Accelerating Genetic Gain in Sugarcane Breeding Using Genomic Selection

Abstract

Sugarcane is a major industrial crop cultivated in tropical and subtropical regions of the world. It is the primary source of sugar worldwide, accounting for more than 70% of world sugar consumption. Additionally, sugarcane is emerging as a source of sustainable bioenergy. However, the increase in productivity from sugarcane has been small compared to other major crops, and the rate of genetic gains from current breeding programs tends to be plateauing. In this review, some of the main contributors for the relatively slow rates of genetic gain are discussed, including (i) breeding cycle length and (ii) low narrow-sense heritability for major commercial traits, possibly reflecting strong non-additive genetic effects involved in quantitative trait expression. A general overview of genomic selection (GS), a modern breeding tool that has been very successfully applied in animal and plant breeding, is given. This review discusses key elements of GS and its potential to significantly increase the rate of genetic gain in sugarcane, mainly by (i) reducing the breeding cycle length, (ii) increasing the prediction accuracy for clonal performance, and (iii) increasing the accuracy of breeding values for parent selection. GS approaches that can accurately capture non-additive genetic effects and potentially improve the accuracy of genomic estimated breeding values are particularly promising for the adoption of GS in sugarcane breeding. Finally, different strategies for the efficient incorporation of GS in a practical sugarcane breeding context are presented. These proposed strategies hold the potential to substantially increase the rate of genetic gain in future sugarcane breeding.

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects

“…Genetic improvement by selection has substantially contributed to the cane and sugar yield of modern cultivars (Ming et al 2010). However, over the past two decades, the genetic improvement rate has been low or static in sugarcane compared to other major crops (Wei and Jackson 2016;Yadav et al 2020).…”

Near-infrared spectroscopy outperforms genomics for predicting sugarcane feedstock quality traits

“…At T1, an array of limitations including physical space and short supply of propagation material precludes the installation of appropriate statistical experimental designs, which contributes to diminishing the selection accuracy, especially regarding low heritability traits [ 25 ]. Moreover, most sugarcane traits are believed to be quantitatively inherited [ 104 , 105 ]. Therefore, the subsequent stages of selection involve capital intensive field trials over multiple sites and years.…”

“…Therefore, the subsequent stages of selection involve capital intensive field trials over multiple sites and years. Today, one breeding cycle of phenotypic selection in sugarcane can take up to 13 years [ 105 , 106 ].…”

“…The optimal strategy to incorporate GP into breeding schemes is not straightforward and needs consideration, since it can be influenced by many factors [ 107 ]. In the context of sugarcane breeding, some authors have argued that the main benefit of applying GP could come from the length reduction of breeding cycles by performing early selection of parental clones [ 58 , 105 ]. Sugarcane breeding programs typically adopt into their pipelines intrapopulational recurrent selection (IRS) schemes [ 108 ].…”

“…According to Yadav et al, (2020) [ 105 ], the costs associated with high-throughput genotyping can be a major impediment for the adoption of large scale GP in sugarcane breeding. However, the decreasing costs of genotyping platforms and the integration with HTP platforms is encouraging [ 1 , 11 , 40 ].…”