Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits

Specificity of RNA Folding and Its Association with Evolutionarily Adaptive mRNA Secondary Structures

The secondary structure is a fundamental feature of both noncoding and messenger RNAs. However, our understanding of the secondary structure of mRNA, especially that of the coding regions, remains elusive, likely due to translation and the lack of RNA-binding proteins that sustain the consensus structure, such as those that bind to noncoding RNA. Indeed, mRNA has recently been found to adopt diverse alternative structures, the overall functional significance of which remains untested. We hereby approached this problem by estimating the folding specificity, i.e., the probability that a fragment of RNA folds back to the same partner once refolded. We showed that the folding specificity of mRNA is lower than that of noncoding RNA and exhibits moderate evolutionary conservation. Notably, we found that specific rather than alternative folding is likely evolutionarily adaptive since specific folding is frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the ability to modulate ribosome movement as one potential functional advantage provided by specific folding. Our findings revealed a novel facet of the RNA structurome with important functional and evolutionary implications and indicated a potential method for distinguishing the mRNA secondary structures maintained by natural selection from molecular noise.

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections

Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A mixed genotyping strategy was implemented, by combining proprietary genotyping-by-sequencing data with public whole-genome-sequencing data, to generate an integrative 11,834-common single nucleotide polymorphism matrix including the three breeding collections. In general, the GD estimates obtained were moderate. An analysis of molecular variance provided evidence of population structure between breeding collections. However, the optimal number of subpopulations, studied via discriminant analysis of principal components (K = 12), the bayesian STRUCTURE algorithm (K = 6) and distance-based methods (K = 9) remains unclear, since no single unifying characteristic is apparent for any of the inferred groups. Different overall patterns of linkage disequilibrium (LD) were observed across chromosomes, with Chr10, Chr17, Chr5, and Chr2 showing the highest LD. This work represents the largest and most comprehensive inter-breeding collection analysis of genomic diversity for cultivated sunflower conducted to date.

Sunflower resistance to multiple downy mildew pathotypes revealed by recognition of conserved effectors of the oomycete Plasmopara halstedii

Over the last 40 years, new sunflower downy mildew isolates (Plasmopara halstedii) have overcome major gene resistances in sunflower, requiring the identification of additional and possibly more durable broad-spectrum resistances. Here, 354 RXLR effectors defined in silico from our new genomic data were classified in a network of 40 connected components sharing conserved protein domains. Among 205 RXLR effector genes encoding conserved proteins in 17 P. halstedii pathotypes of varying virulence, we selected 30 effectors that were expressed during plant infection as potentially essential genes to target broad-spectrum resistance in sunflower. The transient expression of the 30 core effectors in sunflower and in Nicotiana benthamiana leaves revealed a wide diversity of targeted subcellular compartments, including organelles not so far shown to be targeted by oomycete effectors such as chloroplasts and processing bodies. More than half of the 30 core effectors were able to suppress pattern-triggered immunity in N. benthamiana, and five of these induced hypersensitive responses (HR) in sunflower broad-spectrum resistant lines. HR triggered by PhRXLRC01 co-segregated with Pl22 resistance in F3 populations and both traits localized in 1.7 Mb on chromosome 13 of the sunflower genome. Pl22 resistance was physically mapped on the sunflower genome recently sequenced, unlike all the other downy mildew resistances published so far. PhRXLRC01 and Pl22 are proposed as an avirulence/resistance gene couple not previously described in sunflower. Core effector recognition is a successful strategy to accelerate broad-spectrum resistance gene identification in complex crop genomes such as sunflower.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits.

Ten Broad Spectrum Resistances to Downy Mildew Physically Mapped on the Sunflower Genome

Resistance to downy mildew (Plasmopara halstedii) in sunflower (Helianthus annuus L.) is conferred by major resistance genes, denoted Pl. Twenty-two Pl genes have been identified and genetically mapped so far. However, over the past 50 years, wide-scale presence of only a few of them in sunflower crops led to the appearance of new, more virulent pathotypes (races) so it is important for sunflower varieties to carry as wide a range of resistance genes as possible. We analyzed phenotypically 12 novel resistant sources discovered in breeding pools derived from two wild Helianthus species and in eight wild H. annuus ecotypes. All were effective against at least 16 downy mildew pathotypes. We mapped their resistance genes on the sunflower reference genome of 3,600 Mb, in intervals that varied from 75 Kb to 32 Mb using an AXIOM^® genotyping array of 49,449 SNP. Ten probably new genes were identified according to resistance spectrum, map position, hypersensitive response to the transient expression of a P. halstedii RXLR effector, or the ecotype/species from which they originated. The resistance source HAS6 was found to carry the first downy mildew resistance gene mapped on chromosome 11, whereas the other resistances were positioned on chromosomes 1, 2, 4, and 13 carrying already published Pl genes that we also mapped physically on the same reference genome. The new genes were designated Pl₂₃-Pl₃₂ according to the current nomenclature. However, since sunflower downy mildew resistance genes have not yet been sequenced, rules for designation are discussed. This is the first large scale physical mapping of both 10 new and 10 already reported downy mildew resistance genes in sunflower.