Project description:This work represents the first epigenomic study carried out on saffron crocus. Five accessions of saffron, showing differences in tepal pigmentation, yield of saffron and flowering time, were analysed at the epigenetic level by applying a methylation-sensitive restriction enzyme-sequencing (MRE-seq) approach. Five accession-specific hypomethylomes plus a reference hypomethylome, generated by combining the sequence data from the single accessions, were obtained. Assembled sequences were annotated against existing online databases. In the absence of the Crocus genome, the rice genome was mainly used as the reference as it is the best annotated genome among monocot plants. Comparison of the hypomethylomes revealed many differentially methylated regions, confirming the high epigenetic variability present among saffron accessions, including sequences encoding for proteins that could be good candidates to explain the accessions’ alternative phenotypes. In particular, transcription factors involved in flowering process (MADS-box and TFL) and for the production of pigments (MYB) were detected. Finally, by comparing the generated sequences of the different accessions, a high number of SNPs, likely having arisen as a consequence of the prolonged vegetative propagation, were detected, demonstrating surprisingly high genetic variability. Gene ontology (GO) was performed to map and visualise sequence polymorphisms located within the GOs and to compare their distributions among different accessions. As well as suggesting the possible existence of alternative phenotypes with a genetic basis, a clear difference in polymorphic GO is present among accessions based on their geographic origin, supporting a possible signature of selection in the Indian accession with respect to the Spanish ones.
Project description:In this study, we aim to present a global transcriptome analysis of medicinal/spice plant, Crocus sativus. We generated about 206 million high-quality reads from five tissues (corm, leaf, Tepal, stamen and stigma) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples.