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Harnessing the Physical Proximity of Genes with Gene Co-expression Analysis

In plants, most of the knowrn SM pathways are randomly distributed across the genome; however, some newly discovered pathways show clustering and co-expression phenomenon (Niitzmann et al. 2016). This discovery of gene clusters has been aided by the growing number of sequenced plant genomes with high-quality sequence assemblies and comprehensive transcriptome catalogues (Figure 6.2b(v)). Therefore, the utility of gene proximity and co-expression mining may prove informative for revealing novel PV genes that are organized in gene clusters. Indeed, at least for the terpene biosynthetic pathway genes, this seem highly feasible.

For example, TPS and CYP genes are often found co-located together far more frequently than expected by chance and volatile production may require both two types of genes. Indeed, formation of the volatile DMNT in the belowground tissues of Arabidopsis w'as recently demonstrated to involve the degradation of triterpenes by CYP genes (Sohrabi et al. 2015). The responsible gene encodes CYP705A1, a cytochrome P450 monooxygenase involved in the cleavage of arabidiol tri- terpene precursor to produce DMNT and a nonvolatile C,9-ketone product. This gene is clustered next to PENTACYCLIC TRITERPENE SYNTHASE 1 gene encoding an arabidiol synthase (ABDS) and shared coordinated regulation in the roots.

Harnessing Expression Quantitative Trait Loci (eQTL) for Candidate Prioritization

Compared to classical QTL analysis, expression-QTL (eQTL) analysis aims to discover genetic variants that contribute to the variation in gene expression (the quantitative trait) at a genome-wide scale across precise genetic backgrounds (e.g., RILs). Such approaches promise to greatly assist the linking of genes to various phenotypic traits (Kliebenstein 2009). Now with RNA-seq, genomewide sequence and expression information can be simultaneously obtained (Scheben et al. 2017), allowing eQTL analysis to be performed for a wider range of species than ever before.

In a recent study, eQTL w'as used as supporting evidence for prioritizing candidate genes associated with the production of multiple fatty acid-derived flavor volatiles in tomato fruits (Garbowicz et al. 2018). Through large-scale lipid profiling of S. pennellii introgression lines (IL) fruit pericarp and leaf tissues, and by utilizing additional genetic mapping resources (e.g., backcross inbred lines and sub-IL populations), tissue-specific lipid metabolite QTLs hotspots were first identified. A hypothesis-driven search for lipid metabolism-related genes within these hotspots was then conducted, resulting in the identification of some lipid-related genes that were supported by eQTLs exhibiting higher expression in S. pennellii-derived lines compared to w'ild-type 5. lycopersicum var. “M82.” In particular, one gene encoding class III lipase family {LIPI), with >600-fold greater expression in S. pennellii, was also positively correlated with high levels of fatty acid-derived volatiles during fruit development and ripening. The role of LIP1 was subsequently confirmed using SpLIPI-silenced and overexpression lines.

 
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