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Title: Population extremes for assessing trait value and correlated response of genetically complex traits

item REBETZKE, GREG - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item RICHARDS, RICHARD - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item Holland, Jim - Jim

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/25/2016
Publication Date: 2/1/2017
Citation: Rebetzke, G., Richards, R., Holland, J.B. 2017. Population extremes for assessing trait value and correlated response of genetically complex traits. Field Crops Research. 201:122-132.

Interpretive Summary: Basic crop scientists have proposed a number of traits that are not common in cultivars, but could provide benefit to crop productivity in specific environments. An example of this is early vigor in dryland wheat. Detailed analyses of the effects of these traits when incorporated into diverse varieties would be useful to predict which traits should be targeted by plant breeders. However, such detailed analyses are costly and time-consuming, delaying the eventual incorporation of useful traits into cultivars. We propose here a method to conduct initial screenings in breeding populations for a proposed trait of interest, then selecting only the most extreme lines from the distribution of the selection trait. These ‘extreme tails’ of the distribution can then be evaluated in replicated field trials for yield and productivity. Differences between the two tail groups are a good indication of the potential utility of the trait as a selection criterion. Evaluating only the extremes of the population is a simple way to dramatically reduce the costs of conducting experiments.

Technical Abstract: Physiological studies have led to the identification of many traits hypothesized to be useful for breeding improved crop performance. The effect of selection for these traits on yield across breeding populations and across target environments is generally unknown, such that crop breeders may have difficulty in prioritizing evaluation resources among potentially many traits. A simple method to estimate the effect on crop performance from selection on a proposed trait would facilitate trait adoption toward implementation and delivery in improved varieties. The response to indirect selection for different traits can be accurately predicted with nearly-isogenic lines differing for only small regions of the genome and those traits under investigation. An alternative approach better suited to complex, polygenic traits is the assessment of direct and indirect response in ‘tails’ representing phenotypic extremes from a distribution for a target trait. The smaller set of lines representing the two tail groups can then be evaluated more extensively for yield or other expensive and difficult to phenotype traits. Assuming an infinitesimal model appropriate for polygenic traits, we used simulations to understand the influence of population size, proportion of lines sampled in each tail group, trait heritability, and the genotypic correlation between the selection and evaluation trait on the resulting difference between tail means. The power of the tail comparison test was closely related to the heritability of the selection trait and its genotypic correlation with the evaluation trait, demonstrating that the tail comparison test can appropriately evaluate and rank the potential utility of different selection traits. Increasing the entry-mean heritability through multiple environment testing can be coupled with larger population and tail group sizes to increase power and confidence in assessment of both selection and response trait values. We assessed the selection of phenotypic distribution tails for water productivity traits in wheat. Reduced-tillering tails were associated with an average 14% reduction in tiller number and significantly reduces yields (-5%), particularly at wider row-spacings. High vigour tails were associated with a 49% increase in early ground cover and 40% increase in NDVI score, and greater yields (+18%) across all sampled environments. Assessment of population tails across multiple genetic backgrounds will guide selection in commercial breeding programs and enhance facilitate trait delivery of trait values in improved cultivars.