Gene Pool Subdivision of East African Sweetpotato Parental Material

David, Maria; Díaz, Federico; Mwanga, R.O.M.; Tumwegamire, Silver; Mansilla, Roberto; Grüneberg, Wolfgang J.

doi:10.2135/cropsci2017.11.0695

Cited by 30 publications

(44 citation statements)

References 48 publications

(90 reference statements)

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“…The MDP population was developed from the sweetpotato breeding platform for east and central Africa of the International Potato Center (CIP). It is made up of a diallel cross among 16 parents from this breeding platform, coming from two gene pools (here A and B) separated by SSR markers (David et al, 2018). There are 64 families (8B by 8A crosses) each with 30 genotypes on average.…”

Section: Methodsmentioning

confidence: 99%

When a phenotype is not the genotype: Implications of phenotype misclassification and pedigree errors in genomics-assisted breeding of sweetpotato [Ipomoea batatas(L.) Lam.]

Gemenet¹,

Boeck²,

Pereira

et al. 2019

Preprint

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Experimental error, especially through genotype misclassification and pedigree errors, negatively affects breeding decisions by creating ‘noise’ that compounds the genetic signals for selection. Unlike genotype-by-environment interactions, for which different methods have been proposed to address, the effect of ‘noise’ due to pedigree errors and misclassification has not received much attention in most crops. We used two case studies in sweetpotato, based on data from the International Potato Center’s breeding program to estimate the level of phenotype misclassification and pedigree error and to demonstrate the consequences of such errors when combining phenotypes with the respective genotypes. In the first case study, 27.7% phenotype misclassification was observed when moving genotypes from a diversity panel throughin-vitro, screenhouse and field trialing. Additionally, 22.7% pedigree error was observed from misclassification between and within families. The second case study involving multi-environment testing of a full-sib population and quantitative trait loci (QTL) mapping showed reduced genetic correlations among pairs of environments in mega-environments with higher phenotype misclassification errors when compared to the mega-environments with lower phenotype misclassification errors. Additionally, no QTL could be identified in the low genetic correlation mega-environments. Simulation analysis indicated that phenotype misclassification was more detrimental to QTL detection when compared to missingness in data. The current information is important to inform current and future breeding activities involving genomic-assisted breeding decisions in sweetpotato, and to facilitate putting in place improved workflows that minimize phenotype misclassification and pedigree errors.

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Section: Methodsmentioning

confidence: 99%

When a phenotype is not the genotype: Implications of phenotype misclassification and pedigree errors in genomics-assisted breeding of sweetpotato [Ipomoea batatas(L.) Lam.]

Gemenet¹,

Boeck²,

Pereira

et al. 2019

Preprint

Self Cite

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“…The MDP population was developed by crossing 16 parents from the east and central African support platform. The parents were crossed in 8*8 without reciprocals following a B*A pseudo-heterotic grouping based on genetic distance established by simple sequence repeat (SSR) markers ( David et al 2018 ). With about 30 genotypes per family on average leading to ∼2000 genotypes, about 5% of this population was selected for QA/QC, tracking the population from in vitro , through screen house and field ( Gemenet et al 2019a ).…”

Section: Methodsmentioning

confidence: 99%

Development of diagnostic SNP markers for quality assurance and control in sweetpotato [Ipomoea batatas (L.) Lam.] breeding programs

Gemenet¹,

Kitavi²,

David³

et al. 2019

Preprint

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AbstractQuality assurance and control (QA/QC) is an essential element of a breeding program’s optimization efforts towards increased genetic gains. Due to auto-hexaploid genome complexity, a low-cost marker platform for routine QA/QC in sweetpotato breeding programs is still unavailable. We used 662 parents of the International Potato Center (CIP)’s global breeding program spanning Peru, Uganda, Mozambique and Ghana, to develop a low-density highly informative single nucleotide polymorphism (SNP) marker set to be deployed for routine QA/QC. Segregation of the selected 30 SNPs (two SNPs per base chromosome) in a recombined breeding population was evaluated using 282 progeny from some of the parents above. The progeny were replicated from in-vitro, screenhouse and field, and the selected SNP-set was confirmed to identify relatively similar mislabeling error rates as a high density SNP-set of 10,159 markers. Six additional trait-specific markers were added to the selected SNP set from previous quantitative trait loci mapping. The 36-SNP set will be deployed for QA/QC in breeding pipelines and in fingerprinting of advanced clones or released varieties to monitor genetic gains in famers fields. The study also enabled evaluation of CIP’s global breeding population structure and the effect of some of the most devastating biotic stresses like sweetpotato virus disease on genetic variation management. These results will inform future deployment of genomic selection in sweetpotato.Key MessageA 36-SNP diagnostic marker set has been developed for quality assurance and control to support global sweetpotato breeding optimization efforts. Breeding population structure is shaped by sweetpotato virus disease prevalence.

