Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker–trait associations in sugarcaneThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Abstract

Few association mapping studies have simultaneously accounted for population structure, genotype by environment interaction (GEI), and spatial variation. In this sugarcane association mapping study we tested models accounting for these factors and identified the impact that each model component had on the list of markers declared as being significantly associated with traits. About 480 genotypes were evaluated for cane yield and sugar content at three sites and scored with DArT markers. A mixed model was applied in analysis of the data to simultaneously account for the impacts of population structure, GEI, and spatial variation within a trial. Two forms of the DArT marker data were used in the analysis: the standard discrete data (0, 1) and a continuous DArT score, which is related to the marker dosage. A large number of markers were significantly associated with cane yield and sugar content. However, failure to account for population structure, GEI, and (or) spatial variation produced both type I and type II errors, which on the one hand substantially inflated the number of significant markers identified (especially true for failing to account for GEI) and on the other hand resulted in failure to detect markers that could be associated with cane yield or sugar content (especially when failing to account for population structure). We concluded that association mapping based on trials from one site or analysis that failed to account for GEI would produce many trial-specific associated markers that would have low value in breeding programs.

Genome‐wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America

“…GWA and genomic prediction studies that used phenotypic data spanning multiple continents are rare, with notable exceptions being a few studies in wheat (Crossa et al, 2014(Crossa et al, , 2007. However, such broad sampling of environments can enable the identification of SNPs that are broadly useful for improving breeding values across environments (Wei et al, 2010) and improve genomic prediction accuracy via the use of phenotypes from correlated environments (Crossa et al, 2014;Spindel et al, 2016).…”

Prospecting sugarcane resistance to Sugarcane yellow leaf virus by genome-wide association

“…Notwithstanding genome complexity, several studies have applied association mapping to sugarcane. Using 1,209 polymorphic markers (AFLP and SSR), Wei et al (2006) detected associations with resistance to four diseases in a collection of 154 cultivars and later on they identified DArT markers related to cane yield and sugar content traits on a sample of 480 genotypes (Wei et al 2010). These studies confirmed the potential of genome-wide association mapping in the polyploid context of sugarcane.…”

Full-Length Enriched cDNA Libraries and ORFeome Analysis of Sugarcane Hybrid and Ancestor Genotypes

“…Despite recent advances [10]–[16], biotechnology for sugarcane analysis is less advanced than that for other economically important crops. For example, compared with sorghum, maize, and rice, sugarcane does not have a draft genome sequence available or a well-annotated transcriptome.…”