Multiple-genotypes transcriptional analysis revealed candidates genes and nucleotide variants for improvement of quality characteristics in tea (Camellia sinensis (L.) O. Kuntze).
Genomics
; 113(1 Pt 1): 305-316, 2021 01.
Article
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| MEDLINE
| ID: mdl-33321202
Tea quality is a polygenic trait that exhibits tremendous genetic variability due to accumulation of array of secondary metabolites. To elucidate global molecular insights controlling quality attributes, metabolite profiling and transcriptome sequencing of twelve diverse tea cultivars was performed in tea shoots harvested during quality season. RP-HPLC-DAD analysis of quality parameters revealed significant difference in catechins, theanine and caffeine contents. Transcriptome sequencing resulted into 50,107 non-redundant transcripts with functional annotations of 81.6% (40,847) of the transcripts. Interestingly, 2872 differentially expressed transcripts exhibited significant enrichment in 38 pathways (FDR ≤ 0.05) including secondary metabolism, amino acid and carbon metabolism. Thirty-eight key candidates reportedly involved in biosynthesis of fatty acid derived volatiles, volatile terpenes, glycoside hydrolysis and key quality related pathways (flavonoid, caffeine and theanine-biosynthesis) were highly expressed in catechins-rich tea cultivars. Furthermore, enrichment of candidates involved in flavonoid biosynthesis, transcriptional regulation, volatile terpene and biosynthesis of fatty acid derived volatile in Protein-Protein Interactome network revealed well-coordinated regulation of quality characteristics in tea. Additionally, ascertainment of 23,649 non-synonymous SNPs and validation of candidate SNPs present in quality related genes suggests their potential utility in genome-wide mapping and marker development for expediting breeding of elite compound-rich tea cultivars.
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Bases de datos:
MEDLINE
Asunto principal:
Proteínas de Plantas
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Carácter Cuantitativo Heredable
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Polimorfismo de Nucleótido Simple
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Camellia sinensis
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Transcriptoma
Idioma:
En
Revista:
Genomics
Asunto de la revista:
GENETICA
Año:
2021
Tipo del documento:
Article