Genome-wide association mapping and genomic prediction for CBSD resistance in Manihot esculenta

Abstract

Cassava (Manihot esculenta Crantz) is an important security crop that faces severe yield loses due to cassava brown streak disease (CBSD). Motivated by the slow progress of conventional breeding, genetic improvement of cassava is undergoing rapid change due to the implementation of quantitative trait loci mapping, Genome-wide association mapping (GWAS), and genomic selection (GS). In this study, two breeding panels were genotyped for SNP markers using genotyping by sequencing and phenotyped for foliar and CBSD root symptoms at five locations in Uganda. Our GWAS study found two regions associated to CBSD, one on chromosome 4 which co-localizes with a Manihot glaziovii introgression segment and one on chromosome 11, which contains a cluster of nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes. We evaluated the potential of GS to improve CBSD resistance by assessing the accuracy of seven prediction models. Predictive accuracy values varied between CBSD foliar severity traits at 3 months after planting (MAP) (0.27–0.32), 6 MAP (0.40–0.42) and root severity (0.31–0.42). For all traits, Random Forest and reproducing kernel Hilbert spaces regression showed the highest predictive accuracies. Our results provide an insight into the genetics of CBSD resistance to guide CBSD marker-assisted breeding and highlight the potential of GS to improve cassava breeding.

Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection

“…The broad-sense heritability estimates for CBSD in the present study were comparable with heritability estimates previously reported (Kayondo et al, 2018), ranging from 0.25 for CBSDRs to 0.61 for CBSD3s, from the genome-wide association study involving ?1300 clones evaluated across five sites in Uganda. The broad-sense heritability estimates for CBSD in the present study were comparable with heritability estimates previously reported (Kayondo et al, 2018), ranging from 0.25 for CBSDRs to 0.61 for CBSD3s, from the genome-wide association study involving ?1300 clones evaluated across five sites in Uganda.…”

“…Moderate to high estimates of broad-sense heritability for foliar and root severities were registered for CBSD (ranging from 0.26 to 0.70) in both populations studied here. The broad-sense heritability estimates for CBSD in the present study were comparable with heritability estimates previously reported (Kayondo et al, 2018), ranging from 0.25 for CBSDRs to 0.61 for CBSD3s, from the genome-wide association study involving ?1300 clones evaluated across five sites in Uganda. These moderate to high broad-sense heritability estimates for CBSD indicated that selection efficiency either through conventional or GS would be high enough to achieve the desired genetic gains.…”

“…Genomic prediction accuracies from the initial training population (C 0 ) at NaCRRI have been estimated to be reasonably accurate for highly heritable traits, such as dry matter content (DMC) and CMD, but less for low heritability traits, such as fresh root yield (Wolfe et al, 2017). Whereas Wolfe et al (2017) focused on predicting yield traits and CMD, which are common problems across all cassava breeding programs in Africa, Kayondo et al (2018) specifically focused on QTL mapping and genomic predictions for CBSD-related traits, a problem facing cassava production only in eastern, central, and southern parts of Africa. Whereas Wolfe et al (2017) focused on predicting yield traits and CMD, which are common problems across all cassava breeding programs in Africa, Kayondo et al (2018) specifically focused on QTL mapping and genomic predictions for CBSD-related traits, a problem facing cassava production only in eastern, central, and southern parts of Africa.…”

Evolutionary and ecological functional genomics, from lab to the wild

“…() showcased the method's power for mapping natural genetic variants for more than 100 traits in A. thaliana . To date, GWAS have also identified the genetic basis of numerous agronomic traits, speeding up breeding programs of crops such as maize (Jiao et al ., ; Zila et al ., ; Wallace et al ., ; Hu et al ., ; Xu et al ., ) and rice (Huang et al ., , ; McCouch et al ., ; Wang et al ., ; Wang et al ., ), as well as crops with less well‐developed molecular resources such as wheat (Liu et al ., ; Kristensen et al ., ), soybean (Fang et al ., ), barley (Sharma et al ., ), cotton (Fang et al ., ; Du et al ., ), cassava (Kayondo et al ., ), foxtail millet (Jia et al ., ), spinach (Ma et al ., ) and cauliflower (Thorwarth et al ., ). GWAS are a particularly relevant tool for perennial species such as apple (Urrestarazu et al ., ), citrus (Minamikawa et al ., ), eucalyptus (Resende et al ., ) and poplar (Liu et al ., ).…”

Improving root characterisation for genomic prediction in cassava

“…Because cassava is an outcrossing species mostly 87 propagated by stem cuttings, conventional breeding methods can take more than five years to 88 produce superior performing clones (www.nextgencassava.org). Genome-wide association 89 studies (GWAS) are complementary to GS as they have proven effective for the identification 90 of QTL regions associated with several traits that are critical for cassava breeding, including 91 cassava mosaic disease resistance (CMD) (Wolfe et al, 2016), cassava brown streak disease 92 resistance (CBSD) (Kayondo et al, 2018), and beta-carotene content and dry matter content 93 (Rabbi et al, 2017). 94 95 In this study, size and shape related traits describing cassava roots were obtained through 96 automated image analysis.…”