Identification of flowering-time genes in mast flowering plants using de novo transcriptomic analysis

Abstract

Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. In this study, a high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for Celmisia and Chionochloa. The two datasets generated were blasted against the publicly available databases, TAIR, Swiss-Prot, non-redundant protein (nr), KEGG and COG for unigene annotations. On average, 56% of the unigenes were finally annotated with gene descriptions mapped to known protein sequences for both the species. Gene ontology analysis was then performed on the assembled reference transcriptomes, categorising the transcripts on the basis of putative biological processes, molecular function, and cellular localisation. A total of 543 transcripts from Celmisia and 470 transcripts from Chionochloa were also mapped to unique flowering-time proteins identified in Arabidopsis, suggesting the conservation of the flowering network in these wild alpine plants, growing in natural field conditions. These genes can further be analysed to understand the molecular regulation of the reproductive phase transition in the masting plants.