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The legume family (Fabaceae) is the third-largest angiosperm family and is considered one of the most important crop families. Biotic stress constrains legume yield, and resistance breeding is currently considered the most sustainable management method to deal with pathogen pressure in the field. Many legumes share the same pathogens, but whether they share the same genetic basis of resistance is currently unknown. Thus our goal is to identify, classify and compare resistance (R) genes in the Fabaceae family. As a first step towards uncovering the repertoire of Fabaceae resistance genes, we undertook a phylogenomic analysis of nucleotide-binding leucine-rich repeat proteins (NLRs) in 23 legume species. First, NLRtracker was used to identify the NLRs in each genome, then these genes were aligned using v1.2.2 of the Clustal Omega Alignment tool, and the FastTree algorithm was used to generate approximately maximum-likelihood NLR phylogenetic trees. The trees were visualized using iTOL and the data was analysed using R. These analyses revealed large variation in overall NLR abundance as well as in the frequency of the different NLR classes. The distribution of the NLR classes did not always match the species' phylogeny, potentially hinting that other forces, such as artificial selection, can be at play. For instance, pea (Pisum sativum) and grass pea (Lathyrus sativus) have significantly different NLR repertoires, despite being closely related. The Fabaceae NLR repertoire will be an important tool for comparative resistance mapping studies and for R gene enriched Genome-Wide Association Studies. The outcome of these analyses will be used to accomplish the long-term goal of my project: to develop tools to assist legume breeding programs for durable resistance.
This poster was developed for and presented at the 12th ITQB NOVA Ph.D. Students' Meeting that occurred in 2022 from the 20th to the 22nd of April.
Leguminosae, Phylogenomics, Fabaceae, Papilionaceae, NLR
Leguminosae, Phylogenomics, Fabaceae, Papilionaceae, NLR
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