB1, the largest subunit of RNAP polymerase II, we showed that transcription elongation was disturbed upon U1 AMO treatment, with a particular high phosphorylation of Ser2 signal at intronic cryptic polyadenylation sites (PASs). In addition, we showed that core 3'processing factors CPSF/CstF are involved in the processing of intronic cryptic PAS. Their recruitment accumulated toward cryptic PASs upon U1 AMO treatment, as indicated by chromatin immunoprecipitation sequencing and individual-nucleotide resolution CrossLinking and ImmunoPrecipitation sequencing analysis. Conclusively, our data suggest that disruption of U1 snRNP structure mediated by U1 AMO provides a key for understanding the U1 telescripting mechanism.

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq.

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.

Selecting Representative Samples From Complex Biological Datasets Using K-Medoids Clustering.

Rapid growth of single-cell sequencing techniques enables researchers to investigate almost millions of cells with diverse properties in a single experiment. Meanwhile, it also presents great challenges for selecting representative samples from massive single-cell populations for further experimental characterization, which requires a robust and compact sampling with balancing diverse properties of different priority levels. The conventional sampling methods fail to generate representative and generalizable subsets from a massive single-cell population or more complicated ensembles. Here, we present a toolkit called Cookie which can efficiently select out the most representative samples from a massive single-cell population with diverse properties. This method quantifies the relationships/similarities among samples using their Manhattan distances by vectorizing all given properties and then determines an appropriate sample size by evaluating the coverage of key properties from multiple candidate sizes, following by a k-medoids clustering to group samples into several clusters and selects centers from each cluster as the most representatives. Comparison of Cookie with conventional sampling methods using a single-cell atlas dataset, epidemiology surveillance data, and a simulated dataset shows the high efficacy, efficiency, and flexibly of Cookie. The Cookie toolkit is implemented in R and is freely available at https://wilsonimmunologylab.github.io/Cookie/.

Plastid development of albino viviparous propagules in the woody mangrove species of Kandelia obovata.

The process of plastids developing into chloroplasts is critical for plants to survive. However, this process in woody plants is less understood. Kandelia obovata Sheue, Liu & Yong is a viviparous mangrove species; the seeds germinate on the maternal tree, and the hypocotyls continue to develop into mature propagules. We identified rare albino propagules through field observation among normal green and brown ones. Toward unveiling the propagule plastid development mechanism, albino propagule leaves only have etioplasts, low photosynthesis rates, and drastically reduced chlorophyll a/b and carotenoid contents, but with increased superoxide dismutase activities. To identify candidate genes controlling propagule plastid development, a genome-wide association study (GWAS) was performed between the albino and green propagules. Twenty-five significant single nucleotide polymorphisms (SNPs) were associated with albino propagule plastid development, the most significant SNPs being located on chromosomes 1 and 5. Significant differentially expressed genes were identified in porphyrin and chlorophyll metabolisms, carotenoid and flavonoid biosynthesis by combining transcriptome and GWAS data. In particular, KoDELLAs, encoding a transcription factor and KoCHS, encoding chalcone synthase, may be essential to regulate the albino propagules plastid development through weakened chlorophyll and flavonoid biosynthesis pathways while promoting chlorophyll degradation. Our results provide insights into genetic mechanisms regulating propagule plastid development in woody plants.

Uninterrupted embryonic growth leading to viviparous propagule formation in woody mangrove.

Vivipary is a rare sexual reproduction phenomenon where embryos germinate directly on the maternal plants. However, it is a common genetic event of woody mangroves in the Rhizophoraceae family. The ecological benefits of vivipary in mangroves include the nurturing of seedlings in harsh coastal and saline environments, but the genetic and molecular mechanisms of vivipary remain unclear. Here we investigate the viviparous embryo development and germination processes in mangrove Kandelia obovata by a transcriptomic approach. Many key biological pathways and functional genes were enriched in different tissues and stages, contributing to vivipary. Reduced production of abscisic acid set a non-dormant condition for the embryo to germinate directly. Genes involved in the metabolism of and response to other phytohormones (gibberellic acid, brassinosteroids, cytokinin, and auxin) are expressed precociously in the axis of non-vivipary stages, thus promoting the embryo to grow through the seed coat. Network analysis of these genes identified the central regulatory roles of LEC1 and FUS3, which maintain embryo identity in Arabidopsis. Moreover, photosynthesis related pathways were significantly up-regulated in viviparous embryos, and substance transporter genes were highly expressed in the seed coat, suggesting a partial self-provision and maternal nursing. We conclude that the viviparous phenomenon is a combinatorial result of precocious loss of dormancy and enhanced germination potential during viviparous seed development. These results shed light on the relationship between seed development and germination, where the continual growth of the embryo replaces a biphasic phenomenon until a mature propagule is established.

