Long-read sequencing technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelming. To assist in the design and analysis of long-read sequencing projects, we review the current landscape of available tools and present an online interactive database, long-read-tools.org, to facilitate their browsing. We further focus on the principles of error correction, base modification detection, and long-read transcriptomics analysis and highlight the challenges that remain.

DNA methylation in plants is traditionally partitioned into CG, CHG and CHH contexts (with H any nucleotide but G). By investigating DNA methylation patterns in trinucleotide contexts in four angiosperm species, we show that such a representation hides spatial and functional partitioning of different methylation pathways and is incomplete. CG methylation (mCG) is largely context-independent whereas, at CHG motifs, there is under-representation of mCCG in pericentric regions of A. thaliana and tomato and throughout the chromosomes of maize and rice. In A. thaliana the biased representation of mCCG in heterochromatin is related to specificities of H3K9 methyltransferase SUVH family members. At CHH motifs there is an over-representation of different variant forms of mCHH that, similarly to mCCG hypomethylation, is partitioned into the pericentric regions of the two dicots but dispersed in the monocot chromosomes. The over-represented mCHH motifs in A. thaliana associate with specific types of transposon including both class I and II elements. At mCHH the contextual bias is due to the involvement of various chromomethyltransferases whereas the context-independent CHH methylation in A. thaliana and tomato is mediated by the RNA-directed DNA methylation process that is most active in the gene-rich euchromatin. This analysis therefore reveals that the sequence context of the methylome of plant genomes is informative about the mechanisms associated with maintenance of methylation and the overlying chromatin structure.

BackgroundSeed germination involves progression from complete metabolic dormancy to a highly active, growing seedling. Many factors regulate germination and these interact extensively, forming a complex network of inputs that control the seed-to-seedling transition. Our understanding of the direct regulation of gene expression and the dynamic changes in the epigenome and small RNAs during germination is limited. The interactions between genome, transcriptome and epigenome must be revealed in order to identify the regulatory mechanisms that control seed germination.ResultsWe present an integrated analysis of high-resolution RNA sequencing, small RNA sequencing and MethylC sequencing over ten developmental time points in Arabidopsis thaliana seeds, finding extensive transcriptomic and epigenomic transformations associated with seed germination. We identify previously unannotated loci from which messenger RNAs are expressed transiently during germination and find widespread alternative splicing and divergent isoform abundance of genes involved in RNA processing and splicing. We generate the first dynamic transcription factor network model of germination, identifying known and novel regulatory factors. Expression of both microRNA and short interfering RNA loci changes significantly during germination, particularly between the seed and the post-germinative seedling. These are associated with changes in gene expression and large-scale demethylation observed towards the end of germination, as the epigenome transitions from an embryo-like to a vegetative seedling state.ConclusionsThis study reveals the complex dynamics and interactions of the transcriptome and epigenome during seed germination, including the extensive remodelling of the seed DNA methylome from an embryo-like to vegetative-like state during the seed-to-seedling transition. Data are available for exploration in a user-friendly browser at https://jbrowse.latrobe.edu.au/germination_epigenome.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1302-3) contains supplementary material, which is available to authorized users.