Molecular markers associated with a new source of resistance to the cassava mosaic disease

The predominant source of resistance to the cassava mosaic disease (CMD) is known to be polygenic requiring evaluation in multiple environments to characterise resistant genotypes, which makes the detection of genes for resistance using segregation analysis inefficient. Recently, some landraces have been identified which exhibit high levels of resistance to CMD. In this study, molecular markers associated with resistance to CMD in a resistant landrace were identified, using F1 progenies derived from a cross between the CMD resistant landrace TME7 and the susceptible line TMS30555, as a first step in marker assisted breeding for CMD resistance. Bulk segregant analysis (BSA) on the parents, resistant and susceptible DNA pools, using simple sequence repeat (SSR) and amplified fragment length polymorphism (AFLP) markers revealed that an SSR marker, SSRY28-180, donated by the resistant parent was linked with resistance to CMD. Marker-trait association detected by regression analysis showed that the marker, accounted for 57.41% of total phenotypic variation for resistance. The analysis furthershowed that another SSR marker, SSRY106-207 and an AFLP marker, E-ACC/M-CTC-225, accounted for 35.59% and 22.5% of the total phenotypic variation for resistance, respectively. The implication of the results in breeding for resistance to CMD is discussed

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