No abstract

Sugarcane cultivars are interspecific hybrids with an aneuploid, highly heterozygous polyploid genome. The complexity of the sugarcane genome is the main obstacle to the use of marker-assisted selection in sugarcane breeding. Given the promising results of recent studies of plant genomic selection, we explored the feasibility of genomic selection in this complex polyploid crop. Genetic values were predicted in two independent panels, each composed of 167 accessions representing sugarcane genetic diversity worldwide. Accessions were genotyped with 1,499 DArT markers. One panel was phenotyped in Reunion Island and the other in Guadeloupe. Ten traits concerning sugar and bagasse contents, digestibility and composition of the bagasse, plant morphology, and disease resistance were used. We used four statistical predictive models: bayesian LASSO, ridge regression, reproducing kernel Hilbert space, and partial least square regression. The accuracy of the predictions was assessed through the correlation between observed and predicted genetic values by cross validation within each panel and between the two panels. We observed equivalent accuracy among the four predictive models for a given trait, and marked differences were observed among traits. Depending on the trait concerned, within-panel cross validation yielded median correlations ranging from 0.29 to 0.62 in the Reunion Island panel and from 0.11 to 0.5 in the Guadeloupe panel. Cross validation between panels yielded correlations ranging from 0.13 for smut resistance to 0.55 for brix. This level of correlations is promising for future implementations. Our results provide the first validation of genomic selection in sugarcane.

Comprehensive inventories of plant viral diversity are essential for effective quarantine and sanitation efforts. The safety of regulated plant material exchanges presently relies heavily on techniques such as PCR or nucleic acid hybridisation, which are only suited to the detection and characterisation of specific, well characterised pathogens. Here, we demonstrate the utility of sequence-independent next generation sequencing (NGS) of both virus-derived small interfering RNAs (siRNAs) and virion-associated nucleic acids (VANA) for the detailed identification and characterisation of viruses infecting two quarantined sugarcane plants. Both plants originated from Egypt and were known to be infected with Sugarcane streak Egypt Virus (SSEV; Genus Mastrevirus, Family Geminiviridae), but were revealed by the NGS approaches to also be infected by a second highly divergent mastrevirus, here named Sugarcane white streak Virus (SWSV). This novel virus had escaped detection by all routine quarantine detection assays and was found to also be present in sugarcane plants originating from Sudan. Complete SWSV genomes were cloned and sequenced from six plants and all were found to share >91% genome-wide identity. With the exception of two SWSV variants, which potentially express unusually large RepA proteins, the SWSV isolates display genome characteristics very typical to those of all other previously described mastreviruses. An analysis of virus-derived siRNAs for SWSV and SSEV showed them to be strongly influenced by secondary structures within both genomic single stranded DNA and mRNA transcripts. In addition, the distribution of siRNA size frequencies indicates that these mastreviruses are likely subject to both transcriptional and post-transcriptional gene silencing. Our study stresses the potential advantages of NGS-based virus metagenomic screening in a plant quarantine setting and indicates that such techniques could dramatically reduce the numbers of non-intercepted virus pathogens passing through plant quarantine stations.