DEMENOU, B. B. | bioRxiv Science

bioRxiv2025

High-throughput SNP discovery, development and validation of a 30 K target SNP genotyping tool for cultivated flax (Linum usitatissimum) breeding and germplasm characterization

The cultivated flax (Linum usitatissimum L.) is an industrial crop widely cultivated for fiber and seeds, in broad geographical regions around the world. This crop faces many challenges (yield, quality, biotic and abiotic stresses) linked to climate change as almost all other crops. Among solution for improving or breeding new adapted cultivars, marker-assisted selection has been widely applied in plant breeding to enhance crop yield, quality, and tolerance to biotic or abiotic stresses. Recent advance of targeted genotyping-by-sequencing (GBS) offers an ultimate MAS tool to accelerate plant breeding and crop improvement. To facilitate the utility of SNP-based genotyping, we developed and validated in this study a target SNPs genotyping tool named AT-SNP-30K using Allegro targeted SNPs technology. A total of 41k SNPs were selected from 4.78 million and 3.73 million SNPs identified in two different accessions panels, respectively. Probe design for all these markers was successfully achieved for 35,791 of these markers, representing a 86% conversion success rate. The set of markers was then validated by genotyping a diversity panel comprising 384 individuals, including 376 accessions and eight replicates of the fiber flax Ideo cultivar. The validated genotyping tool includes 35,791 SNPs, covering the fifteen chromosomes with 24,951 high-quality SNPs (MAF> 5%, average low rate of missing data) and 27,247 SNPs having a MAF greater than 1%; demonstrating high polymorphism and excellent genotyping accuracy. The repeatability of genotyping in the validation experiment, reached 99.00% of SNPs for the eight Ideo replicate controls. The AT-SNP-30K genotyping tool is a robust resource for genetic studies, germplasm characterisation and cultivated flax marker-assisted selection studies. It can be used to enhance the breeding of new flax cultivars adapted to the context of climate change.

genomics↗

bioRxiv2025

Optimizing core collections for genetic studies: a worldwide flax germplasm case study

Core collections provide a strategic approach to reducing population size while retaining genetic diversity and allele frequencies, serving as key resources for genetic research. Although various sampling and selection strategies have been proposed, most of them focused on either diversity or representativeness, rarely both, and none fully integrated these with QTL detection optimization. The first part of our study focuses on a genetic diversity analysis of a flax germplasm (Linum usitatissimum L.), a prerequisite for the development of core collections. This germplasm, maintained by the Arvalis Institute, is a worldwide flax collection comprising 1,593 accessions originating from 42 countries, encompassing all major flax-growing regions. It includes both spring- and winter-type lines, as well as oilseed and fiber types. The results revealed a pronounced genetic structure within the germplasm, strongly influenced by cultivation purposes (fiber vs. oilseed flax), growth cycle (winter vs. spring), and geographic origin. A K-means clustering procedure identified six clusters as the optimal structuration, which aligns with our knowledge of this germplasm. Overall genetic diversity was moderate (H = 0.22), with oilseed flax clusters displaying greater diversity than fiber flax, likely due to the broader selection history and wider geographic distribution, findings consistent with previous studies. In a second step we evaluated twenty distinct strategies for core-collection development. Some approaches were originally developed for core-collection construction while others were developed for optimizing genomic-selection calibration panels. QTL detection performance was assessed via extensive simulations of QTLs distributed across the genome. We observed a fundamental trade-off between maximizing diversity and ensuring representativeness in core collection design. Diversity-oriented approaches may overemphasize rare or outlier genotypes, compromising representativeness, while representativeness-focused strategies leaded to overlooking rare alleles, thus limiting diversity. In our results we have found that particular combinations of selection criteria achieved a favorable balance between genetic diversity and representativeness, while concurrently maintaining a robust capacity to capture QTL signals across the genome. We demonstrated that using the Shannon index combined with the allelic coverage led to optimal core-collection design adapted for GWAS applications in a structured population. These results provide knowledge for the development of optimized core collections tailored to GWAS applications.

genetics↗