Genetic analysis and association of simple sequence repeat markers with storage root yield, dry matter, starch and β-carotene content in sweetpotato

Abstract

Molecular markers are needed for enhancing the development of elite sweetpotato (Ipomoea batatas (L.) Lam) cultivars with a wide range of commercially important traits in sub-Saharan Africa. This study was conducted to estimate the heritability and determine trait correlations of storage root yield, dry matter, starch and β-carotene content in a cross between ‘New Kawogo’ × ‘Beauregard’. The study was also conducted to identify simple sequence repeat (SSR) markers associated with these traits. A total of 287 progeny and the parents were evaluated for two seasons at three sites in Uganda and genotyped with 250 SSR markers. Broad sense heritability (H2) for storage root yield, dry matter, starch and β-carotene content were 0.24, 0.68, 0.70 and 0.90, respectively. Storage root β-carotene content was negatively correlated with dry matter (r = −0.59, P < 0.001) and starch (r = −0.93, P < 0.001) content, while storage root yield was positively correlated with dry matter (r = 0.57, P = 0.029) and starch (r = 0.41, P = 0.008) content. Through logistic regression, a total of 12, 4, 6 and 8 SSR markers were associated with storage root yield, dry matter, starch and β-carotene content, respectively. The SSR markers used in this study may be useful for quantitative trait loci analysis and selection for these traits in future.

Adaptability of a U.S. purple-fleshed sweetpotato breeding population in Uganda

“…Results also indicated that genotypes expressed the trait differently in different environments. Earlier research reported that dry matter content varied widely with the genotype and locations (Manrique and Hermann, 2000;Mwanga et al, 2007;Rukundo et al, 2013;Shumbusha et al, 2014;Yada et al, 2017). In this study, dry matter content ranged from 21.5 to 33.7% across locations and seasons.…”

Quantitative trait loci and differential gene expression analyses reveal the genetic basis for negatively associated β-carotene and starch content in hexaploid sweetpotato [Ipomoea batatas (L.) Lam.]

“…Using this method, multiple QTL mapping is performed, so that the search for new QTL is conditioned to all the other QTL already in the model (Pereira et al 2019). Although previous studies in sweetpotato have reported QTL for quality-related traits including β-carotene (flesh color), dry matter, and starch (Cervantes-Flores et al 2011;Zhao et al 2013;Xiao-xia et al 2014;Zhang et al 2016;Yada et al 2017), such studies following the pseudo-testcross approach have not contributed substantially towards applied breeding as they present a challenge in comparison with other studies. The current study provides a major improvement in the potential of marker-assisted breeding in sweetpotato.…”

“…The modification of amyloplasts, which are the energy stores within the plant cell to store carotenoids, results in starch biosynthesis and carotenoid biosynthesis competing for carbon that leads to the negative association reported in several crops including citrus (Cao et al 2015), potato (Mortimer et al 2016), and sweetpotato (Yada et al 2017). Application of quantitative and population genetic principles, combined with improved experimental and statistical designs, has led to the release of many improved sweetpotato varieties, including orange-fleshed ones, in several countries within SSA recently (Gruneberg et al 2015;Andrade et al 2016).…”

Phenotypic Variation in Leaf Morphology of the USDA, ARS Sweetpotato (Ipomoea batatas) Germplasm Collection

“…The diversity in sweetpotato has been assessed using morphological, physiological (chemical), and molecular methods (Elameen et al, 2011;He et al, 2006;Huang and Sun, 2000 Although morphological characterization was the initial method for assessing diversity in sweetpotato (Mohan et al, 2012;Mwanga et al, 2017), morphological characters cannot be used alone to characterize sweetpotato germplasm fully, as ''phenotypic diversity is discordant to molecular diversity and both types of data are necessary in order to characterize sweetpotato germplasm'' (Elameen et al, 2011). Thus, diversity analyses often include both morphological and molecular information (Alfred et al, 2019;Koussao et al, 2014;Yada et al, 2017). Furthermore, Rosero et al (2019) found that the inclusion of morphometric (e.g., circularity, aspect ratio, roundness, solidity, area) and colorimetric (CIE L*a*b*C*h* or RGB data from images) information to standard morphological characterization improved estimates of phenotypic plant diversity in sweetpotato, and they were able to discriminate different phenotypes not detected by conventional morphological descriptors.…”