Intragenic heterochromatin-mediated alternative polyadenylation modulates miRNA and pollen development in rice.

Despite a much higher proportion of intragenic heterochromatin-containing genes in crop genomes, the importance of intragenic heterochromatin in crop development remains unclear. Intragenic heterochromatin can be recognised by a protein complex, ASI1-AIPP1-EDM2 (AAE) complex, to regulate alternative polyadenylation. Here, we investigated the impact of rice ASI1 on global poly(A) site usage through poly(A) sequencing and ASI1-dependent regulation on rice development. We found that OsASI1 is essential for rice pollen development and flowering. OsASI1 dysfunction has an important impact on global poly(A) site usage, which is closely related to heterochromatin marks. Intriguingly, OsASI1 interacts with the intronic heterochromatin of OsXRNL, a nuclear XRN family exonuclease gene involved in the processing of an miRNA precursor, to promote the processing of full-length OsXRNL and regulate miRNA abundance. We found that OsASI1-mediated regulation of pollen development partially depends on OsXRNL. Finally, we characterised the rice AAE complex and its involvement in alternative polyadenylation and pollen development. Our findings help to elucidate an epigenetic mechanism governing miRNA abundance and rice development, and provide a valuable resource for studying the epigenetic mechanisms of many important processes in crops.

Multi-omics analyses on Kandelia obovata reveal its response to transplanting and genetic differentiation among populations.

BACKGROUND: Restoration through planting is the dominant strategy to conserve mangrove ecosystems. However, many of the plantations fail to survive. Site and seeding selection matters for planting. The process of afforestation, where individuals were planted in a novel environment, is essentially human-controlled transplanting events. Trying to deepen and expand the understanding of the effects of transplanting on plants, we have performed a seven-year-long reciprocal transplant experiment on Kandelia obovata along a latitudinal gradient. RESULTS: Combined phenotypic analyses and next-generation sequencing, we found phenotypic discrepancies among individuals from different populations in the common garden and genetic differentiation among populations. The central population with abundant genetic diversity and high phenotypic plasticity had a wide plantable range. But its biomass was reduced after being transferred to other latitudes. The suppressed expression of lignin biosynthesis genes revealed by RNA-seq was responsible for the biomass reduction. Moreover, using whole-genome bisulfite sequencing, we observed modification of DNA methylation in MADS-box genes that involved in the regulation of flowering time, which might contribute to the adaptation to new environments. CONCLUSIONS: Taking advantage of classical ecological experiments as well as multi-omics analyses, our work observed morphology differences and genetic differentiation among different populations of K. obovata, offering scientific advice for the development of restoration strategy with long-term efficacy, also explored phenotypic, transcript, and epigenetic responses of plants to transplanting events between latitudes.

QuantifyPoly(A): reshaping alternative polyadenylation landscapes of eukaryotes with weighted density peak clustering.

The dynamic choice of different polyadenylation sites in a gene is referred to as alternative polyadenylation, which functions in many important biological processes. Large-scale messenger RNA 3' end sequencing has revealed that cleavage sites for polyadenylation are presented with microheterogeneity. To date, the conventional determination of polyadenylation site clusters is subjective and arbitrary, leading to inaccurate annotations. Here, we present a weighted density peak clustering method, QuantifyPoly(A), to accurately quantify genome-wide polyadenylation choices. Applying QuantifyPoly(A) on published 3' end sequencing datasets from both animals and plants, their polyadenylation profiles are reshaped into myriads of novel polyadenylation site clusters. Most of these novel polyadenylation site clusters show significantly dynamic usage across different biological samples or associate with binding sites of trans-acting factors. Upstream sequences of these clusters are enriched with polyadenylation signals UGUA, UAAA and/or AAUAAA in a species-dependent manner. Polyadenylation site clusters also exhibit species specificity, while plants ones generally show higher microheterogeneity than that of animals. QuantifyPoly(A) is broadly applicable to any types of 3' end sequencing data and species for accurate quantification and construction of the complex and dynamic polyadenylation landscape and enables us to decode alternative polyadenylation events invisible to conventional methods at a much higher resolution.

QPAT-seq, a rapid and deduplicatable method for quantification of poly(A) site usages.

Alternative polyadenylation (APA) is an essential regulatory mechanism for gene expression. The next generation sequencing provides ample opportunity to precisely delineate APA sites genome-wide. Various methods for profiling transcriptome-wide poly(A) sites were developed. By comparing available methods, the ways for adding sequencing adaptors to fit with the Illumina sequencing platform are different. These methods have identified more than 50% genes that undergo APA in eukaryotes. However, due to the unbalanced PCR during library preparation, accurate quantification of poly(A) sites is still a challenge. Here, we describe an updated poly(A) tag sequencing method that incorporates unique molecular identifier (UMI) into the adaptor for removing quantification bias induced by PCR duplicates. Hence, quantification of poly(A) site usages can be achieved by counting UMIs. This protocol, quantifying poly(A) tag sequencing (QPAT-seq), can be finished in 1 day with reduced cost, and is particularly useful for application with a large number of samples.

