Abstract
Cassava ( Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden.
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Claims 8
Claim · model-written summary
Nonadditive models predicted about 10% better than other models in cross-validation within cassava populations.
- Taxon
- Cassava
Manihot esculentat0 - Outcome
- Cross-validation resultse1
- Value
- 10%e1
- Qualifier
- nonadditive modelse1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e1“Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average”
Claim · model-written summary
Cross-population prediction accuracy was generally low.
- Taxon
- CassavaManihot esculentat0
- Outcome
- Cross-population accuracye2
- Value
- 0.18e2
- Qualifier
- generally lowe2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e2“Cross-population accuracy was generally low (mean = 0.18)”
Claim · model-written summary
Combining data from another related population increased the prediction of cassava mosaic disease by up to 57% in one Nigerian population.
- Taxon
- CassavaManihot esculentat0
- Treatment
- data from another related populatione3
- Outcome
- prediction of cassava mosaic diseasee3
- Direction
- increasede3
- Value
- up to 57%e3
- Setting
- Nigerian populatione3
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e3“prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined”
Claim · model-written summary
Prediction accuracy across generations was poorer than within-generation accuracy.
- Taxon
- CassavaManihot esculentat0
- Outcome
- Accuracy across generationse4
- Direction
- poorere4
- Comparator
- within-generation accuracye4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e4“Accuracy across generations was poorer than within-generation accuracy”
Claim · model-written summary
Accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling genomic selection.
- Taxon
- CassavaManihot esculentat0
- Outcome
- accuracy for dry matter content and mosaic disease severitye5
- Qualifier
- sufficient for rapid-cycling GSe5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e5“accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS”
Claim · model-written summary
Increasing the training population size mattered more for accuracy across generations than the choice of prediction model.
- Taxon
- CassavaManihot esculentat0
- Treatment
- increasing TP sizee6
- Outcome
- difference across generationse6
- Direction
- more importante6
- Comparator
- Selection of a prediction modele6
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e6“Selection of a prediction model made some difference across generations, but increasing TP size was more important”
Claim · model-written summary
With a genetic algorithm, selecting one-third of progeny for phenotyping gave accuracy equivalent to phenotyping all progeny.
- Taxon
- CassavaManihot esculentat0
- Treatment
- selection of one-third of progenye7
- Outcome
- accuracye7
- Direction
- equivalente7
- Qualifier
- With a genetic algorithme7
- Comparator
- phenotyping all progenye7
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e7“With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny”
Claim · model-written summary
The authors recommend growing training populations while phenotyping only a carefully selected subset of individuals.
- Taxon
- CassavaManihot esculentat0
- Outcome
- phenotypinge7
- Qualifier
- on a cleverly selected subset of individualse7
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Prospects for Genomic Selection in Cassava Breeding”
e7“TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals”