Integration of early disease-resistance phenotyping, histological characterization, and transcriptome sequencing reveals insights into downy mildew resistance in impatiens

Abstract

Downy mildew (DM), caused by obligate parasitic oomycetes, is a destructive disease for a wide range of crops worldwide. Recent outbreaks of impatiens downy mildew (IDM) in many countries have caused huge economic losses. A system to reveal plant–pathogen interactions in the early stage of infection and quickly assess resistance/susceptibility of plants to DM is desired. In this study, we established an early and rapid system to achieve these goals using impatiens as a model. Thirty-two cultivars of Impatiens walleriana and I. hawkeri were evaluated for their responses to IDM at cotyledon, first/second pair of true leaf, and mature plant stages. All I. walleriana cultivars were highly susceptible to IDM. While all I. hawkeri cultivars were resistant to IDM starting at the first true leaf stage, many (14/16) were susceptible to IDM at the cotyledon stage. Two cultivars showed resistance even at the cotyledon stage. Histological characterization showed that the resistance mechanism of the I. hawkeri cultivars resembles that in grapevine and type II resistance in sunflower. By integrating full-length transcriptome sequencing (Iso-Seq) and RNA-Seq, we constructed the first reference transcriptome for Impatiens comprised of 48,758 sequences with an N50 length of 2060 bp. Comparative transcriptome and qRT-PCR analyses revealed strong candidate genes for IDM resistance, including three resistance genes orthologous to the sunflower gene RGC203, a potential candidate associated with DM resistance. Our approach of integrating early disease-resistance phenotyping, histological characterization, and transcriptome analysis lay a solid foundation to improve DM resistance in impatiens and may provide a model for other crops.

DataColor: unveiling biological data relationships through distinctive color mapping

“…In an era marked by an escalating influx of biological data, encompassing a spectrum of multi-omics information spanning genomics [ 27 – 31 ], transcriptomics [ 32 – 36 ], metabolomics [ 34 ], phenomics [ 37 , 38 ], and histological data [ 39 , 40 ], the imperative to visualize this data stands as a paramount challenge for bioinformatics researchers. Their objective revolves around unraveling relationships and unearthing pivotal insights from this vast trove of information.…”

QTL mapping and genetic map for the ornamental sunflower in China

“…QTL map markers should be selected according to the purpose of mapping. If the purpose of mapping is to construct a frame linkage map of chromosomes, the basic requirement is that the average spacing between markers on the constructed map should not be greater than 20cM (Peng et al, 2021). If the purpose of mapping is to locate the relevant quantitative traits, the average distance between markers should be no more than 10cM, and more related QTLs should be found as much as possible.…”

Transcriptomic and functional analyses reveal the molecular mechanisms underlying Fe-mediated tobacco resistance to potato virus Y infection

“…Overall, combining analysis of NGS and SMRT sequencing can provide high-quality, accurate, and complete isoforms in transcriptome studies, which is thereby conducive to discovering more alternative splicing (AS) isoforms, long non-coding RNAs (lncRNAs) and fusion genes. A reference transcriptome of impatiens infected with downy mildew has been constructed by full-length transcriptome sequencing and RNA sequencing (RNA-Seq), which provided a comprehensive data source to screen resistance genes ( Peng et al., 2021 ).…”