Alternative polyadenylated mRNAs behave as asynchronous rhythmic transcription in Arabidopsis.

Alternative polyadenylation (APA) is a widespread post-transcriptional modification method that changes the 3' ends of transcripts by altering poly(A) site usage. However, the longitudinal transcriptomic 3' end profile and its mechanism of action are poorly understood. We applied diurnal time-course poly(A) tag sequencing (PAT-seq) for Arabidopsis and identified 3284 genes that generated both rhythmic and arrhythmic transcripts. These two classes of transcripts appear to exhibit dramatic differences in expression and translation activisty. The asynchronized transcripts derived by APA are embedded with different poly(A) signals, especially for rhythmic transcripts, which contain higher AAUAAA and UGUA signal proportions. The Pol II occupancy maximum is reached upstream of rhythmic poly(A) sites, while it is present directly at arrhythmic poly(A) sites. Integrating H3K9ac and H3K4me3 time-course data analyses revealed that transcriptional activation of histone markers may be involved in the differentiation of rhythmic and arrhythmic APA transcripts. These results implicate an interplay between histone modification and RNA 3'-end processing, shedding light on the mechanism of transcription rhythm and alternative polyadenylation.

movAPA: modeling and visualization of dynamics of alternative polyadenylation across biological samples.

MOTIVATION: Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3' end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses. RESULTS: We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3' UTR shortening/lengthening events between conditions. APA site switching involving non-3' UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells. AVAILABILITY AND IMPLEMENTATION: https://github.com/BMILAB/movAPA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

scAPAtrap: identification and quantification of alternative polyadenylation sites from single-cell RNA-seq data.

Alternative polyadenylation (APA) generates diverse mRNA isoforms, which contributes to transcriptome diversity and gene expression regulation by affecting mRNA stability, translation and localization in cells. The rapid development of 3' tag-based single-cell RNA-sequencing (scRNA-seq) technologies, such as CEL-seq and 10x Genomics, has led to the emergence of computational methods for identifying APA sites and profiling APA dynamics at single-cell resolution. However, existing methods fail to detect the precise location of poly(A) sites or sites with low read coverage. Moreover, they rely on priori genome annotation and can only detect poly(A) sites located within or near annotated genes. Here we proposed a tool called scAPAtrap for detecting poly(A) sites at the whole genome level in individual cells from 3' tag-based scRNA-seq data. scAPAtrap incorporates peak identification and poly(A) read anchoring, enabling the identification of the precise location of poly(A) sites, even for sites with low read coverage. Moreover, scAPAtrap can identify poly(A) sites without using priori genome annotation, which helps locate novel poly(A) sites in previously overlooked regions and improve genome annotation. We compared scAPAtrap with two latest methods, scAPA and Sierra, using scRNA-seq data from different experimental technologies and species. Results show that scAPAtrap identified poly(A) sites with higher accuracy and sensitivity than competing methods and could be used to explore APA dynamics among cell types or the heterogeneous APA isoform expression in individual cells. scAPAtrap is available at https://github.com/BMILAB/scAPAtrap.

HDA6-dependent histone deacetylation regulates mRNA polyadenylation in Arabidopsis.

Eukaryotic histone deacetylation, critical for maintaining nucleosome structure and regulating gene expression, is mediated by histone deacetylases (HDACs). Although nucleosomes have been reported to regulate mRNA polyadenylation in humans, the role of HDACs in regulating polyadenylation has not been uncovered. Taking advantage of phenotypic studies on Arabidopsis, HDA6 (one of HDACs) was found to be a critical part of many biological processes. Here, we report that HDA6 affects mRNA polyadenylation in Arabidopsis Poly(A) sites of up-regulated transcripts are closer to the histone acetylation peaks in hda6 compared to the wild-type Col-0. HDA6 is required for the deacetylation of histones around DNA on nucleosomes, which solely coincides with up-regulated or uniquely presented poly(A) sites in hda6 Furthermore, defective HDA6 results in an overrepresentation of the canonical poly(A) signal (AAUAAA) usage. Chromatin loci for generating AAUAAA-type transcripts have a comparatively low H3K9K14ac around poly(A) sites when compared to other noncanonical poly(A) signal-containing transcripts. These results indicate that HDA6 regulates polyadenylation in a histone deacetylation-dependent manner in Arabidopsis.

Discovery of alternative polyadenylation dynamics from single cell types.

