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Int J Mol Sci ; 21(3)2020 Feb 06.
Article in English | MEDLINE | ID: mdl-32041193

ABSTRACT

RNA-Seq technology was used to analyze the transcriptome of two rice hybrids, Ajay (based on wild-abortive (WA)-cytoplasm) and Rajalaxmi (based on Kalinga-cytoplasm), and their respective parents at the panicle initiation (PI) and grain filling (GF) stages. Around 293 and 302 million high quality paired-end reads of Ajay and Rajalaxmi, respectively, were generated and aligned against the Nipponbare reference genome. Transcriptome profiling of Ajay revealed 2814 and 4819 differentially expressed genes (DEGs) at the PI and GF stages, respectively, as compared to its parents. In the case of Rajalaxmi, 660 and 5264 DEGs were identified at PI and GF stages, respectively. Functionally relevant DEGs were selected for validation through qRT-PCR, which were found to be co-related with the expression patterns to RNA-seq. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated significant DEGs enriched for energy metabolism pathways, such as photosynthesis, oxidative phosphorylation, and carbon fixation, at the PI stage, while carbohydrate metabolism-related pathways, such as glycolysis and starch and sucrose metabolism, were significantly involved at the GF stage. Many genes involved in energy metabolism exhibited upregulation at the PI stage, whereas the genes involved in carbohydrate biosynthesis had higher expression at the GF stage. The majority of the DEGs were successfully mapped to know yield related rice quantitative trait loci (QTLs). A set of important transcription factors (TFs) was found to be encoded by the identified DEGs. Our results indicated that a complex interplay of several genes in different pathways contributes to higher yield and vigor in rice hybrids.


Subject(s)
Gene Expression Profiling/methods , Oryza/growth & development , Plant Proteins/genetics , Edible Grain/genetics , Edible Grain/growth & development , Energy Metabolism , Gene Expression Regulation, Plant , Oryza/genetics , Quantitative Trait Loci , Sequence Analysis, RNA
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