Accounting for variability in the detection and use of markers for simple and complex traits

There are many sources of variability in gene–phenotype associations. During the measurement of genotype and phenotype and during selection, researchers must deal with experimental error in trials; gene-gene interaction (epistasis) for sub-traits and observed traits; trait-trait interaction (pleiotropy) and gene- or genotype-by-environment interaction. These effects can be structured in a framework that allows simulation of the entire gene-environment ‘landscape’. Studies of these landscapes have been published by others. Here we aim to explain with simple examples some of the types of insights that can be made. A current challenge for breeders working with simple marker–phenotype associations is to design selection strategies that can rapidly create new combinations of multiple marker-based traits. For a real-world example in wheat, we have used simulation to show how gene enrichment during early generations (selection of homozygotes and heterozygotes with desirable alleles) can greatly reduce resource requirements when combining 9 genes into one genotype through marker-assisted selection. Another wheat example compares phenotypic and QTL-based selection for coleoptile length where the QTL also had a pleiotropic association with plant height. These simulations show the relative negative effects of either low heritability, or less than complete detection of QTL associated with traits. Finally, we revisit a marker-assisted selection (MAS) example whereby a QTL study is undertaken on a population for a complex trait, and then those QTL are used in selection. This process is subject to all sources of error described above. If the trait is complex, then interactions among sub-traits; between sub-traits and the environment; or between the chromosomal locations of controlling genes, create an extremely ‘rugged’ selection landscape that slows breeding progress. In this situation, a detailed understanding of some of these interactions is required if MAS is to be able to exceed the progress of conventional breedin

Evaluation of a reduced-tillering (tin) gene in wheat lines grown across different production environments

Post-anthesis water deficit and increasing vapour pressure deficit are common and can result in reduced grain yield and the development of small or shrivelled wheat kernels (screenings) that reduce grain value. Previous studies suggest incorporation of a tiller inhibition (tin) gene to restrict tiller number and thereby slow water use and promote the development of larger, fertile spikes to increase kernel weight. This paper reports on the influence of the tin gene on grain yield and screenings in multiple wheat genetic backgrounds assessed in field experiments in 2005 and 2006. Across environments, grain yield ranged from 0.90 to 5.50t/ha and screenings from 4 to 20%. The effect of tin on grain yield and screenings varied with environment and genetic background. Grain yield was unchanged in tin lines derived from varieties Brookton, Chara, and Wyalkatchem assessed in southern Australian environments. However, there was a 31 and 10% advantage of free-tillering over tin-containing Silverstar lines for the 2005 western and 2006 northern experiments, respectively, resulting in an average 12% reduction in grain yield of Silverstar tin lines. In northern experiments, where screenings ranged from 4 to 12%, Silverstar-based tin lines produced significantly fewer screenings than free-tillering sister lines. Reduction in screenings was associated with a higher kernel weight (+10%) and a tendency for lower grain yield, although individual Silverstar tin progeny with grain yield equivalent to the parent were readily identified. The incorporation of the tin gene has considerable potential to reduce the incidence of screenings in commercial wheat crops. Variation in grain yield associated with the tin gene was dependent on genetic background, with potential for selection of higher yielding tin progeny for commercial line development