Dario Copetti

Background: Nested association mapping (NAM) populations are a powerful tool for investigating the genetic control of agronomically important traits and have been successfully used in self-pollinating crop species. Here, we present the first NAM population established in the outcrossing forage grass species Italian ryegrass ( Lolium multiflorum Lam.), to dissect the genetic control of seed shattering. High and stable seed yields are essential for the commercial success of new cultivars. Seed shattering strongly reduces seed yield in Italian ryegrass, but has so far not been targeted in Italian ryegrass breeding programs. Results: The NAM population was based on one common and 23 diverse founder plants and consisted of 708 F ₂ individuals. Reduced-representation sequencing (ddRAD) of the 708 F ₂ individuals, combined with whole genome sequencing data of the 24 founder plants, yielded a total of 3,199,253 SNPs that were used for population structure analysis, parentship analysis and genome-wide association studies. Phenotypic data for seed shattering and seed yield-related traits, collected in three field trials, showed high phenotypic variance within the NAM population. A total of seven quantitative trait loci (QTL) were identified for seed shattering, seed yield, spike length, flag leaf length and flowering time. Within these QTL regions, one putative candidate gene for seed shattering and three putative candidate genes for flowering time were identified. For seed shattering, the significantly associated SNP within the gene chr7.26897 , known to be involved in ripening-related pathways, explained 10.03% of the phenotypic variance. Conclusions: The identified loci provide valuable resources for breeding. The QTL regions containing putative candidate genes identified within these loci offer promising targets for functional validation and demonstrate the effectiveness of NAM populations for elucidating the genetic architecture of complex traits in outcrossing forage grasses.

One hundred diatom species have been selected for genome and transcriptome sequencing. The 100 Diatom Genomes Project aims to provide a scalable framework for understanding diatom biodiversity, ecology and evolution, and for investigating their use in biotechnology.

Key message: Field phenotyping of a recently established NAM population for stem rust resistance, combined with high-density genotyping, enabled the identification of novel sources of stem rust resistance in Italian ryegrass. Stem rust, caused by Puccinia graminis ssp. graminicola , is a major disease affecting the outcrossing species Italian ryegrass ( Lolium multiflorum Lam.) and leading to substantial reductions in seed yield. Until now, knowledge on the genetic control of stem rust resistance in Italian ryegrass has been limited to a few quantitative trait loci identified in biparental mapping populations. To discover novel resistance sources for use in breeding programs, appropriate plant populations, reliable phenotyping methods and advanced genomic tools are essential. In this study, we utilized a previously established F ₂ nested association mapping (NAM) population comprising 708 individuals derived from 24 founder plants, exhibiting high variation in stem rust resistance. Phenotypic evaluation was conducted under natural inoculation in three location-by-year combinations. By integrating reduced-representation sequencing of the NAM population with whole genome sequencing of the founder plants, we identified 3,199,253 SNP markers for association mapping. The high SNP marker density, together with the strong detection power of the NAM population, enabled the identification of four novel candidate genes. Two of these genes, located on chromosomes 6 and 7, encode receptor-like serine/threonine kinases that are known to play a role in stem rust resistance in other crops. Within the serine/threonine kinase gene Chr7.32208 , two superior haplotypes were identified that can be directly implemented as selection criteria in breeding programs. The novel stem rust resistance candidate genes reported here provide promising targets for functional validation and the improvement of stem rust resistance in Italian ryegrass breeding.

Polyploidization is a key evolutionary force in plants, but the reasons behind its prevalence remain unclear. While the potential ecological benefits of established polyploids are well studied, little is known about the short-term genomic and epigenetic responses immediately after polyploidization, which are crucial for successful speciation. In this study, we assemble the genomes of the two progenitors of Arabidopsis kamchatica ( A. halleri and A. lyrata ) and examine the epigenome of synthetic and natural tetraploids of A. kamchatica to investigate the combined effect of allopolyploidization and environment on DNA methylation changes. We find the most significant methylation changes at allopolyploidization, followed by smaller changes in subsequent generations. Offspring grown under different conditions show divergent patterns, suggesting environmental effects, while their methylation patterns converge toward those of natural tetraploids over generations. Our findings highlight two key epigenetic changes post-polyploidization: convergence toward established polyploids and divergence driven by environmental factors.