Alternative polyadenylation (APA) occurs in the process of mRNA maturation by adding a poly(A) tail at different locations, resulting increased diversity of mRNA isoforms and contributing to the complexity of gene regulatory network. Benefit from the development of high-throughput sequencing technologies, we could now delineate APA profiles of transcriptomes at an unprecedented pace. Especially the single cell RNA sequencing (scRNA-seq) technologies provide us opportunities to interrogate biological details of diverse and rare cell types. Despite increasing evidence showing that APA is involved in the cell type-specific regulation and function, efficient and specific laboratory methods for capturing poly(A) sites at single cell resolution are underdeveloped to date. In this review, we summarize existing experimental and computational methods for the identification of APA dynamics from diverse single cell types. A future perspective is also provided.

A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data.

Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.

scHinter: imputing dropout events for single-cell RNA-seq data with limited sample size.

MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) is fast and becoming a powerful technique for studying dynamic gene regulation at unprecedented resolution. However, scRNA-seq data suffer from problems of extremely high dropout rate and cell-to-cell variability, demanding new methods to recover gene expression loss. Despite the availability of various dropout imputation approaches for scRNA-seq, most studies focus on data with a medium or large number of cells, while few studies have explicitly investigated the differential performance across different sample sizes or the applicability of the approach on small or imbalanced data. It is imperative to develop new imputation approaches with higher generalizability for data with various sample sizes. RESULTS: We proposed a method called scHinter for imputing dropout events for scRNA-seq with special emphasis on data with limited sample size. scHinter incorporates a voting-based ensemble distance and leverages the synthetic minority oversampling technique for random interpolation. A hierarchical framework is also embedded in scHinter to increase the reliability of the imputation for small samples. We demonstrated the ability of scHinter to recover gene expression measurements across a wide spectrum of scRNA-seq datasets with varied sample sizes. We comprehensively examined the impact of sample size and cluster number on imputation. Comprehensive evaluation of scHinter across diverse scRNA-seq datasets with imbalanced or limited sample size showed that scHinter achieved higher and more robust performance than competing approaches, including MAGIC, scImpute, SAVER and netSmooth. AVAILABILITY AND IMPLEMENTATION: Freely available for download at https://github.com/BMILAB/scHinter. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

scDAPA: detection and visualization of dynamic alternative polyadenylation from single cell RNA-seq data.

MOTIVATION: Alternative polyadenylation (APA) plays a key post-transcriptional regulatory role in mRNA stability and functions in eukaryotes. Single cell RNA-seq (scRNA-seq) is a powerful tool to discover cellular heterogeneity at gene expression level. Given 3' enriched strategy in library construction, the most commonly used scRNA-seq protocol-10× Genomics enables us to improve the study resolution of APA to the single cell level. However, currently there is no computational tool available for investigating APA profiles from scRNA-seq data. RESULTS: Here, we present a package scDAPA for detecting and visualizing dynamic APA from scRNA-seq data. Taking bam/sam files and cell cluster labels as inputs, scDAPA detects APA dynamics using a histogram-based method and the Wilcoxon rank-sum test, and visualizes candidate genes with dynamic APA. Benchmarking results demonstrated that scDAPA can effectively identify genes with dynamic APA among different cell groups from scRNA-seq data. AVAILABILITY AND IMPLEMENTATION: The scDAPA package is implemented in Shell and R, and is freely available at https://scdapa.sourceforge.io. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PlantAPAdb: A Comprehensive Database for Alternative Polyadenylation Sites in Plants.

Alternative cleavage and polyadenylation (APA) is increasingly recognized as an important regulatory mechanism in eukaryotic gene expression and is dynamically modulated in a developmental, tissue-specific, or environmentally responsive manner. Given the functional importance of APA and the rapid accumulation of APA sites in plants, a comprehensive and easily accessible APA site database is necessary for improved understanding of APA-mediated gene expression regulation. We present a database called PlantAPAdb that catalogs the most comprehensive APA site data derived from sequences from diverse 3' sequencing protocols and biological samples in plants. Currently, PlantAPAdb contains APA sites in six species, Oryza sativa (japonica and indica), Arabidopsis (Arabidopsis thaliana), Medicago truncatula, Trifolium pratense, Phyllostachys edulis, and Chlamydomonas reinhardtii APA sites in PlantAPAdb are available for bulk download and can be queried in a Google-like manner. PlantAPAdb provides rich information of the whole-genome APA sites, including genomic locations, heterogeneous cleavage sites, expression levels, and sample information. It also provides comprehensive poly(A) signals for APA sites in different genomic regions according to distinct profiles of cis-elements in plants. In addition, PlantAPAdb contains events of 3' untranslated region shortening/lengthening resulting from APA, which helps to understand the mechanisms underlying systematic changes in 3' untranslated region lengths. Additional information about conservation of APA sites in plants is also available, providing insights into the evolutionary polyadenylation configuration across species. As a user-friendly database, PlantAPAdb is a large and extendable resource for elucidating APA mechanisms, APA conservation, and gene expression regulation.