Abstract:
:As one of the world's most important food crops, the potato (Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive (G), digenic dominant (D), and additive × additive epistatic (G#G) effects were calculated using 3895 markers, and the numerator relationship matrix (A) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm.
journal_name
Geneticsjournal_title
Geneticsauthors
Endelman JB,Carley CAS,Bethke PC,Coombs JJ,Clough ME,da Silva WL,De Jong WS,Douches DS,Frederick CM,Haynes KG,Holm DG,Miller JC,Muñoz PR,Navarro FM,Novy RG,Palta JP,Porter GA,Rak KT,Sathuvalli VR,Thompson AL,Yenchdoi
10.1534/genetics.118.300685subject
Has Abstractpub_date
2018-05-01 00:00:00pages
77-87issue
1eissn
0016-6731issn
1943-2631pii
genetics.118.300685journal_volume
209pub_type
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