Insights into the early transcriptomic response against watermelon mosaic virus in melon.

BACKGROUND: Watermelon mosaic virus (WMV) is one of the most prevalent viruses affecting melon worldwide. Recessive resistance to WMV in melon has previously been reported in the African accession TGR-1551. Moreover, the genomic regions associated to the resistance have also been described. Nevertheless, the transcriptomic response that might infer the resistance to this potyvirus has not been explored. RESULTS: We have performed a comparative transcriptomic analysis using mock and WMV-inoculated plants of the susceptible cultivar "Bola de oro" (BO) and a resistant RIL (Recombinant inbred line) derived from the initial cross between "TGR-1551" and BO. In total, 616 genes were identified as differentially expressed and the weighted gene co-expression network analysis (WGCNA) detected 19 gene clusters (GCs), of which 7 were differentially expressed for the genotype x treatment interaction term. SNPs with a predicted high impact on the protein function were detected within the coding regions of most of the detected DEGs. Moreover, 3 and 16 DEGs were detected within the QTL regions previously described in chromosomes 11 and 5, respectively. In addition to these two specific genomic regions, we also observde large transcriptomic changes from genes spread across the genome in the resistant plants in response to the virus infection. This early response against WMV implied genes involved in plant-pathogen interaction, plant hormone signal transduction, the MAPK signaling pathway or ubiquitin mediated proteolysis, in detriment to the photosynthetic and basal metabolites pathways. Moreover, the gene MELO3C021395, which coded a mediator of RNA polymerase II transcription subunit 33A (MED33A), has been proposed as the candidate gene located on chromosome 11 conferring resistance to WMV. CONCLUSIONS: The comparative transcriptomic analysis presented here showed that, even though the resistance to WMV in TGR-1551 has a recessive nature, it triggers an active defense response at a transcriptomic level, which involves broad-spectrum resistance mechanisms. Thus, this study represents a step forward on our understanding of the mechanisms underlaying WMV resistance in melon. In addition, it sheds light into a broader topic on the mechanisms of recessive resistances.

Variant Annotation and Functional Prediction: SnpEff.

Variant annotations, in general, refer to the process of information enrichment of genomic variants from a sequencing experiment. Typically these annotations include functional predictions, such as predicting the amino acid sequence changes from the DNA variant, predicting whether the variant will induce a splice anomaly, or predicting nonsense mediated decay. But other annotations also include combining with genomic databases, adding conservation scores, or comparing to allele frequencies from large population databases. Finally, all these annotations are combined to prioritize and filter variants into a reduced set of highly relevant variants for the study or clinical assay.

Variations in Nomenclature of Clinical Variants between Annotation Tools.

BACKGROUND: Accurate nomenclature of variants is an essential element for genetic diagnosis and patient care. OBJECTIVE: To investigate annotation differences of clinical variants between annotation tools. METHODS: We analyzed 218,156 clinical variants from the Human Gene Mutation Database. Multiple nomenclatures based on RefSeq transcripts were provided using ANNOVAR and snpEff. RESULTS: The concordance rate between ANNOVAR and snpEff was approximately 85%. Based on the Human Genome Variation Society (HGVS) nomenclature, snpEff was more accurate than ANNOVAR (coding variants, 99.3% vs 84.9%; protein variants, 94.3% vs 79.8%). When annotating each variant with ANNOVAR and snpEff, the accuracy of nomenclature was 99.5%. CONCLUSIONS: There were substantial differences between ANNOVAR and snpEff annotations. The findings of this study suggest that simultaneous use of multiple annotation tools could decrease nomenclature errors and contribute to providing standardized clinical reporting.

Validation of Genotyping by Sequencing Using Transcriptomics for Diversity and Application of Genomic Selection in Tetraploid Potato.

Potato is an important food crop due to its increasing consumption, and as a result, there is demand for varieties with improved production. However, the current status of breeding for improved varieties is a long process which relies heavily on phenotypic evaluation and dated molecular techniques and has little emphasis on modern genotyping approaches. Evaluation and selection before a cultivar is commercialized typically takes 10-15 years. Molecular markers have been developed for disease and pest resistance, resulting in initial marker-assisted selection in breeding. This study has evaluated and implemented a high-throughput transcriptome sequencing method for dense marker discovery in potato for the application of genomic selection. An Australian relevant collection of commercial cultivars was selected, and identification and distribution of high quality SNPs were examined using standard bioinformatic pipelines and a custom approach for the prediction of allelic dosage. As a result, a large number of SNP markers were identified and filtered to generate a high-quality subset that was then combined with historic phenotypic data to assess the approach for genomic selection. Genomic selection potential was predicted for highly heritable traits and the approach demonstrated advantages over the previously used technologies in terms of markers identified as well as costs incurred. The high-quality SNP list also provided acceptable genome coverage which demonstrates its applicability for much larger future studies. This SNP list was also annotated to provide an indication of function and will serve as a resource for the community in future studies. Genome wide marker tools will provide significant benefits for potato breeding efforts and the application of genomic selection will greatly enhance genetic progress.