Genomics of predictive radiation mutagenesis in oilseed rape: modifying seed oil composition

生物 油菜籽 基因组 突变 基因组学 计算生物学 分子育种 遗传学 基因 生物技术 脂肪酸去饱和酶 拷贝数变化 多不饱和脂肪酸 脂肪酸 突变体 植物 生物化学
作者
Lenka Havlíčková,Zhesi He,Madeleine Berger,Lihong Wang,Greta Sandmann,Yen Peng Chew,Guilherme V. Yoshikawa,Guangyuan Lu,Qiong Hu,S. S. Banga,Frédéric Beaudoin,Ian Bancroft
出处
期刊:Plant Biotechnology Journal [Wiley]
标识
DOI:10.1111/pbi.14220
摘要

Rapeseed is a crop of global importance but there is a need to broaden the genetic diversity available to address breeding objectives. Radiation mutagenesis, supported by genomics, has the potential to supersede genome editing for both gene knockout and copy number increase, but detailed knowledge of the molecular outcomes of radiation treatment is lacking. To address this, we produced a genome re-sequenced panel of 1133 M2 generation rapeseed plants and analysed large-scale deletions, single nucleotide variants and small insertion-deletion variants affecting gene open reading frames. We show that high radiation doses (2000 Gy) are tolerated, gamma radiation and fast neutron radiation have similar impacts and that segments deleted from the genomes of some plants are inherited as additional copies by their siblings, enabling gene dosage decrease. Of relevance for species with larger genomes, we showed that these large-scale impacts can also be detected using transcriptome re-sequencing. To test the utility of the approach for predictive alteration of oil fatty acid composition, we produced lines with both decreased and increased copy numbers of Bna.FAE1 and confirmed the anticipated impacts on erucic acid content. We detected and tested a 21-base deletion expected to abolish function of Bna.FAD2.A5, for which we confirmed the predicted reduction in seed oil polyunsaturated fatty acid content. Our improved understanding of the molecular effects of radiation mutagenesis will underpin genomics-led approaches to more efficient introduction of novel genetic variation into the breeding of this crop and provides an exemplar for the predictive improvement of other crops.
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