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  • Title: Deep sequencing-based characterization of transcriptome of Pyrus ussuriensis in response to cold stress.
    Author: Yang T, Huang XS.
    Journal: Gene; 2018 Jun 30; 661():109-118. PubMed ID: 29580898.
    Abstract:
    Pyrus ussuriensis is extremely cold hardy when fully acclimated, but knowledge relevant to the molecular mechanisms underlying this economically valuable trait is still limited so far. In this study, global transcriptome profiles of Pyrus ussuriensis under cold conditions (4 °C) over a time course were generated by high-throughput sequencing. In total, >57,121,199 high quality clean reads were obtained with approximately 11.0 M raw data for each library. Among them, the values of 66.84%-72.03% of clean reads in the digital transcript abundance measurement could be well mapped to the pear genome database, resulting in the identification of 8544 differentially expressed genes (DEGs) having 43 Gene Ontology (GO) terms and 17 clusters of orthologous groups (COG) involved in 385 Kyoto Encyclopedia of Genes and Genomes (KEGG) defined pathways. These comprised 3124 (1033 up-regulated, 2091 down-regulated), 1243 (729 up-regulated, 514 down-regulated), and 750 (458 up-regulated, 292 down-regulated) genes from the cold-treated samples at 5, 12 and 24 h, respectively. The accuracy of the RNA-Seq derived transcript expression data was validated by analyzing the expression patterns of 16 DGEs by quantitative real-time PCR. Plant-pathogen interaction, plant hormone signal transduction, Photosynthesis, signal transduction, innate immune response and response to biotic stimulus were the most significantly enriched GO categories among in the DEGs. A total of 335 transcription factors were shown to be cold responsive. In addition, a number of genes involved in the catabolism and signaling of hormones were significantly affected by the cold stress. The RNA-Seq and digital expression profiling provides valuable insights into the understanding the molecular events related to cold responses in Pyrus ussuriensis and dataset may help guide future identification and functional analysis of potential genes that are important for enhancing cold hardiness.
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