Improving root characterisation for genomic prediction in cassava

Abstract

Cassava is cultivated due to its drought tolerance and high carbohydrate-containing storage roots. The lack of uniformity and irregular shape of storage roots poses constraints on harvesting and postharvest processing. Here, we phenotyped the Genetic gain and offspring (C1) populations from the International Institute of Tropical Agriculture (IITA) breeding program using image analysis of storage root photographs taken in the field. In the genome-wide association analysis (GWAS), we detected for most shape and size-related traits, QTL on chromosomes 1 and 12. In a previous study, we found the QTL on chromosome 12 to be associated with cassava mosaic disease (CMD) resistance. Because the root uniformity is important for breeding, we calculated the standard deviation (SD) of individual root measurements per clone. With SD measurements we identified new significant QTL for Perimeter, Feret and Aspect Ratio on chromosomes 6, 9 and 16. Predictive accuracies of root size and shape imageextracted traits were mostly higher than yield trait prediction accuracies. This study aimed to evaluate the feasibility of the image phenotyping protocol and assess GWAS and genomic prediction for size and shape image-extracted traits. The methodology described and the results are promising and open up the opportunity to apply high-throughput methods in cassava. Cassava (Manihot esculenta Crantz), a tropical root crop with origins in Latin America, ranks as the 3rd most important crop in the tropics after rice and maize 1. In Africa, more than 800 million people rely on cassava as a primary source of calories 2. Cassava is widely cultivated due to its high drought tolerance and high carbohydrate-containing storage roots, and although most of the production is for human consumption, its use extends to animal feed and industrially processed products 2-4. In addition to the edible, high-starch storage roots, cassava plants produce thin fibrous roots, which function to absorb water and nutrients from the soil 5. The development and differentiation of fibrous roots, as well as the mechanism that triggers root storage formation in cassava, are poorly understood. Cassava storage roots are morphologically diverse, the lack of uniformity and irregular shape between and within genotypes poses significant constraints on harvesting and post-harvest processing. The irregularity of root shape results in considerable losses of valuable root yield 3. The waste of tuber flesh and the inefficiency of hand peeling could be avoided by peeling mechanization. However, breeding for root characteristics that facilitate that process requires a thorough understanding of the genetic basis of cassava root morphology. Several studies have attempted to characterize cassava root shape to support the development of peeling mechanization 6,7. The root characteristics that were evaluated in those studies include root diameter, weight, length and peel thickness. Routine assessment of storage root size and shape in breeding plots relies on visual scores (www.cassavabase.o...

Technological Innovations for Improving Cassava Production in Sub-Saharan Africa

“… Kengkanna et al (2019) developed cassava shovelomics to evaluate root architecture traits. More recently, Yonis et al (2020) , demonstrated the feasibility of root phenotyping using image capture and analysis. Routine implementation of these new phenotyping solutions offers new opportunities for cassava breeders to efficiently and precisely select and release cultivars with root architecture that are favorable for harvesting, processing, as well as selection for early bulking characteristics.…”

“…There are great expectations for the use of GS in cassava breeding. Since the first GS studies in cassava conducted by de Oliveira et al (2012) and Ly et al (2013) , highlighting the potential of GS, several studies have been published ( Wolfe et al, 2017 ; Ozimati et al, 2018 ; de Andrade et al, 2019 ; Yonis et al, 2020 ). GS has been utilized in cassava breeding to increase resistance against CMD and CBSD in cassava populations ( Wolfe et al, 2016 ; Kayondo et al, 2018 ; Ozimati et al, 2018 ).…”

“… Torres et al (2019) predicted good progress in selecting clones for traits such as fresh root yield (FRY), dry matter content (DMC), fresh shoot yield (FSY), harvest index (HI), dry yield (DY) using GS. Yonis et al (2020) assessed genomic prediction for root size and shape based on root traits extracted from digital images. Greater predictive ability has been reported for DMC, CMD, and, to a lesser extent, HI compared to other traits ( Wolfe et al, 2016 ; de Andrade et al, 2019 ).…”

“…Greater predictive ability has been reported for DMC, CMD, and, to a lesser extent, HI compared to other traits ( Wolfe et al, 2016 ; de Andrade et al, 2019 ). This success has been attributed to their high to moderate heritability, large-effect QTLs and low genotype × environment interaction ( Torres et al, 2019 ; Yonis et al, 2020 ). GS is especially attractive for complex traits controlled by many QTLs with low heritability that are difficult or expensive to assess or are measured late in the breeding cycle ( de Oliveira et al, 2012 ).…”

Genomic mating in outbred species: predicting cross usefulness with additive and total genetic covariance matrices

“…Cassava is one of the most important tropical staple foods, especially in Africa (http://faostat.fao.org). Among outbred, clonal crops, GS is relatively mature in cassava breeding (Yonis et al;de Oliveira et al 2012;Ly et al 2013;Wolfe et al 2016a;b, 2017;Okeke et al 2017;Elias et al 2018;Ozimati et al 2018) because of the Next Generation Cassava Breeding Project (http://www.nextgencassava.org, est. 2012), and the species can serve as a model for many others.…”