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Strickert, M.

Publications and source records attributed to Strickert, M..

2 recordsLinked to original sources

GBS and a newly developed mRNA-GBS approach to link population genetic and transcriptome analyses reveal pattern differences between sites and treatments in red clover (Trifolium pratense L.)

The important worldwide forage crop red clover (Trifolium pratense L.) is widely cultivated as cattle feed and for soil improvement. Wild populations and landraces have great natural diversity that could be used to improve cultivated red clover. However, to date, there is still insufficient knowledge about the natural genetic and phenotypic diversity of the species. Here, we developed a low-cost transcriptome analysis (mRNA-GBS) with reduced complexity and compared the results with population genetic (GBS) and previously published mRNA-Seq data, to assess whether analysis of intraspecific variation within and between populations and transcriptome responses is possible simultaneously. The mRNA-GBS approach was successful. SNP analyses from the mRNA-GBS approach revealed comparable patterns to the GBS results, but it was not possible to link transcriptome analyses with reduced complexity and sequencing depth to previously published greenhouse and field expression studies. The use of short sequences upstream of the poly(A) tail of mRNA to reduce complexity are promising approaches that combine population genetics and expression profiling to analyze many individuals with trait differences simultaneously and cost-effectively, even in non-model species. Our mRNA-GBS approach revealed too many additional short mRNA sequences, hampering sequence alignment depth and SNP recovery. Optimizations are being discussed. Nevertheless, our study design across different regions in Germany was also challenging as the use of differential expression analyses with reduced complexity, in which mRNA is fragmented at specific sites rather than randomly, is most likely counteracted under natural conditions by highly complex plant reactions at low sequencing depth.

plant biology↗

'Macrobot' - an automated segmentation-based system for powdery mildew disease quantification

Plant diseases, as one of the perpetual problems in agriculture, is increasingly difficult to manage due to intensifying of the field production, global trafficking, reduction of genetic variability of crops, climatic changes-driven expansion of pests, redraw and loss of effectiveness of pesticides and rapid breakdown of the disease resistance in the field. The substantial progress in genomics of both plants and pathogens, achieved in the last decades has the potential to counteract this negative trend, however, only when the genomic data is supported by relevant phenotypic data that allows linking the genomic information to specific traits. In this respect, phenotyping is and will remain an essential element of any comprehensive functional genomics study. We have developed a set of methods and equipment and combined them into a "Macrophenomics pipeline". The pipeline has been optimized for the quantification of powdery mildew infection symptoms on wheat and barley but it can be adapted to other diseases and host plants. The Macrophenomics pipeline scores the visible disease symptoms, typically 5-7 days after inoculation (dai) in a highly automated manner. The system can precisely and reproducibly quantify the percentage of the infected leaf area with a throughput of the image acquisition module of up to 10 000 individual samples per day, making it appropriate for phenotyping of large germplasms collections and crossing populations.

plant biology↗