Alternative polyadenylation (APA) has been shown to play an important role in gene expression regulation in animals and plants. However, the extent of sense and antisense APA at the genome level is not known. We developed a deep-sequencing protocol that queries the junctions of 3′UTR and poly(A) tails and confidently maps the poly(A) tags to the annotated genome. The results of this mapping show that 70% of Arabidopsis genes use more than one poly(A) site, excluding microheterogeneity. Analysis of the poly(A) tags reveal extensive APA in introns and coding sequences, results of which can significantly alter transcript sequences and their encoding proteins. Although the interplay of intron splicing and polyadenylation potentially defines poly(A) site uses in introns, the polyadenylation signals leading to the use of CDS protein-coding region poly(A) sites are distinct from the rest of the genome. Interestingly, a large number of poly(A) sites correspond to putative antisense transcripts that overlap with the promoter of the associated sense transcript, a mode previously demonstrated to regulate sense gene expression. Our results suggest that APA plays a far greater role in gene expression in plants than previously expected.

The position of a poly(A) site of eukaryotic mRNA is determined by sequence signals in pre-mRNA and a group of polyadenylation factors. To reveal rice poly(A) signals at a genome level, we constructed a dataset of 55 742 authenticated poly(A) sites and characterized the poly(A) signals. This resulted in identifying the typical tripartite cis-elements, including FUE, NUE and CE, as previously observed in Arabidopsis. The average size of the 3′-UTR was 289 nucleotides. When mapped to the genome, however, 15% of these poly(A) sites were found to be located in the currently annotated intergenic regions. Moreover, an extensive alternative polyadenylation profile was evident where 50% of the genes analyzed had more than one unique poly(A) site (excluding microheterogeneity sites), and 13% had four or more poly(A) sites. About 4% of the analyzed genes possessed alternative poly(A) sites at their introns, 5′-UTRs, or protein coding regions. The authenticity of these alternative poly(A) sites was partially confirmed using MPSS data. Analysis of nucleotide profile and signal patterns indicated that there may be a different set of poly(A) signals for those poly(A) sites found in the coding regions. Based on the features of rice poly(A) signals, an updated algorithm termed PASS-Rice was designed to predict poly(A) sites.

Alternative polyadenylation (APA) has been increasingly recognized as a crucial mechanism that contributes to transcriptome diversity and gene expression regulation. As RNA-seq has become a routine protocol for transcriptome analysis, it is of great interest to leverage such unprecedented collection of RNA-seq data by new computational methods to extract and quantify APA dynamics in these transcriptomes. However, research progress in this area has been relatively limited. Conventional methods rely on either transcript assembly to determine transcript 3′ ends or annotated poly(A) sites. Moreover, they can neither identify more than two poly(A) sites in a gene nor detect dynamic APA site usage considering more than two poly(A) sites. We developed an approach called APAtrap based on the mean squared error model to identify and quantify APA sites from RNA-seq data. APAtrap is capable of identifying novel 3′ UTRs and 3′ UTR extensions, which contributes to locating potential poly(A) sites in previously overlooked regions and improving genome annotations. APAtrap also aims to tally all potential poly(A) sites and detect genes with differential APA site usages between conditions. Extensive comparisons of APAtrap with two other latest methods, ChangePoint and DaPars, using various RNA-seq datasets from simulation studies, human and Arabidopsis demonstrate the efficacy and flexibility of APAtrap for any organisms with an annotated genome. Freely available for download at https://apatrap.sourceforge.io. Supplementary data are available at Bioinformatics online.

Polyadenylation sites mark the ends of mRNA transcripts. Alternative polyadenylation (APA) may alter sequence elements and/or the coding capacity of transcripts, a mechanism that has been demonstrated to regulate gene expression and transcriptome diversity. To study the role of APA in transcriptome dynamics, we analyzed a large-scale data set of RNA “tags” that signify poly(A) sites and expression levels of mRNA. These tags were derived from a wide range of tissues and developmental stages that were mutated or exposed to environmental treatments, and generated using digital gene expression (DGE)–based protocols of the massively parallel signature sequencing (MPSS-DGE) and the Illumina sequencing-by-synthesis (SBS-DGE) sequencing platforms. The data offer a global view of APA and how it contributes to transcriptome dynamics. Upon analysis of these data, we found that ∼60% of Arabidopsis genes have multiple poly(A) sites. Likewise, ∼47% and 82% of rice genes use APA, supported by MPSS-DGE and SBS-DGE tags, respectively. In both species, ∼49%–66% of APA events were mapped upstream of annotated stop codons. Interestingly, 10% of the transcriptomes are made up of APA transcripts that are differentially distributed among developmental stages and in tissues responding to environmental stresses, providing an additional level of transcriptome dynamics. Examples of pollen-specific APA switching and salicylic acid treatment-specific APA clearly demonstrated such dynamics. The significance of these APAs is more evident in the 3034 genes that have conserved APA events between rice and Arabidopsis.

The Arabidopsis thaliana ortholog of the 30-kD subunit of the mammalian Cleavage and Polyadenylation Specificity Factor (CPSF30) has been implicated in the responses of plants to oxidative stress, suggesting a role for alternative polyadenylation. To better understand this, poly(A) site choice was studied in a mutant (oxt6) deficient in CPSF30 expression using a genome-scale approach. The results indicate that poly(A) site choice in a large majority of Arabidopsis genes is altered in the oxt6 mutant. A number of poly(A) sites were identified that are seen only in the wild type or oxt6 mutant. Interestingly, putative polyadenylation signals associated with sites that are seen only in the oxt6 mutant are decidedly different from the canonical plant polyadenylation signal, lacking the characteristic A-rich near-upstream element (where AAUAAA can be found); this suggests that CPSF30 functions in the handling of the near-upstream element. The sets of genes that possess sites seen only in the wild type or mutant were enriched for those involved in stress and defense responses, a result consistent with the properties of the oxt6 mutant. Taken together, these studies provide new insights into the mechanisms and consequences of CPSF30-mediated alternative polyadenylation.

Alternative polyadenylation (APA), in which a transcript uses one of the poly(A) sites to define its 3′-end, is a common regulatory mechanism in eukaryotic gene expression. However, the potential of APA in determining crop agronomic traits remains elusive. This study systematically tallied poly(A) sites of 14 different rice tissues and developmental stages using the poly(A) tag sequencing (PAT-seq) approach. The results indicate significant involvement of APA in developmental and quantitative trait loci (QTL) gene expression. About 48% of all expressed genes use APA to generate transcriptomic and proteomic diversity. Some genes switch APA sites, allowing differentially expressed genes to use alternate 3′ UTRs. Interestingly, APA in mature pollen is distinct where differential expression levels of a set of poly(A) factors and different distributions of APA sites are found, indicating a unique mRNA 3′-end formation regulation during gametophyte development. Equally interesting, statistical analyses showed that QTL tends to use APA for regulation of gene expression of many agronomic traits, suggesting a potential important role of APA in rice production. These results provide thus far the most comprehensive and high-resolution resource for advanced analysis of APA in crops and shed light on how APA is associated with trait formation in eukaryotes.