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Rose rosette disease (RRD), caused by the rose rosette emaravirus (RRV), is a major viral disease in roses (Rosa sp.) that threatens the rose industry. Recent studies have revealed quantitative trait loci (QTL) for reduced susceptibility to RRD in the linkage groups (LGs) 1, 5, 6, and 7 in tetraploid populations and the LGs 1, 3, 5, and 6 in diploid populations. In this study, we seek to better localize and understand the relationship between QTL identified in both diploid and tetraploid populations. We do so by remapping the populations found in these studies and performing a meta-analysis. This analysis reveals that the peaks and intervals for QTL using diploid and tetraploid populations co-localized on LG 1, suggesting that these are the same QTL. The same was seen on LG 3. Three meta-QTL were identified on LG 5, and two were discovered on LG 6. The meta-QTL on LG 1, MetaRRD1.1, had a confidence interval (CI) of 10.53 cM. On LG 3, MetaRRD3.1 had a CI of 5.94 cM. MetaRRD5.1 had a CI of 17.37 cM, MetaRRD5.2 had a CI of 4.33 cM, and MetaRRD5.3 had a CI of 21.95 cM. For LG 6, MetaRRD6.1 and MetaRRD6.2 had CIs of 9.81 and 8.81 cM, respectively. The analysis also led to the identification of potential disease resistance genes, with a primary interest in genes localized in meta-QTL intervals on LG 5 as this LG was found to explain the greatest proportion of phenotypic variance for RRD resistance. The results from this study may be used in the design of more robust marker-based selection tools to track and use a given QTL in a plant breeding context.

Rose rosette disease (RRD), caused by the Rose rosette emaravirus (RRV), is a major threat to the garden rose industry in the United States. There has been limited work on the genetics of host plant resistance to RRV. Two interconnected tetraploid garden rose F1 biparental mapping populations were created to develop high-quality tetraploid rose linkage maps that allowed the discovery of RRD resistance quantitative trait loci (QTLs) on linkage groups (LGs) 5, 6, and 7. These QTLs individually accounted for around 18–40% of the phenotypic variance. The locus with the greatest effect on partial resistance was found in LG 5. Most individuals with the LG 5 QTL were in the simplex configuration; however, two individuals were duplex (likely due to double reduction). Identification of resistant individuals and regions of interest can help the development of diagnostic markers for marker-assisted selection in a breeding program.

Rose rosette disease (RRD) caused by the rose rosette emaravirus (RRV) and transmitted by the eriophyid mite Phyllocoptes fructiphilus (Pf), both native to North America, has caused significant damage to roses over the last several decades. As cultural and chemical control of this disease is difficult and expensive, a field trial was established to systematically screen rose germplasm for potential sources of resistance. One hundred and eight rose accessions representing the diversity of rose germplasm were planted in Tennessee and Delaware, managed to encourage disease development, and evaluated for symptom development and viral presence for three years. All major commercial rose cultivars were susceptible to this viral disease to varying levels. The rose accessions with no or few symptoms were species accessions from the sections Cinnamomeae, Carolinae, Bracteatae, and Systylae or hybrids with these. Among these, some were asymptomatic; they displayed no symptoms but were infected by the virus. Their potential depends on their ability to serve as a source of viruses. The next step is to understand the mechanism of resistance and genetic control of the various sources of resistance identified.

Resistance to rose rosette disease (RRD), a fatal disease of roses (Rosa spp.), is a high priority for rose breeding. As RRD resistance is time-consuming to phenotype, the identification of genetic markers for resistance could expedite breeding efforts. However, little is known about the genetics of RRD resistance. Therefore, we performed a quantitative trait locus (QTL) analysis on a set of inter-related diploid rose populations phenotyped for RRD resistance and identified four QTLs. Two QTLs were found in multiple years. The most consistent QTL is qRRV_TX2WSE_ch5, which explains approximately 20% and 40% of the phenotypic variation in virus quantity and severity of RRD symptoms, respectively. The second, a QTL on chromosome 1, qRRD_TX2WSE_ch1, accounts for approximately 16% of the phenotypic variation for severity. Finally, a third QTL on chromosome 3 was identified only in the multiyear analysis, and a fourth on chromosome 6 was identified in data from one year only. In addition, haplotypes associated with significant changes in virus quantity and severity were identified for qRRV_TX2WSE_ch5 and qRRD_TX2WSE_ch1. This research represents the first report of genetic determinants of resistance to RRD. In addition, marker trait associations discovered here will enable better parental selection when breeding for RRD resistance and pave the way for marker-assisted selection for RRD resistance.

Rose rosette disease (RRD) whose causal agent, the Emaravirus Rose rosette virus (RRV), was only recently identified has caused widespread death of roses in the midwestern and eastern sections of the United States. A national research team is working on the detection and best management practices for this highly damaging disease. Unfortunately, little is known about the host plant resistance to either the causal viral agent or its vector, the eriophyid mite Phyllocoptes fructiphilus. Thus far, the only confirmed resistance is among Rosa species. Of the over 600 rose cultivars observed, only 7% have not exhibited symptoms of RRD. Replicated trials are in progress to confirm resistance and/or susceptibility of ≈300 rose accessions in Tennessee and Delaware. Rose is a multispecies cultivated complex that consists of diploid, triploid, and tetraploid cultivars. The basic breeding cycle is 4 years with a 3-year commercial trial coupled with mass propagation before release. Thus, if only one breeding cycle is needed, a new cultivar could be produced in 7 years. Unfortunately, for the introgression of a new trait such as disease resistance from a related species into the commercial rose germplasm, multiple generations are required which can easily take two decades from the first cross to cultivar release. Research is ongoing to develop a rapid selection procedure for resistance to RRD with the aid of molecular markers associated with the resistance. Such an approach has the potential of reducing the breeding cycle time by 50% and increasing the efficiency of seedling and parental selection manifold, leading to commercially acceptable rose cultivars with high RRD resistance in less time and with less expense.

Tomato spotted wilt virus (TSWV) is a persistent threat to tomato (Solanum lycopersicum L) production, with diseased plants exhibiting reduced growth and direct effects on tomato fruit. TSWV incidence and associated yield losses in tomato plants were assessed with two interrow soil treatments (rye ground cover and bare ground) and four levels of biologic treatments, Make, Agricen, Make + Agricen, and a water control. Tomato plants treated with the biologic formulations in the rye interrow treatment had lower TSWV incidence than the water control, although this did not translate to improved fruit yield. No difference in fruit yield occurred between rye and bare soil interrow treatments. Because biologic treatments reduced TSWV incidence, consideration should be given to integrating them with production practices.

BackgroundGenotyping-by-Sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by PCR duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations.ResultsWe developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows runGATKandfreebayesfor SNP calling andupdog, polyRAD, andSuperMASSAfor genotype calling, andOneMapandGUSMapto build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version ofOneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. The results showed a low impact of segregation distortion in the linkage map quality, improvements in ordering markers with haplotype-based multiallelic markers, and improved maps with expected size using reliable genotype probabilities or a global error rate of 5%.ConclusionsThe pipelines results in each scenario changed according to the data set used, indicating that optimal pipelines and parameters are dataset-dependent and cannot be generalized to all GBS data sets. The Reads2Map workflow can reproduce the analysis in other GBS empirical data sets where users can select the pipeline and parameters adapted to their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.