Genetic architecture of leaf ecophysiological traits in Helianthus

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.

Genotypes of Brassica rapa respond differently to plant-induced variation in air CO2 concentration in growth chambers with standard and enhanced venting

Growth chambers allow measurement of phenotypic differences among genotypes under controlled environment conditions. However, unintended variation in growth chamber air CO2 concentration ([CO2]) may affect the expression of diverse phenotypic traits, and genotypes may differ in their response to variation in [CO2]. We monitored [CO2] and quantified phenotypic responses of 22 Brassica rapa genotypes in growth chambers with either standard or enhanced venting. [CO2] in chambers with standard venting dropped to 280 micromol mol(-1) during the period of maximum canopy development, approximately 80 micromol mol(-1) lower than in chambers with enhanced venting. The stable carbon isotope ratio of CO2 in chamber air (delta13C(air)) was negatively correlated with [CO2], suggesting that photosynthesis caused observed [CO2] decreases. Significant genotype x chamber-venting interactions were detected for 12 of 20 traits, likely due to differences in the extent to which [CO2] changed in relation to genotypes' phenology or differential sensitivity of genotypes to low [CO2]. One trait, 13C discrimination (delta13C), was particularly influenced by unaccounted-for fluctuations in delta13C(air) and [CO2]. Observed responses to [CO2] suggest that genetic variance components estimated in poorly vented growth chambers may be influenced by the expression of genes involved in CO2 stress responses; genotypic values estimated in these chambers may likewise be misleading such that some mapped quantitative trait loci may regulate responses to CO2 stress rather than a response to the environmental factor of interest. These results underscore the importance of monitoring, and where possible, controlling [CO2].

Phenotypic selection on leaf ecophysiological traits in Helianthus

Habitats that differ in soil resource availability are expected to differ for selection on resource-related plant traits. Here, we examined spatial and temporal variation in phenotypic selection on leaf ecophysiological traits for 10 Helianthus populations, including two species of hybrid origin, Helianthus anomalus and Helianthus deserticola, and artificial hybrids of their ancestral parents. Leaf traits assessed were leaf size, succulence, nitrogen (N) concentration and water-use efficiency (WUE). Biomass and leaf traits of artificial hybrids indicate that the actively moving dune habitat of H. anomalus was more growth limiting, with lower N availability but higher relative water availability than the stabilized dune habitat of H. deserticola. Habitats differed for direct selection on leaf N and WUE, but not size or succulence, for the artificial hybrids. However, within the H. anomalus habitat, direct selection on WUE also differed among populations. Across years, direct selection on leaf traits did not differ. Leaf N was the only trait for which direct selection differed between habitats but not within the H. anomalus habitat, suggesting that nutrient limitation is an important selective force driving adaptation of H. anomalus to the active dune habitat.