Transcriptome analysis of strawberry (Fragaria × ananassa) fruits under osmotic stresses and identification of genes related to ascorbic acid pathway.
Vanessa GalliRafael S MessiasFrank GuzmanEllen C PerinRogério MargisCesar V RombaldiPublished in: Physiologia plantarum (2018)
Strawberry (Fragaria ananassa Duch.) is an economically important fruit with a high demand owing to its good taste and medicinal properties. However, its cultivation is affected by various biotic and abiotic stresses. Plants exhibit several intrinsic mechanisms to deal with stresses. In the case of strawberry, the mechanisms highlighting the response against these stresses remain to be elucidated, which has hampered the efforts to develop and cultivate strawberry plants with high yield and quality. Although a virtual reference genome of F. ananassa has recently been published, there is still a lack of information on the expression of genes in response to various stresses. Therefore, to provide molecular information for further studies with strawberry plants, we present the reference transcriptome dataset of F. ananassa, assembled and annotated from deep RNA-Seq data of fruits cultivated under salinity and drought stresses. We also systematically arranged a series of transcripts differentially expressed during these stresses, with an emphasis on genes related to the accumulation of ascorbic acid (AsA). Ascorbic acid is the most potent antioxidant present in these fruits and highly considered during biofortification. A comparison of the expression profile of these genes by RT-qPCR with the content of AsA in the fruits verified a tight regulation and balance between the expression of genes, from biosynthesis, degradation and recycling pathways, resulting in the reduced content of AsA in fruits under these stresses. These results provide a useful repertoire of genes for metabolic engineering, thereby improving the tolerance to stresses.
Keyphrases
- genome wide
- bioinformatics analysis
- rna seq
- genome wide identification
- poor prognosis
- dna methylation
- genome wide analysis
- healthcare
- oxidative stress
- systematic review
- microbial community
- randomized controlled trial
- climate change
- long non coding rna
- binding protein
- transcription factor
- quality improvement
- arabidopsis thaliana
- social media
- artificial intelligence
- drug induced
- meta analyses
- case control
- high throughput sequencing