Search

Additional file 3: Figure S18. Comparison of AtIso transcripts and SJs to Araport and AtRTD2.

Additional file 2: Fig. S1. Iso-seq transcripts contain false SJs prior to accurate SJ determination and filtering. Fig. S2. Determination of TSS and TES sites for genes with high and low abundance reads. Fig. S3. Comparison of AtIso TSSs and TESs with previously published transcript start and end sites. Fig. S4. Generation of high-level transcripts. Fig. S5. Number of genes and transcripts contributed to AtIso from each Iso-seq library. Fig. S6. Saturation curve of increase in unique genes and transcripts added to AtIso with addition of each library. Fig. S7. SQANTI3 assessment of quality of long read transcripts in AtRTD3 and AtIso. Fig. S8. Increased number of transcript isoforms in AtRTD3. Fig. S9. Genes with characterised different TSS. Fig. S10. Genes with characterised alternative TES. Fig. S11. Confirmation of AS variant isoforms in the lncRNA, FLORE. Fig. S12. Novel genes in AtRTD3 – lncRNAs. Fig. S13. Chimeric transcripts. Fig. S14. Correlation of splicing ratios calculated from the RNA-seq and HR RT-PCR data including outliers. Fig. S15. Accurate Iso-seq transcript determination identifies THIC RNAs produced by riboswitch. Fig. S16. Novel cold-induced isoform of CIPK1 from AtRTD3. Fig. S17. Novel transcript isoform in AtRTD3 affects expression levels of main transcripts compared to AtRTD2.

Additional file 4: Review history.

Storage ability of trifoliate yam (Dioscorea dumetorum) is restricted by a severe post-harvest hardening (PHH) phenomenon, which starts within the first 24 h after harvest and renders tubers inedible. Previous work has only focused on the biochemical changes affecting PHH in D. dumetorum. To the best of our knowledge, the candidate genes responsible for the hardening of D. dumetorum have not been identified. Here, transcriptome analyses of D. dumetorum tubers were performed in yam tubers of four developmental stages: 4 months after emergence (4MAE), immediately after harvest (AH), 3 days after harvest (3DAH) and 14 days after harvest (14DAH) of four accessions (Bangou 1, Bayangam 2, Fonkouankem 1, and Ibo sweet 3) using RNA-Seq. In total, between AH and 3DAH, 165, 199, 128 and 61 differentially expressed genes (DEGs) were detected in Bayangam 2, Fonkouankem 1, Bangou 1 and Ibo sweet 3, respectively. Functional analysis of DEGs revealed that genes encoding for CELLULOSE SYNTHASE A (CESA), XYLAN O-ACETYLTRANSFERASE (XOAT), CHLOROPHYLL A/B BINDING PROTEIN 1, 2, 3, 4 (LHCB1, LHCB2, LHCB3, and LCH4) and an MYB transcription factor were predominantly and significantly up-regulated 3DAH, implying that these genes were potentially involved in the PHH as confirmed by qRT-PCR. A hypothetical mechanism of this phenomenon and its regulation has been proposed. These findings provide the first comprehensive insights into gene expression in yam tubers after harvest and valuable information for molecular breeding against the PHH.

Background Alternative splicing (AS) is a process which generates several distinct mRNA isoforms from the same gene by splicing different portions out of the precursor transcript. Due to the (patho-)physiological importance of AS, a complete inventory of AS is of great interest. While this is in reach for human and mammalian model organisms, our knowledge of AS in plants has remained more incomplete. Experimental approaches for monitoring AS are either based on transcript sequencing or rely on hybridization to DNA microarrays. Among the microarray platforms facilitating the discovery of AS events, tiling arrays are well-suited for identifying intron retention, the most prevalent type of AS in plants. However, analyzing tiling array data is challenging, because of high noise levels and limited probe coverage. Results In this work, we present a novel method to detect intron retentions (IR) and exon skips (ES) from tiling arrays. While statistical tests have typically been proposed for this purpose, our method instead utilizes support vector machines (SVMs) which are appreciated for their accuracy and robustness to noise. Existing EST and cDNA sequences served for supervised training and evaluation. Analyzing a large collection of publicly available microarray and sequence data for the model plant A. thaliana, we demonstrated that our method is more accurate than existing approaches. The method was applied in a genome-wide screen which resulted in the discovery of 1,355 IR events. A comparison of these IR events to the TAIR annotation and a large set of short-read RNA-seq data showed that 830 of the predicted IR events are novel and that 525 events (39%) overlap with either the TAIR annotation or the IR events inferred from the RNA-seq data. Conclusions The method developed in this work expands the scarce repertoire of analysis tools for the identification of alternative mRNA splicing from whole-genome tiling arrays. Our predictions are highly enriched with known AS events and complement the A. thaliana genome annotation with respect to AS. Since all predicted AS events can be precisely attributed to experimental conditions, our work provides a basis for follow-up studies focused on the elucidation of the regulatory mechanisms underlying tissue-specific and stress-dependent AS in plants.