Molecular Characterization of the miR156/MsSPL Model in Regulating the Compound Leaf Development and Abiotic Stress Response in Alfalfa.
Xueyang MinKai LuoWenxian LiuKeyou ZhouJunyi LiZhenwu WeiPublished in: Genes (2022)
Plant leaf patterns and shapes are spectacularly diverse. Changing the complexity of leaflet numbers is a valuable approach to increase its nutrition and photosynthesis. Alfalfa ( Medicago sativa ) is the most important forage legume species and has diversified compound leaf patterns, which makes it a model species for studying compound leaf development. However, transcriptomic information from alfalfa remains limited. In this study, RNA-Seq technology was used to identify 3746 differentially expressed genes (DEGs) between multifoliate and trifoliate alfalfa. Through an analysis of annotation information and expression data, SPL , one of the key regulators in modifiable plant development and abiotic stress response, was further analyzed. Here, thirty MsSPL genes were obtained from the alfalfa genome, of which 16 had the putative miR156 binding site. A tissue expression pattern analysis showed that the miR156-targeted MsSPLs were divided into two classes, namely, either tissue-specific or widely expressed in all tissues. All miR156-targeted SPL s strongly showed diversification and positive roles under drought and salt conditions. Importantly, miR156/MsSPL08 was significantly suppressed in multifoliate alfalfa. Furthermore, in the paralogous mutant of MsSPL08 isolated from Medicago truncatula, the phenotypes of mutant plants reveal that miR156/MsSPL08 is involved not only involved the branches but also especially regulates the number of leaflets. The legume is a typical compound leaf plant; the ratio of the leaflet often affects the quality of the forage. This study sheds light on new functions of SPL genes that regulate leaflet number development.
Keyphrases
- cell proliferation
- long non coding rna
- rna seq
- long noncoding rna
- poor prognosis
- single cell
- genome wide
- mitral valve
- heart failure
- gene expression
- healthcare
- electronic health record
- health information
- dna methylation
- cancer therapy
- quality improvement
- artificial intelligence
- drug delivery
- deep learning
- transcription factor
- atrial fibrillation
- bioinformatics analysis
- wild type
- data analysis