The transcriptomic response to a short day to long day shift in leaves of the reference legume Medicago truncatula

• Published in: PeerJ (San Francisco, CA) CA), 2019-03, Vol.7, p.e6626-e6626, Article e6626
• Main Authors: Thomson, Geoffrey, Taylor, James, Putterill, Joanna
• Format: Article
• Language: English
• Subjects: Arabidopsis thaliana; Bioinformatics; Diurnal; Flowering; Future predictions; Gene expression; Genetic research; Genomics; Grains; Isoflavones; Leaves; Legumes; Long day; Medicago truncatula; Molecular Biology; Photoperiod; Photoperiods; Plant Science; Ribonucleic acid; RNA; RNA sequencing; Seed industry; Seeds; Short day; Transcriptomics
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.6626

Photoperiodic flowering aligns plant reproduction to favourable seasons of the year to maximise successful production of seeds and grains. However understanding of this process in the temperate legumes of the Fabaceae family, which are important both agriculturally and ecologically, is incomplete. Previous work in the reference legume has shown that the gene is a potent floral activator. While is upregulated by long-day photoperiods (LD) and vernalisation, the molecular basis of this is unknown as functional homologues of key regulatory genes present in other species, notably in , have not been identified. In LD maintains a near constant diurnal pattern of expression unlike its homologue in , which has a notable peak in expression at dusk. This suggests a different manner of regulation. Furthermore, possesses other genes such as two LD induced genes which may also act in the regulation of flowering time. genes have a diurnal pattern of expression with peaks at both four and sixteen hours after dawn. This study utilises RNA-Seq to analyse the transcriptome of leaves to identify genes which may regulate or be co-expressed with these genes following a shift from short-day photoperiods to inductive long-days. Specifically this study focuses on the first four hours of the day in the young leaves, which coincides with the first diurnal peak of the genes. Following differential expression analysis at each timepoint, genes which alter their pattern of expression are distinguished from those which just alter their magnitude of expression (and those that do neither). It goes on to categorise these genes into groups with similar patterns of expression using c-means clustering and identifies a number of potential candidate photoperiod flowering time genes for future studies to consider.