Abstract
Given the universality of autopolyploid species in nature, it is crucial to develop genomic selection methods that consider different allele dosages for autopolyploid breeding. However, no method has been developed to deal with autopolyploid data regardless of the ploidy level. In this study, we developed a modified genomic best linear unbiased prediction (GBLUP) model (polyGBLUP) through constructing additive and dominant genomic relationship matrices based on different allele dosages. polyGBLUP could carry out genomic prediction for autopolyploid species regardless of the ploidy level. Through comprehensive simulations and analysis of real data of autotetraploid blueberry and guinea grass and autohexaploid sweet potato, the results showed that polyGBLUP achieved higher prediction accuracy than GBLUP and its superiority was more obvious when the ploidy level of autopolyploids is high. Furthermore, when the dominant effect was added to polyGBLUP (polyGDBLUP), the greater the dominance degree, the more obvious the advantages of polyGDBLUP over the diploid models in terms of prediction accuracy, bias, mean squared error and mean absolute error. For real data, the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population due to the high correlation coefficients between diploid and polyploidy genomic relationship matrices. In addition, polyGDBLUP did not produce higher prediction accuracy than polyGBLUP for most traits of real data as dominant genetic variance was not captured for these traits. Our study will be a significant promising method for genomic prediction of autopolyploid species.
Abstract from the paper’s OpenAlex record; open copy licensed cc-by-nc. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 7
Claim · model-written summary
polyGBLUP predicts autopolyploids regardless of ploidy level.
Not reportedComparatorValue
Verbatim
e0“polyGBLUP could carry out genomic prediction for autopolyploid species regardless of the ploidy level.”
Claim · model-written summary
polyGBLUP had higher prediction accuracy than GBLUP, especially at high ploidy.
Verbatim
e0“polyGBLUP achieved higher prediction accuracy than GBLUP and its superiority was more obvious when the ploidy level of autopolyploids is high.”
Claim · model-written summary
polyGDBLUP advantage over diploid models increased with dominance degree for accuracy, bias, mean squared error and mean absolute error.
- Outcome
- prediction accuracy, bias, mean squared error and mean absolute errore0
- Direction
- more obviouse0
- Comparator
- diploid modelse0
Not reportedTaxon
Verbatim
e0“the greater the dominance degree, the more obvious the advantages of polyGDBLUP over the diploid models in terms of prediction accuracy, bias, mean squared error and mean absolute error.”
Claim · model-written summary
polyGBLUP outperformed GBLUP in blueberry data.
Verbatim
e0“the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population”
Claim · model-written summary
polyGBLUP outperformed GBLUP in sweet potato data.
- Taxon
- sweet potato
_Flower.jpg?width=60)
Ipomoea batatase0 - Outcome
- superioritye0
- Direction
- superioritye0
- Comparator
- GBLUPe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
_Flower.jpg?width=500)
Verbatim
e0“the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population”
Claim · model-written summary
polyGBLUP outperformed GBLUP for some guinea grass traits.
- Taxon
- guinea grass
.jpg?width=60)
Megathyrsus maximuse0 - Outcome
- superioritye0
- Direction
- superioritye0
- Comparator
- GBLUPe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
.jpg?width=500)
Verbatim
e0“the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population”
Claim · model-written summary
polyGDBLUP did not improve prediction accuracy for most real-data traits over polyGBLUP.
- Outcome
- prediction accuracye0
- Direction
- did not produce highere0
- Qualifier
- most traits of real datae0
- Comparator
- polyGBLUPe0
Not reportedTaxon
Verbatim
e0“polyGDBLUP did not produce higher prediction accuracy than polyGBLUP for most traits of real data as dominant genetic variance was not captured for these traits.”