BackgroundAdventitious root (AR) formation is a critical step in vegetative propagation of most ornamental plants, such as carnation. AR formation from stem cuttings is usually divided into several stages according to physiological and metabolic markers. Auxin is often applied exogenously to promote the development of ARs on stem cuttings of difficult-to-root genotypes.ResultsBy whole transcriptome sequencing, we identified the genes involved in AR formation in carnation cuttings and in response to exogenous auxin. Their expression profiles have been analysed through RNA-Seq during a time-course experiment in the stem cutting base of two cultivars with contrasting efficiencies of AR formation. We explored the kinetics of root primordia formation in these two cultivars and in response to exogenously-applied auxin through detailed histological and physiological analyses.ConclusionsOur results provide, for the first time, a number of molecular, histological and physiological markers that characterize the different stages of AR formation in this species and that could be used to monitor adventitious rooting on a wide collection of carnation germplasm with the aim to identify the best-rooting cultivars for breeding purposes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2003-5) contains supplementary material, which is available to authorized users.
BackgroundVernalization is an obligatory requirement of extended exposure to low temperatures to induce flowering in certain plants. It is the most important factor affecting flowering time and quality in Easter lily (Lilium longiflorum). Exposing the bulbs to 4 °C gradually decreases flowering time up to 50 % compared to non-vernalized plants. We aim to understand the molecular regulation of vernalization in Easter lily, for which we characterized the global expression in lily bulb meristems after 0, 2, 5, 7 and 9 weeks of incubation at 4 °C.ResultsWe assembled de-novo a transcriptome which, after filtering, yielded 121,572 transcripts and 42,430 genes which hold 15,414 annotated genes, with up to 3,657 GO terms. This extensive annotation was mapped to the more general GO slim plant with a total of 94 terms. The response to cold exposure was summarized in 6 expression clusters, providing useful patterns for dissecting the dynamics of vernalization in lily. The functional annotation (GO and GO slim plant) was used to group transcripts in gene sets. Analysis of these gene sets and profiles revealed that most of the enriched functions among genes up-regulated by cold exposure were related to epigenetic processes and chromatin remodeling. Candidate vernalization genes in lily were selected based on their sequence similarity to known regulators of flowering in other species.ConclusionsWe present a detailed analysis of gene expression dynamics during vernalization in Lilium, covering several time points and accounting for biological variation by the use of replicates. The resulting collection of transcripts and novel isoforms provides a useful resource for studying the changes occurring during vernalization at a fine level. The selected potential candidate genes can shed light on the regulation of this process.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1675-1) contains supplementary material, which is available to authorized users.
BackgroundGenomic prediction (GP) allows breeders to select plants and animals based on their breeding potential for desirable traits, without lengthy and expensive field trials or progeny testing. We have proposed to use Dissimilarity-based Partial Least Squares (DPLS) for GP. As a case study, we use the DPLS approach to predict Bacterial wilt (BW) in tomatoes using SNPs as predictors. The DPLS approach was compared with the Genomic Best-Linear Unbiased Prediction (GBLUP) and single-SNP regression with SNP as a fixed effect to assess the performance of DPLS.ResultsEight genomic distance measures were used to quantify relationships between the tomato accessions from the SNPs. Subsequently, each of these distance measures was used to predict the BW using the DPLS prediction model. The DPLS model was found to be robust to the choice of distance measures; similar prediction performances were obtained for each distance measure. DPLS greatly outperformed the single-SNP regression approach, showing that BW is a comprehensive trait dependent on several loci. Next, the performance of the DPLS model was compared to that of GBLUP. Although GBLUP and DPLS are conceptually very different, the prediction quality (PQ) measured by DPLS models were similar to the prediction statistics obtained from GBLUP. A considerable advantage of DPLS is that the genotype-phenotype relationship can easily be visualized in a 2-D scatter plot. This so-called score-plot provides breeders an insight to select candidates for their future breeding program.ConclusionsDPLS is a highly appropriate method for GP. The model prediction performance was similar to the GBLUP and far better than the single-SNP approach. The proposed method can be used in combination with a wide range of genomic dissimilarity measures and genotype representations such as allele-count, haplotypes or allele-intensity values. Additionally, the data can be insightfully visualized by the DPLS model, allowing for selection of desirable candidates from the breeding experiments. In this study, we have assessed the DPLS performance on a single trait.
Polyploidy is common among agriculturally important crops. Popular genetic methods and their implementations cannot always be applied to polyploid genetic data. We give an overview about available tools and their limitations in terms of levels of ploidy, auto-and allo-ploidy. The main classes of tools are genotype calling, linkage mapping and haplotyping. The usability of the tools is discussed with a focus on their applicability to data sets produced by state of the art technologies. We show that many challenges remain until the toolset for polyploidy provides similar functionalities as those which are already available for diploids. Some tools have been developed over a decade ago and are now outdated. In addition, we discuss necessary steps to overcome this shortage in the future.
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