PROJECT NAME

NLRome

FINANCERS

• France's National Research Institute for Agriculture, Food and Environment (Grant IB22)
• France's National Research Institute for Agriculture, Food and Environment (Grant NLRome)
• TAKII France SAS (Grant NLRome)
• SYNGENTA France SAS (Grant NLRome)
• SAKATA Vegetable Europe SAS (Grant NLRome)
• GAUTIER SEMENCES (Grant NLRome)
• BASF (Grant NLRome)

GENERAL METADATA

Project_description - Target sequencing and assembly of NLR clusters Organism - Cucumis melo Bioproject_accession_NCBI - PRJNA1127998 Sequencing_platform - PromethION (Oxford Nanopore) Flowcell_version - R10.4.1 Assembly_program - SMARTdenovo v. 2018.2.19 / Canu v. 2.2 Sequencing date - 2024-02-01

DETAILED METADATA

• Sequencing-related metadata is available in the attached file: metadata_sequencing.txt
• Assembly-related metadata is available in the attached file: metadata_assembly.txt
• Detailed explanation about the sequencing and assembly of each accession is available in the attached file : README.txt

ABSTRACT

Understanding and characterizing the defense mechanisms of plants against pathogens represent a major challenge for sustainable agriculture and food production. It facilitates the creation of varieties with a very broad spectrum of resistance by maximizing the use of the known defense mechanisms. In this sense, the structural and functional characterization of the complete set of Nucleotide-binding-site-Leucine-rich-Repeat (NLR) disease resistance genes in a species (or NLRome) becomes especially interesting. NLR genes encode the most diverse family of plant resistance proteins. They play a central role in the so-called effector triggered immunity of plants by recognizing specific pathogen effectors. In melon (Cucumis melo L.), a highly important and widely cultivated vegetable crop belonging to the Cucurbitaceae family, the specific role of each NLR gene remains largely unknown, especially in relation to quantitative resistances. This lack of information is a consequence of a poor sequencing, assembly and annotation of these genes using short-reads sequencing, due to their complex structure and organization. NLR genes are often arranged in clusters that include a large number of repetitive elements. This fact, together with the repetitive intra-structure of NLR genes (domain leucine-rich-repeat) makes them prone to major evolutionary structural changes like duplication or transposition. For these reasons, NLR clusters commonly present a high level of presence-absence (PAV) polymorphisms. Short reads are usually ineffective to characterize them, but long reads sequencing methods may provide a very valuable information. However, they can still result expensive at wetlab, bioinformatics and data storage level when a large number of samples need to be evaluated. Nanopore Adaptive Sampling (NAS) is presumed to be a good approach here, since it can reduce the quantity of information to manage while increasing the coverage of the target regions compared to a whole genome sequencing (WGS). In addition, it is a cost and labor-effective solution compared to other complex and time-consuming targeted sequencing methods. NAS offers a promising approach for assessing genetic diversity in targeted genomic regions. We designed and validated an experiment to enrich a set of resistance genes in several melon cultivars as a proof of concept. We showed that each of the 15 regions we identified in two newly assembled melon genomes (subspecies melo) were successfully and accurately reconstructed as well as in a third cultivar from the agrestis subspecies. We obtained a fourfold enrichment, independently from the samples, but with some variations according to the enriched regions. In the agrestis cultivar, we further confirmed our assembly by PCR. By extending the use of NAS to other melon varieties, we demonstrated it as a simple and efficient approach to explore complex genomic regions. This approach finally unlocks the characterization of resistance genes for a large number of individuals, as required for breeding new cultivars responding to the agroecological transition.

SMARTdenovo, v. 2018.2.19

Canu, v. 2.2