bioRxivPlant BiologyPreprint
Integrative epigenomic analysis uncovers asymmetry of enhancer activity in Brassica napus
Silvia F. ZaniniiD, Kevin RockenbachiD, An Nguyen, Kübra ArslaniD, Gözde YildiziD, Rod John SnowdoniD, Agnieszka A. GolicziD
- Citations
- 2
Abstract
Non-coding regulatory regions are essential to the determination of gene expression and plant phenotypes. In this work, we investigated the cis-regulatory landscape of a winter type rapeseed, Express617, across multiple sample types. Combining chromatin accessibility, DNA methylation and gene expression, we annotated thousands of novel regulatory elements in the Brassica napus genome. Among those regions, we discovered and functionally characterized super-enhancers, observing an asymmetrical distribution of these regulatory elements favoring the Cn subgenome. Super-enhancer (SE) associated genes were found enriched in tissue identity and responses to stimuli related processes. We further establish and apply an in-silico validation pipeline for super-enhancers, integrating population-level expression analysis and machine learning (ML) models predicting gene expression levels. Almost 50% of the newly identified SE-associated genes had an observed expression higher than the expression levels predicted by the ML model. Moreover, structural variants disrupting super-enhancer elements correlate with a reduction of expression in the associated genes, both consistent with the positive effect of these regulatory regions. These results greatly expand the functional annotation of rapeseed and contribute to a better understanding of the link between regulatory elements and their target genes and processes, providing novel insights and targets for B. napus (epi)-genome editing strategies.
- organism: plant (other)
- assay: DNA methylation
- assay: bulk RNA-seq
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
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