No abstract

Coconut (Cocos nucifera L.), a member of the palm family (Arecaceae), is one of the most economically important crops in tropics, serving as an important source of food, drink, fuel, medicine, and construction material. Here we report an assembly of the coconut (C. nucifera, Oman local Tall cultivar) mitochondrial (mt) genome based on next-generation sequencing data. This genome, 678,653bp in length and 45.5% in GC content, encodes 72 proteins, 9 pseudogenes, 23 tRNAs, and 3 ribosomal RNAs. Within the assembly, we find that the chloroplast (cp) derived regions account for 5.07% of the total assembly length, including 13 proteins, 2 pseudogenes, and 11 tRNAs. The mt genome has a relatively large fraction of repeat content (17.26%), including both forward (tandem) and inverted (palindromic) repeats. Sequence variation analysis shows that the Ti/Tv ratio of the mt genome is lower as compared to that of the nuclear genome and neutral expectation. By combining public RNA-Seq data for coconut, we identify 734 RNA editing sites supported by at least two datasets. In summary, our data provides the second complete mt genome sequence in the family Arecaceae, essential for further investigations on mitochondrial biology of seed plants.

RNA editing is a post-transcriptional or cotranscriptional process that changes the sequence of the precursor transcript by substitutions, insertions, or deletions. Almost all of the land plants undergo RNA editing in organelles (plastids and mitochondria). Although several software tools have been developed to identify RNA editing events, there has been a great challenge to distinguish true RNA editing events from genome variation, sequencing errors, and other factors. Here we introduce REDO, a comprehensive application tool for identifying RNA editing events in plant organelles based on variant call format files from RNA-sequencing data. REDO is a suite of Perl scripts that illustrate a bunch of attributes of RNA editing events in figures and tables. REDO can also detect RNA editing events in multiple samples simultaneously and identify the significant differential proportion of RNA editing loci. Comparing with similar tools, such as REDItools, REDO runs faster with higher accuracy, and more specificity at the cost of slightly lower sensitivity. Moreover, REDO annotates each RNA editing site in RNAs, whereas REDItools reports only possible RNA editing sites in genome, which need additional steps to obtain RNA editing profiles for RNAs. Overall, REDO can identify potential RNA editing sites easily and provide several functions such as detailed annotations, statistics, figures, and significantly differential proportion of RNA editing sites among different samples.

The rapid development of high-throughput sequencing technologies has led to a dramatic decrease in the money and time required for de novo genome sequencing or genome resequencing projects, with new genome sequences constantly released every week. Among such projects, the plethora of updated genome assemblies induces the requirement of version-dependent annotation files and other compatible public dataset for downstream analysis. To handle these tasks in an efficient manner, we developed the reference-based genome assembly and annotation tool (RGAAT), a flexible toolkit for resequencing-based consensus building and annotation update. RGAAT can detect sequence variants with comparable precision, specificity, and sensitivity to GATK and with higher precision and specificity than Freebayes and SAMtools on four DNA-seq datasets tested in this study. RGAAT can also identify sequence variants based on cross-cultivar or cross-version genomic alignments. Unlike GATK and SAMtools/BCFtools, RGAAT builds the consensus sequence by taking into account the true allele frequency. Finally, RGAAT generates a coordinate conversion file between the reference and query genomes using sequence variants and supports annotation file transfer. Compared to the rapid annotation transfer tool (RATT), RGAAT displays better performance characteristics for annotation transfer between different genome assemblies, strains, and species. In addition, RGAAT can be used for genome modification, genome comparison, and coordinate conversion. RGAAT is available at https://sourceforge.net/projects/rgaat/ and https://github.com/wushyer/RGAAT_v2 at no cost.

MicroRNAs (miRNAs) play crucial roles in multiple stages of plant development and regulate gene expression at posttranscriptional and translational levels. In this study, we first identified 238 conserved miRNAs in date palm (Phoenix dactylifera) based on a high-quality genome assembly and defined 78 fruit-development-associated (FDA) miRNAs, whose expression profiles are variable at different fruit development stages. Using experimental data, we subsequently detected 276 novel P. dactylifera-specific FDA miRNAs and predicted their targets. We also revealed that FDA miRNAs function mainly in regulating genes involved in starch/sucrose metabolisms and other carbon metabolic pathways; among them, 221 FDA miRNAs exhibit negative correlation with their corresponding targets, which suggests their direct regulatory roles on mRNA targets. Our data define a comprehensive set of conserved and novel FDA miRNAs along with their expression profiles, which provide a basis for further experimentation in assigning discrete functions of these miRNAs in P. dactylifera fruit development.