Dataset Information

Cassava Breeding I: The Value of Breeding Value.

ABSTRACT: Breeding cassava relies on several selection stages (single row trial-SRT; preliminary; advanced; and uniform yield trials-UYT). This study uses data from 14 years of evaluations. From more than 20,000 genotypes initially evaluated only 114 reached the last stage. The objective was to assess how the data at SRT could be used to predict the probabilities of genotypes reaching the UYT. Phenotypic data from each genotype at SRT was integrated into the selection index (SIN) used by the cassava breeding program. Average SIN from all the progenies derived from each progenitor was then obtained. Average SIN is an approximation of the breeding value of each progenitor. Data clearly suggested that some genotypes were better progenitors than others (e.g., high number of their progenies reaching the UYT), suggesting important variation in breeding values of progenitors. However, regression of average SIN of each parental genotype on the number of their respective progenies reaching UYT resulted in a negligible coefficient of determination (r (2) = 0.05). Breeding value (e.g., average SIN) at SRT was not efficient predicting which genotypes were more likely to reach the UYT stage. Number of families and progenies derived from a given progenitor were more efficient predicting the probabilities of the progeny from a given parent reaching the UYT stage. Large within-family genetic variation tends to mask the true breeding value of each progenitor. The use of partially inbred progenitors (e.g., S1 or S2 genotypes) would reduce the within-family genetic variation thus making the assessment of breeding value more accurate. Moreover, partial inbreeding of progenitors can improve the breeding value of the original (S0) parental material and sharply accelerate genetic gains. For instance, homozygous S1 genotypes for the dominant resistance to cassava mosaic disease (CMD) could be generated and selected. All gametes from these selected S1 genotypes would carry the desirable allele and 100% of their progenies would be resistant. Only half the gametes produced by the heterozygous S0 progenitor would carry the allele of interest. For other characteristics, progenies from the S1 genotypes should be, at worst, similar to those generated by the S0 progenitors.

SUBMITTER: Ceballos H

PROVIDER: S-EPMC5003041 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Cassava Breeding I: The Value of Breeding Value.

Ceballos Hernán H Pérez Juan C JC Joaqui Barandica Orlando O Lenis Jorge I JI Morante Nelson N Calle Fernando F Pino Lizbeth L Hershey Clair H CH

Frontiers in plant science 20160829

Breeding cassava relies on several selection stages (single row trial-SRT; preliminary; advanced; and uniform yield trials-UYT). This study uses data from 14 years of evaluations. From more than 20,000 genotypes initially evaluated only 114 reached the last stage. The objective was to assess how the data at SRT could be used to predict the probabilities of genotypes reaching the UYT. Phenotypic data from each genotype at SRT was integrated into the selection index (SIN) used by the cassava breed ...[more]

PMID: 27621734

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Project description:Cassava brown streak disease (CBSD) caused by the rapidly evolving cassava brown streak viruses (CBSVs), causes immense yield losses to the cassava value chain in eastern and southern Africa. Western Africa, another region that heavily depends on cassava is under eminent threat from CBSD. Resistance breeding is the best practical solution. However, complexities associated with CBSD resistance screening i.e., variable root sampling units, limit systematic attainment of genetic progress. Accordingly, we compared efficiency of five CBSD root necrosis assessment methods to guide selection: cassava brown streak disease root incidence (CBSDRi), cassava brown streak disease root severity (CBSDRs), cassava brown streak disease root severity computed as harmonic mean (CBSD-Harmonic), proportion-based root necrosis index (CBSD-proportion), and standardized root necrosis index (CBSD-standardized). The indexes (CBSD-proportion and CBSD-standardized) correct for variable sample size. We analyzed CBSD root necrosis data of 256 clones evaluated across 12 environments. Higher and variable standard errors were associated with root severity score 1 (no CBSD root necrosis). Lowest and highest plot-based heritability were respectively registered for CBSD-standardized (0.22) and CBSD-proportion (0.71). CBSDRs was only positively correlated with CBSDRi (r = 0.92) and CBSD-Harmonic (r = 0.97). Using best linear unbiased predictions (BLUPs), we ranked the top 15 CBSD resistant clones; only one clone (UG130014) featured in all the five assessment methods; two clones (UG130006 and UG120156) featured in four (CBSD-Harmonic, CBSDRi, CBSDRs, and CBSD-standardized); and five clones (UG120180, UG120063, UG130002, UG130033, and UG120183) featured in three methods (CBSD-Harmonic, CBSDRi, and CBSDRs). Influence of sample size was also quantified by sub-setting and analyzing CBSDRs data to have plots with at least 40 or 30 roots. Data stabilization was evident in plots with 30 roots. The significant influence of root sample sizes on overall ranking of clones, justifies the use of CBSD root necrosis indexes in early selection stages i.e., seedling and/or clonal trials, that are often characterized by high variations in roots assessed per plot. It is expected that this information will provide a foundation for harmonizing and/or optimizing on-going and future CBSD resistance breeding efforts.

Project description:BACKGROUND:Microparasitic diseases are caused by bacteria and viruses. Genetic improvement of resistance to microparasitic diseases in breeding programs is desirable and should aim at reducing the basic reproduction ratio [Formula: see text]. Recently, we developed a method to derive the economic value of [Formula: see text] for macroparasitic diseases. In epidemiological models for microparasitic diseases, an animal's disease status is treated as infected or not infected, resulting in a definition of [Formula: see text] that differs from that for macroparasitic diseases. Here, we extend the method for the derivation of the economic value of [Formula: see text] to microparasitic diseases. METHODS:When [Formula: see text], the economic value of [Formula: see text] is zero because the disease is very rare. When [Formula: see text]. is higher than 1, genetic improvement of [Formula: see text] can reduce expenditures on vaccination if vaccination induces herd immunity, or it can reduce production losses due to disease. When vaccination is used to achieve herd immunity, expenditures are proportional to the critical vaccination coverage, which decreases with [Formula: see text]. The effect of [Formula: see text] on losses is considered separately for epidemic and endemic disease. Losses for epidemic diseases are proportional to the probability and size of major epidemics. Losses for endemic diseases are proportional to the infected fraction of the population at the endemic equilibrium. RESULTS:When genetic improvement reduces expenditures on vaccination, expenditures decrease with [Formula: see text] at an increasing rate. When genetic improvement reduces losses in epidemic or endemic diseases, losses decrease with [Formula: see text] at an increasing rate. Hence, in all cases, the economic value of [Formula: see text] increases as [Formula: see text] decreases towards 1. DISCUSSION:[Formula: see text] and its economic value are more informative for potential benefits of genetic improvement than heritability estimates for survival after a disease challenge. In livestock, the potential for genetic improvement is small for epidemic microparasitic diseases, where disease control measures limit possibilities for phenotyping. This is not an issue in aquaculture, where controlled challenge tests are performed in dedicated facilities. If genetic evaluations include infectivity, genetic gain in [Formula: see text] can be accelerated but this would require different testing designs. CONCLUSIONS:When [Formula: see text], its economic value is zero. The economic value of [Formula: see text] is highest at low values of [Formula: see text] and approaches zero at high values of [Formula: see text].

Dataset Information

Cassava Breeding I: The Value of Breeding Value.

Publications

Cassava Breeding I: The Value of Breeding Value.

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