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.

Climate change leading to increased periods of low water availability as well as increasing demands for food in the coming years makes breeding for drought tolerant crops a high priority. Plants have developed diverse strategies and mechanisms to survive drought stress. However, most of these represent drought escape or avoidance strategies like early flowering or low stomatal conductance that are not applicable in breeding for crops with high yields under drought conditions. Even though a great deal of research is ongoing, especially in cereals, in this regard, not all mechanisms involved in drought tolerance are yet understood. The identification of candidate genes for drought tolerance that have a high potential to be used for breeding drought tolerant crops represents a challenge. Breeding for drought tolerant crops has to focus on acceptable yields under water-limited conditions and not on survival. However, as more and more knowledge about the complex networks and the cross talk during drought is available, more options are revealed. In addition, it has to be considered that conditioning a crop for drought tolerance might require the production of metabolites and might cost the plants energy and resources that cannot be used in terms of yield. Recent research indicates that yield penalty exists and efficient breeding for drought tolerant crops with acceptable yields under well-watered and drought conditions might require uncoupling yield penalty from drought tolerance.

Potato is regarded as drought sensitive and most vulnerable to climate changes. Its cultivation in drought prone regions or under conditions of more frequent drought periods, especially in subtropical areas, requires intensive research to improve drought tolerance in order to guarantee high yields under limited water supplies. A candidate gene approach was used to develop functional simple sequence repeat (SSR) markers for association studies in potato with the aim to enhance breeding for drought tolerance. SSR primer combinations, mostly surrounding interrupted complex and compound repeats, were derived from 103 candidate genes for drought tolerance. Validation of the SSRs was performed in an association panel representing 34 mainly starch potato cultivars. Seventy-five out of 154 SSR primer combinations (49%) resulted in polymorphic, highly reproducible banding patterns with polymorphic information content (PIC) values between 0.11 and 0.90. Five SSR markers identified allelic differences between the potato cultivars that showed significant associations with drought sensitivity. In all cases, the group of drought-sensitive cultivars showed predominantly an additional allele, indicating that selection against these alleles by marker-assisted breeding might confer drought tolerance. Further studies of these differences in the candidate genes will elucidate their role for an improved performance of potatoes under water-limited conditions.

Drought represents a major abiotic stress factor negatively affecting growth, yield and tuber quality of potatoes. Quantitative trait locus (QTL) analyses were performed in cultivated potatoes for drought tolerance index DRYM (deviation of relative starch yield from the experimental median), tuber starch content, tuber starch yield, tuber fresh weight, selected transcripts and metabolites under control and drought stress conditions. Eight genomic regions of major interest for drought tolerance were identified, three representing standalone DRYM QTL. Candidate genes, e.g., from signaling pathways for ethylene, abscisic acid and brassinosteroids, and genes encoding cell wall remodeling enzymes were identified within DRYM QTL. Co-localizations of DRYM QTL and QTL for tuber starch content, tuber starch yield and tuber fresh weight with underlying genes of the carbohydrate metabolism were observed. Overlaps of DRYM QTL with metabolite QTL for ribitol or galactinol may indicate trade-offs between starch and compatible solute biosynthesis. Expression QTL confirmed the drought stress relevance of selected transcripts by overlaps with DRYM QTL. Bulked segregant analyses combined with next-generation sequencing (BSAseq) were used to identify mutations in genes under the DRYM QTL on linkage group 3. Future analyses of identified genes for drought tolerance will give a better insight into drought tolerance in potatoes.

Cytoplasmic male sterility (CMS) systems represent ideal mutants to study the role of mitochondria in pollen development. In sunflower, CMS PET2 also has the potential to become an alternative CMS source for commercial sunflower hybrid breeding. CMS PET2 originates from an interspecific cross of H. petiolaris and H. annuus as CMS PET1, but results in a different CMS mechanism. Southern analyses revealed differences for atp6, atp9 and cob between CMS PET2, CMS PET1 and the male-fertile line HA89. A second identical copy of atp6 was present on an additional CMS PET2-specific fragment. In addition, the atp9 gene was duplicated. However, this duplication was followed by an insertion of 271 bp of unknown origin in the 5′ coding region of the atp9 gene in CMS PET2, which led to the creation of two unique open reading frames orf288 and orf231. The first 53 bp of orf288 are identical to the 5′ end of atp9. Orf231 consists apart from the first 3 bp, being part of the 271-bp-insertion, of the last 228 bp of atp9. These CMS PET2-specific orfs are co-transcribed. All 11 editing sites of the atp9 gene present in orf231 are fully edited. The anther-specific reduction of the co-transcript in fertility-restored hybrids supports the involvement in male-sterility based on CMS PET2.