Identification of novel flowering genes using RNA-Seq pipeline employing combinatorial approach in Arabidopsis thaliana time-series apical shoot meristem data. (2nd February 2020)

• Record Type: Journal Article
• Authors: Deshpande, Sumukh; James, Anne; Franklin, Chris; Leach, Lindsey; Yang, Jianhua
• Is Part Of: International journal of bioinformatics research and applications. Volume 16:Number 1(2020)
• Page Start: 25
• Page End: 58
• Publication Date: 2020-02-02
• Subjects: apical shoot -- flowering -- pipeline -- Cuffdiff -- step analysis -- differential expression -- enrichment -- Arabidopsis thaliana; Bioinformatics -- Periodicals; 570.285
• Languages: English
• ISSNs: 1744-5485

Abstract

Floral transition is a crucial event in the reproductive cycle of a flowering plant during which many genes are expressed that govern the transition phase. Identification of additional genes connected to flowering genes is vital since they may regulate flowering genes and vice versa. Through our study, expression values of additional genes have been found similar to flowering genes FLC and LFY in the transition phase. The presented approach plays a crucial role in this discovery. An RNA-Seq computational pipeline was developed for identification of novel genes involved in floral transition from A. thaliana apical shoot meristem time-series data. By intersecting differentially expressed genes (DEGs) from Cuffdiff, DEseq and edgeR, we identified 30 genes as principle regulators in the transition phase. Additionally, expression profiles of highly connected genes from network analysis revealed 76 genes with non-functional association and high correlation to FLC and LFY suggesting their potential role in floral regulation.