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The genetic architectures of vine and skin maturity in tetraploid potato
Author(s) -
Maria V. CarazaHarter,
Jeffrey B. Endelman
Publication year - 2022
Publication title -
theoretical and applied genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.922
H-Index - 179
eISSN - 1432-2242
pISSN - 0040-5752
DOI - 10.1007/s00122-022-04159-z
Subject(s) - biology , diallel cross , quantitative trait locus , heritability , genetics , vine , genetic architecture , allele , genetic variation , horticulture , gene , hybrid
The genetic architectures of potato vine and skin maturity, as well as the correlation between the traits, were investigated using multiple techniques from quantitative genetics and genomics. Potato vine and skin maturity, which refer to foliar senescence and adherence of the tuber periderm, respectively, are both important to production and therefore breeding. Our objective was to investigate the genetic architectures of these traits in a genome-wide association panel of 586 genotypes, and through joint linkage mapping in a half-diallel subset (N = 397). Skin maturity was measured by image analysis after mechanized harvest 120 days after planting. To correct for the influence of vine maturity on skin maturity under these conditions, the former was used as a covariate in the analysis. The genomic heritability based on a 10 K SNP array was 0.33 for skin maturity vs. 0.46 for vine maturity. Only minor QTLs were detected for skin maturity, the largest being on chromosome 9 and explaining 8% of the variation. As in many previous studies, S. tuberosum Cycling DOF Factor 1 (CDF1) had a large influence on vine maturity, explaining 33% of the variation in the panel as a bi-allelic SNP and 44% in the half-diallel as a multi-allelic QTL. From the estimated effects of the parental haplotypes in the half-diallel and prior knowledge of the allelic series for CDF1, the CDF1 allele for each haplotype was predicted and ultimately confirmed through whole-genome sequencing. The ability to connect statistical alleles from QTL models with biological alleles based on DNA sequencing represents a new milestone in genomics-assisted breeding for tetraploid species.

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