The transcriptomic response to a short day to long day shift in leaves of the reference legume Medicago truncatula
- Published
- Accepted
- Subject Areas
- Bioinformatics, Genomics, Molecular Biology, Plant Science
- Keywords
- Medicago truncatula, Transcriptomics, Photoperiod, FT, Long day, Short day, Flowering time, Floral induction, Legume, RNA-Seq
- Copyright
- © 2018 Thomson et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. The transcriptomic response to a short day to long day shift in leaves of the reference legume Medicago truncatula. PeerJ Preprints 6:e27366v1 https://doi.org/10.7287/peerj.preprints.27366v1
Abstract
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 Medicago truncatula has shown that the FT-like gene MtFTa1 is a potent floral activator. While MtFTa1 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 CONSTANS in A. thaliana, have not been identified. In LD MtFTa1 maintains a near constant diurnal pattern of expression unlike its homologue FT in A. thaliana, which has a notable peak in expression at dusk. This suggests a different manner of regulation. Furthermore, M. truncatula possesses other FT-like genes such as two LD induced MtFTb genes which may also act in the regulation of flowering time. MtFTb 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 M. truncatula leaves to identify genes which may regulate or be co-expressed with these FT-like 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 FTb 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.
Author Comment
This is a submission to PeerJ for review.
Supplemental Information
README
This is a key to the supplementary tables 1-9.
TPM
Gene abundances in Transcripts per Million for each gene by condition, timepoint and replicate
RT-qPCR Primers
Primers used for RT-qPCR in this study.
Individual timepoint analysis
Contrasts LD expression against SD expression results at individual timepoints using using Wald significance tests.
DE pattern genes
Results of the likelihood ratio test testing for genes with significant interaction terms indicative of differential patterns of expression.
DE pattern contrasts
Contrasts LD expression against SD expression for genes with differential patterns of expression at individual timepoints.
DE pattern clusters
Cluster assignments of genes of the differential patterns of expression class
DE magnitude genes
Results of the Wald significance test testing for the significance of the condition in explaining the magnitude of gene expression.
DE magnitude contrasts
Contrasts LD expression against SD expression for genes with differential magnitudes but not patterns of expression at individual timepoints.
DE magnitude clusters
Cluster assignments of genes with differential magnitudes but not patterns of expression at individual timepoints