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“…The population used in this study (Mwanga Diversity Panel) groups separated by 18 SSR markers (David et al, 2018). 64 crosses (B×A: B being the female parent and A being the male parent) were done to generate seeds that were established in vitro (at BecA) and later transferred to Uganda for phenotypic evaluation.…”

Section: Plant Materials and Crossesmentioning

confidence: 99%

“…Sweet potato is grown for food and nutritional security with the white-and cream-fleshed storage roots usually consumed as raw, boiled or fried as calorie sources, while the orange-fleshed sweet potato (OFSP) having sufficient beta-carotene levels to alleviate vitamin A deficiency (Gurmu et al, 2014). Additionally, sweet potato leaves are used as vegetable and aboveground biomass is widely used as animal feed (David et al, 2018). Bearing in mind the importance of this crop, efficient sweet potato breeding programs are vital to increase food security and improve health worldwide (in sub-Sahara Africa specifically).…”

Section: Introductionmentioning

confidence: 99%

Heterosis and combining ability for storage root, flesh color, virus disease resistance and vine weight in Sweet potato [Ipomoea batatas (L.) Lam.]

Bâ¹,

Gemenet²,

Onguso³

et al. 2020

Afr. J. Agric. Res.

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This study was done to determine the mid-parent heterosis, the general (GCA) and specific (SCA) combining abilities of storage root yield, sweet potato virus resistance (SPVD), flesh color and vine weight of candidate sweet potato clones. Sixteen selected genotypes from two gene pools were crossed in an 8B×8A cross having 64 families. Trials were conducted with 1,896 offsprings and 16 parents during two seasons at the National Crops Resources Research Institute in Uganda (NaCRRI) using a Westcott design (only checks were replicated). Significant differences in performance were noted among families for all traits in both seasons (P ≤ 0.001). Magabali×NK259L and Resisto×Naspot 7 were the best crosses for improving total storage root while Naspot 5×Naspot 7 stood out as the best cross for flesh color. The ratio of general combining ability to specific combining ability (GCA/SCA) for storage root, flesh color and SPVD ranged from 0.55 to 0.79, implying that additive gene effects were more important than non-additive gene effects for these traits. For vine weight, non-additive gene effects tended to be predominant. A susceptible parent Magabali and a moderately susceptible parent Naspot 1 had the most resistant progenies. This suggests that SPVD resistant alleles could be homozygous recessive, which may be confirmed in further studies. Correlation studies between traits were almost all significant except for flesh color and storage root yield. There was a positive and significant correlation (P ≤ 0.001) between flesh color and SPVD resistance, with orange roots being the most resistant to SPVD. This important finding can help breeders to come up with orange-fleshed sweet potatoes that are highly resistant to virus diseases.

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Gene Pool Subdivision of East African Sweetpotato Parental Material

Cited by 30 publications

References 48 publications

When a phenotype is not the genotype: Implications of phenotype misclassification and pedigree errors in genomics-assisted breeding of sweetpotato [Ipomoea batatas(L.) Lam.]

When a phenotype is not the genotype: Implications of phenotype misclassification and pedigree errors in genomics-assisted breeding of sweetpotato [Ipomoea batatas(L.) Lam.]

Development of diagnostic SNP markers for quality assurance and control in sweetpotato [Ipomoea batatas (L.) Lam.] breeding programs

Heterosis and combining ability for storage root, flesh color, virus disease resistance and vine weight in Sweet potato [Ipomoea batatas (L.) Lam.]

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