Login / Signup

Inbreeding Effects on the Performance and Genomic Prediction for Polysomic Tetraploid Potato Offspring Grown at High Nordic Latitudes.

Rodomiro OrtizFredrik ReslowRamesh Raju VetukuriM Rosario García-GilPaulino Pérez-RodríguezJosé Crossa
Published in: Genes (2023)
Inbreeding depression (ID) is caused by increased homozygosity in the offspring after selfing. Although the self-compatible, highly heterozygous, tetrasomic polyploid potato ( Solanum tuberosum L.) suffers from ID, some argue that the potential genetic gains from using inbred lines in a sexual propagation system of potato are too large to be ignored. The aim of this research was to assess the effects of inbreeding on potato offspring performance under a high latitude and the accuracy of the genomic prediction of breeding values (GEBVs) for further use in selection. Four inbred (S 1 ) and two hybrid (F 1 ) offspring and their parents (S 0 ) were used in the experiment, with a field layout of an augmented design with the four S 0 replicated in nine incomplete blocks comprising 100, four-plant plots at Umeå (63°49'30″ N 20°15'50″ E), Sweden. S 0 was significantly ( p < 0.01) better than both S 1 and F 1 offspring for tuber weight (total and according to five grading sizes), tuber shape and size uniformity, tuber eye depth and reducing sugars in the tuber flesh, while F 1 was significantly ( p < 0.01) better than S 1 for all tuber weight and uniformity traits. Some F 1 hybrid offspring (15-19%) had better total tuber yield than the best-performing parent. The GEBV accuracy ranged from -0.3928 to 0.4436. Overall, tuber shape uniformity had the highest GEBV accuracy, while tuber weight traits exhibited the lowest accuracy. The F 1 full sib's GEBV accuracy was higher, on average, than that of S 1 . Genomic prediction may facilitate eliminating undesired inbred or hybrid offspring for further use in the genetic betterment of potato.
Keyphrases
  • high fat diet
  • copy number
  • genome wide
  • body mass index
  • physical activity
  • weight loss
  • insulin resistance
  • mental health
  • early onset
  • body weight
  • sleep quality
  • virtual reality