Expanded transcriptomic view of strawberry fruit ripening through meta-analysis

Advances in genomics and genome editing for improving strawberry (Fragaria ×ananassa)

The cultivated strawberry, Fragaria ×ananassa, is a recently domesticated fruit species of economic interest worldwide. As such, there is significant interest in continuous varietal improvement. Genomics-assisted improvement, including the use of DNA markers and genomic selection have facilitated significant improvements of numerous key traits during strawberry breeding. CRISPR/Cas-mediated genome editing allows targeted mutations and precision nucleotide substitutions in the target genome, revolutionizing functional genomics and crop improvement. Genome editing is beginning to gain traction in the more challenging polyploid crops, including allo-octoploid strawberry. The release of high-quality reference genomes and comprehensive subgenome-specific genotyping and gene expression profiling data in octoploid strawberry will lead to a surge in trait discovery and modification by using CRISPR/Cas. Genome editing has already been successfully applied for modification of several strawberry genes, including anthocyanin content, fruit firmness and tolerance to post-harvest disease. However, reports on many other important breeding characteristics associated with fruit quality and production are still lacking, indicating a need for streamlined genome editing approaches and tools in Fragaria ×ananassa. In this review, we present an overview of the latest advancements in knowledge and breeding efforts involving CRISPR/Cas genome editing for the enhancement of strawberry varieties. Furthermore, we explore potential applications of this technology for improving other Rosaceous plant species.

Identification of responsive genes to multiple abiotic stresses in rice (Oryza sativa): a meta-analysis of transcriptomics data

Abiotic stresses limit the quantity and quality of rice grain production, which is considered a strategic crop in many countries. In this study, a meta-analysis of different microarray data at seedling stage was performed to investigate the effects of multiple abiotic stresses (drought, salinity, cold situation, high temperature, alkali condition, iron, aluminum, and heavy metal toxicity, nitrogen, phosphorus, and potassium deficiency) on rice. Comparative analysis between multiple abiotic stress groups and their control groups indicated 561 differentially expressed genes (DEGs), among which 422 and 139 genes were up-regulated and down-regulated, respectively. Gene Ontology analysis showed that the process of responding to stresses and stimuli was significantly enriched. In addition, pathways such as metabolic process and biosynthesis of secondary metabolites were identified by KEGG pathway analysis. Weighted correlation network analysis (WGCNA) uncovered 17 distinct co-expression modules. Six modules were significantly associated with genes involved in response to abiotic stresses. Finally, to validate the results of the meta-analysis, five genes, including TIFY9 (JAZ5), RAB16B, ADF3, Os01g0124650, and Os05g0142900 selected for qRT-PCR analysis. Expression patterns of selected genes confirmed the results of the meta-analysis. The outcome of this study could help introduce candidate genes that may be beneficial for use in genetic engineering programs to produce more tolerant crops or as markers for selection.