Genome-wide association analysis for lodging tolerance and plant height in a diverse European hexaploid oat collection

Abstract

Sensitivity to lodging of oat varieties has been reduced in the last decades through the introduction of dwarfing genes. However, lodging may still cause significant yield loss, underscoring the need for new oat varieties with higher levels of lodging tolerance. In the present study, we analysed lodging and plant height in a collection of European oat accessions including landraces, old and modern varieties, in order to perform a genome-wide association study (GWAS) for identifying markers associated to lodging tolerance. This collection has been recently genotyped by the Infinium 6K SNP array for oat and SNP data were analysed as continuous intensity ratios, rather than as discrete genotypes (Tumino et al. 2016, Theor Appl Genet 129, pp. 1711-1724). Phenotypes for lodging severity, plant height and growth habit were collected under natural conditions in eight European countries. Plant height correlated to lodging severity as previously observed in many studies, explaining about 30% of lodging variation. GWAS analyses detected six significant associations for lodging and two for plant height. These results indicate that GWAS can successfully be used for identifying markers associated to lodging in oat, even though lodging is a quantitative trait influenced by several plant characteristics.

Diversity and Pre-Breeding Prospects for Local Adaptation in Oat Genetic Resources

“…For the plant height the check mean was 98 cm, which was surpassed by 130 out of the entire 260 accessions in the collection, and turned to be too tall for the target environments. The variation in plant height (i.e., 68 to 149 cm; Table 1) was similar to the values reported for a European hexaploid oat collection screened within the AVEQ project [45]. Plant height is associated with lodging, but many other aspects also the affect lodging of oats [46].…”

“…Plant height is associated with lodging, but many other aspects also the affect lodging of oats [46]. Therefore, the correlation between plant height and lodging is often only moderate when a large collection of germplasm is screened [45]. In the present study, no correlation between plant height and lodging was observed as the breeders discarded too tall accessions after the first year and environmental conditions did not favor lodging thereafter.…”

“…Overall, population structure analyses reflected both the high genetic and phenotypic diversity within the identified subpopulations and across all accession in the investigated oats collection. With the emergence of molecular techniques, a few studies concerning the population structure of oat collections were published [7,8,10,13,14,45,[49][50][51][52][53]. Although all studies are biased with respect to the geographic origin of the investigated germplasm, a main conclusion is that the genetic diversity of North American oat varieties is larger compared to European varieties, and that population structures are generally weak and are not associated with morphological traits such as lemma color, caryopsis type, or panicle shape [7,8,[50][51][52].…”

Effects of uniconazole or gibberellic acid application on the lignin metabolism in relation to lodging resistance of culm in common buckwheat (Fagopyrum esculentum M.)

“…Lodging is the failure of plants to maintain an upright position under unfavourable weather conditions (rain and strong wind) (Tumino et al., ). When lodging occurs in cereals during or just after anthesis, it can cause severe losses in grain yield and reduce grain quality and mechanical harvesting efficiency (Acreche & Slafer, ; Berry & Spink, ; Pendleton, ; Stanca, Jenkins, & Hanson, ).…”

Genetic mapping in polyploids

“…The application of GWAS in polyploid species is relatively new, although there have already been a number of studies published in various crop species, for example in potato, oilseed rape, wheat, and oats (Uitdewilligen et al, 2013;Gajardo et al, 2015;Sukumaran et al, 2015;Tumino et al, 2016;Tumino et al, 2017). GWAS studies usually need to account for population structure and relatedness to prevent spurious associations, often in the context of linear mixed models (Yu et al, 2006;Bradbury et al, 2007;Zhang et al, 2010b).…”