(External) Using RNA integrity and gene expression as a proxy for seed viability
Advisor: Leonardo Galindo Gonzalez, Canadian Food Inspection Agency
Suggested co-advisors: Edeline Gagnon, Graham Taylor
The Molecular Identification Research Lab (MIRL) at the Canadian Food Inspection Agency in Ottawa uses molecular biology, omics and bioinformatics for identification of plants of regulatory concern including invasive and weedy species.
Detection of weed seeds in exports and imports is key to maintain ongoing trade with major international partners and to avoid the introduction of alien invasive and detrimental species into the natural and agricultural settings. In Canada, detection of weed seeds is performed by seed analysts but with increasing trade and needs for certification, molecular techniques constitute a complementary tool for efficient identification of plant pests. Additionally, morphological identification of these weed seeds is not always possible and therefore molecular fingerprints constitute an alternative for accurate identification of these species. While morphological and molecular identification through DNA barcoding can classify species of concern, a major question is whether these identified samples are viable noxious seeds (since non-viable contaminants do not have a negative impact upon introduction). Usually, germination or specific viability tests (e.g., chemical detection using Tetrazolium) must be performed to confirm if seeds are alive. However, traditional viability tests take time, and depend on pre-identification of the target noxious seed. In cases where there is a mixed sample containing the weed seed it would be ideal to develop techniques that can rapidly identify the different species in the mix and validate their viability concomitantly. While DNA barcoding or metabarcoding can characterize the species from individual or mixed samples respectively, DNA can remain intact in non-viable cells and has a slow rate of degradation. Contrary to this, RNA is present in metabolically active cells and therefore indicative of an organism being viable.
Therefore, we are performing preliminary experiments to assess RNA integrity and uncover constitutively expressed genes that can be used as markers of viability. We isolated RNA and used Illumina sequencing to obtain transcripts of seeds under dormancy vs seeds undergoing imbibition in two Amaranthus species of regulatory concern (A. palmeri and A. tuberculatus). Analysis of these data will allow us to find active constitutive genes during dormancy (the most usual stage at which seed contaminants can be found), but also confirm if these genes continue to be active once seeds start the process of water imbibition. Uncovering this constitutively active genes may open a door to use them as markers of viability in these and other species.
On this project the student will use the RNAseq Illumina reads to perform whole transcriptome gene expression analysis using a bioinformatics analysis pipeline (e.g., Hisat-StringTie-Ballgown or HTseq-DEseq2). Highly expressed constitutive genes will also be assessed for variability between species to see if they can be used as markers of viability as well as for species-specific barcodes. Most of the gene expression analysis tools will require knowledge in using command line and/or R software. Genes with high constitutive expression found during this project can be validated in the future using technologies like Nanostrings or qPCR, and further tested in other species of the genus, different developmental seed stages, and other noxious species. This will allow to see if they can be used across a large range of species.
This project is set for 4 months (summer 2025) and does not need the student to be on-site since is based solely on the used of computational tools for data analysis. Regular meetings will be set with the student and the University of Guelph co-supervisors to overview progress and support the student. Advance of the project will be evaluated by the end of June to see if an extension is necessary, pending instructor approval.
Knowledge/Skills
Analysis of next-generation sequencing (NGS) data (transcritomics), experience using command line/unix