Stem rust, caused by Puccinia graminis ssp. graminicola, is a major disease affecting the outcrossing species Italian ryegrass (Lolium multiflorum Lam.), leading to substantial reductions in seed yield. Until now, knowledge on the genetic control of stem rust resistance in Italian ryegrass has been limited to a few quantitative trait loci identified in bi-parental mapping populations. To discover novel resistance sources for use in breeding programs, appropriate plant populations, reliable phenotyping methods and advanced genomic tools are essential. In this study, we utilized a previously established F₂ nested association mapping (NAM) population comprising 708 individuals derived from 24 founder plants exhibiting high variation in stem rust resistance. Phenotypic evaluation was conducted under natural inoculation in three location-by-year combinations. By integrating reduced-representation sequencing of the NAM population with whole-genome sequencing of the founder plants, we identified 3,199,253 SNP markers for association mapping. The high SNP marker density, together with the strong detection power of the NAM population, enabled the identification of four novel candidate genes. Two of these genes, located on chromosomes 6 and 7, encode receptor-like serine/threonine kinases that are known to play a role in stem rust resistance in other crops. Within the serine/threonine kinase gene Chr7.32208, two superior haplotypes were identified that can be directly implemented as selection criteria in breeding programs. The novel stem rust resistance candidate genes reported here provide promising targets for functional validation and the improvement of stem rust resistance in Italian ryegrass breeding.

Current methods to generate haplotype-resolved assemblies for highly heterozygous genomes suffer from reference bias when relying on reference-based phasing or may generate imbalanced haplomes when relying on graph-based phasing. Here, we report PhaseGrass, an assembly, phasing and scaffolding workflow that is compatible with accurate or error-prone long reads, generating haplotype-resolved assemblies for highly heterozygous genomes. Requiring no parental data, PhaseGrass combines reference-based phasing with haplotype-specific k-mers to partition long reads or unitigs to corresponding haplotypes, thereby avoiding reference bias and uneven haplotype partitioning. Using PhaseGrass, we generated chromosome-level, haplotype-resolved assemblies for the highly heterozygous, allogamous grass species Lolium perenne L. and L. multiflorum Lam. We find that PhaseGrass can bin 20% more reads to haplotypes than WhatsHap and generated balanced haplomes compared to Hifiasm, which produced largely imbalanced haplomes for L. multiflorum due to abundant structural variations between haplotypes. PhaseGrass will facilitate routine generation of haplotype-resolved pangenomes for species with highly heterozygous genomes.

The rice genome underpins fundamental research and breeding, but the Nipponbare ( japonica ) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent the japonica , indica , aus , and aromatic varietal groups. The RPRP has been consistently annotated and supported by extensive experimental data, and here, we report the computational assignment, characterization, and dissemination of stably identified pangenes, collectively called the PanOryza data set. We identify 25,178 core pangenes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains, and AlphaFold structures, whereas cultivar-specific genes are enriched for domains under selective breeding pressure, such as for disease resistance. We identify more than 5000 genes absent in the IRGSP rice reference genome and present in at least two other Oryza cultivars. We demonstrate the utility of this resource through various examples of pangenes and their protein domains. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware “reference guide” across rice genomes, advancing both basic and applied research.

Nested association mapping (NAM) populations are a powerful tool for investigating the genetic control of agronomically important traits and have been successfully used in many inbreeding crops. Here, we present the first NAM population established in an outcrossing forage grass species, Italian ryegrass ( Lolium multiflorum Lam.), to dissect the genetic control of seed shattering. The NAM population was based on 23 diverse and one common founder plants and consisted of 708 F ₂ individuals. Reduced-representation sequencing (ddRAD) of the 708 F ₂ individuals, combined with whole genome sequencing data of the 24 founder plants, yielded a total of 3,199,253 SNPs that were used for population structure analysis, parentship analysis and genome-wide association studies. Phenotypic data for seed shattering and seed yield-related traits, collected in three year x location environments, showed high phenotypic variance within the NAM population. A total of seven QTL were identified for seed shattering, seed yield, spike length, flag leaf length and flowering time. Within these QTL regions, one candidate gene for seed shattering and three candidate genes for flowering time were identified. For seed shattering, the significant SNP association within the gene chr7.26897, known to be in involved in ripening-related pathways, explained 10.03% of the phenotypic variance. These candidate genes identified provide valuable targets for functional validation and demonstrate the effectiveness of NAM populations for elucidating the genetic architecture of complex traits in outcrossing forage grasses.

The rice genome underpins fundamental research and breeding, but the Nipponbare (japonica) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent japonica , indica , aus , and aromatic varietal groups. The RPRP has been consistently annotated, supported by extensive experimental data and here we report the computational assignment, characterization and dissemination of stably identified pan-genes. We identified 25,178 core pan-genes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains and AlphaFold structures, while cultivar-specific genes were enriched for domains under selective breeding pressure, such as for disease resistance. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware “reference guide” across rice genomes, advancing both basic and applied research.