Genome-wide association mapping of correlated traits in cassava: dry matter and total carotenoid content

Abstract

Cassava is a starchy root crop cultivated in the tropics for fresh consumption and commercial processing. Primary selection objectives in cassava breeding include dry matter content and micronutrient density, particularly provitamin A carotenoids. These traits are negatively correlated in the African germplasm. This study aimed at identifying genetic markers associated with these traits and uncovering whether linkage and/or pleiotropy were responsible for observed negative correlation. A genome-wide association mapping using 672 clones genotyped at 72,279 single nucleotide polymorphism (SNP) loci was performed. Root yellowness was used indirectly to assess variation in carotenoid content. Two major loci for root yellowness were identified on chromosome 1 at positions 24.1 and 30.5 Mbp. A single locus for dry matter content that colocated with the 24.1 Mbp peak for carotenoids was identified. Haplotypes at these loci explained 70 and 37% of the phenotypic variability for root yellowness and dry matter content, respectively. Evidence of megabasescale linkage disequilibrium (LD) around the major loci of the two traits and detection of the major dry matter locus in independent analysis for the white-and yellow-root subpopulations suggests that physical linkage rather that pleiotropy is more likely to be the cause of the negative correlation between the target traits. Moreover, candidate genes for carotenoid (phytoene synthase) and starch biosynthesis (UDP-glucose pyrophosphorylase and sucrose synthase) occurred in the vicinity of the identified locus at 24.1 Mbp. These findings elucidate the genetic architecture of carotenoids and dry matter in cassava and provide an opportunity to accelerate breeding of these traits.

Genome-Wide Association Analysis for Tuber Dry Matter and Oxidative Browning in Water Yam (Dioscorea alata L.)

“…For quality traits, DNA-based strategies such as GWAS reported in this study have advantages over the conventional selection breeding approach because it has the potential to fast-track the development and delivery of improved yam varieties with acceptable end-user attributes. The potential of GWAS to dissect complex traits has been proven in root and tuber crops such as cassava [ 24 , 25 , 26 ] and potatoes [ 27 , 28 ]. The present GWAS sought to identify QTL (s) and putative candidate genes associated with genetic variation in DMC and OxB in water yam.…”

The Cassava Source–Sink project: opportunities and challenges for crop improvement by metabolic engineering

“…Genome‐wide association studies (GWAS) are becoming increasingly important in crop breeding because they connect genotypes with phenotypes (Fernie and Gutierrez‐Marcos, 2019). In cassava, GWAS of 672 cassava clones and 72 000 single nucleotide polymorphism loci used the yellow color intensity (yellowness) of storage roots to indirectly assess variation in carotenoid and dry matter content (Rabbi et al ., 2017). This study built on earlier work using bi‐parental crosses to detect quantitative trait loci for these traits.…”

“…Rabbi et al . (2017) identified two major loci for yellowness and one for dry matter that co‐localized with one of the yellowness loci, although changes in the traits were negatively correlated. The identified genomic region identified was relatively large as a result of the low rate of recombination in the genomic region, although the genes encoding UDP‐glucose pyrophosphorylase and sucrose synthase mapped to this region.…”

Validation of QTLs for plant ideotype, earliness and growth habit traits in pigeonpea (Cajanus cajan Millsp.)

“…The box plots generated to detect favorable allele of trait-linked SSRs suggested that the alleles ASSR8 150 , ASSR390 170 , ASSR295 140 and CcTFL1 734 significantly contributed to earliness and plant type traits in pigeonpea. Similar approach has been used in other crops to discover the contributing allele of a linked marker for a trait, for instance SNP alleles for plant height, grain yield and release of glucose in wheat (Bellucci et al 2015), fruit quality in tomato (Albert et al 2016), lint percentage in upland cotton (Su et al 2016) and dry matter content in cassava (Rabbi et al 2017).…”