Next-Generation Sequence Databases: RNA and Genomic Informatics Resources for Plants.

We developed public web sites and resources for data access, display, and analysis of plant small RNAs. These web sites are interconnected with related data types. The current generation of these informatics tools was developed for Illumina data, evolving over more than 15 years of improvements. Our online databases have customized web interfaces to uniquely handle and display RNA-derived data from diverse plant species, ranging from Arabidopsis (Arabidopsis thaliana) to wheat (Triticum spp.), including many crop and model species. The web interface displays the abundance and genomic context of data for small RNAs, parallel analysis of RNA ends/degradome reads, RNA sequencing, and even chromatin immunoprecipitation sequencing data; it also provides information about potentially novel transcripts (antisense transcripts, alternative splice isoforms, and regulatory intergenic transcripts). Numerous options are included for downloading data as tables or via web services. Interpretation of these data is facilitated by the inclusion of extensive repeat or transposon data in our genome viewer. We have developed graphical and analytical tools, including a new viewer and a query page for the analysis of phased small RNAs; these are particularly useful for understanding the complex small RNA pathways of plants. These public databases are accessible at https://mpss.danforthcenter.org.

An integrated workflow for DNA methylation analysis.

The analysis of cytosine methylation provides a new way to assess and describe epigenetic regulation at a whole-genome level in many eukaryotes. DNA methylation has a demonstrated role in the genome stability and protection, regulation of gene expression and many other aspects of genome function and maintenance. BS-seq is a relatively unbiased method for profiling the DNA methylation, with a resolution capable of measuring methylation at individual cytosines. Here we describe, as an example, a workflow to handle DNA methylation analysis, from BS-seq library preparation to the data visualization. We describe some applications for the analysis and interpretation of these data. Our laboratory provides public access to plant DNA methylation data via visualization tools available at our "Next-Gen Sequence" websites (http://mpss.udel.edu), along with small RNA, RNA-seq and other data types.

Transcriptome dynamics through alternative polyadenylation in developmental and environmental responses in plants revealed by deep sequencing.

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.