Multi-allelic QTL analysis of protein content in a bi-parental population of cultivated tetraploid potato

Abstract

Protein content is a key quality trait for the potato starch industry. The objective of this study was to identify allele-specific quantitative trait loci (QTLs) for tuber protein content in cultivated potato ( Solanum tuberosum L.) at the tetraploid level. We analysed 496 full-sib F 1 clones in a 3-year field trial to dissect the complex genetic architecture of soluble tuber protein content. Genotypic data from a 60K single nucleotide polymorphism (SNP) array was used for SNP dosage scoring, constructing homologue specific linkage maps and assembly of a dense integrated chromosomal linkage map. From the integrated map, probabilistic multi-locus identity-by-descent (IBD) haplotypes (alleles) were estimated and used to detect associations between the IBD haplotypes and the phenotypic trait values. Moderate levels of trait heritability were estimated between 40 and 74% that correspond with previous studies. Our contemporary naive analysis identified potential additive QTLs on chromosomes 2 , 3 , 5 (top arm) and 9 across the years. Moreover, cofactor QTL analysis identified two masked QTLs on chromosomes 1 and 5 (lower arm). The QTLs on chromosomes 2 , 5 (lower arm) and 9 are reported here for the first time. The QTLs that we identified on chromosomes 1 , 3 and 5 (top arm) show overlap with previous studies for protein content in potato. Collectively the naive QTLs explained 12 to 17% of the phenotypic variance. The underlying alleles of the QTLs provided both positive and negative effects on the phenotype. Our work uncovers the complex genetic architecture of this trait and describes potential breeding strategies for improvement. As protein has emerged as a high-value component from industrial potato starch production, the dissection of the genetic architecture and subsequent improvement of this trait by breeding has great economic and environmental relevance. Electronic supplementary material The online version of this article (10.1007/s10681-018-2331-z) contains supplementary material, which is available to authorized users.

The Correlation between Soil Nutrient and Potato Quality in Loess Plateau of China Based on PLSR

“…Processing tubers with high protein content has economic significance for the potato starch industry because of the high economic value of these compounds [53]. The result indicated that genetic loci is an important factor that affects the potato tuber soluble protein content [54]. Therefore, in addition to providing adequate nutrients for potato growth, other agronomic measures, such as variety selection and plant protection, need to be considered.…”

Genome-wide association analysis in tetraploid potato reveals four QTLs for protein content

“…However, few realise that the potato crop also serves as an abundant source of plant protein (Jørgensen et al 2006). Although protein content in potato tubers is relatively low (0.32-1.63%) (Bárta et al 2012;Klaassen et al 2019;Ortiz-Medina 2006), protein yield per hectare (ha) is eminent due to the highyielding ability and high harvest-index of the potato crop that can reach up to 124 ton −1 ha (Kunkel and Campbell 1987). The potato starch industry processes potatoes to produce starch and by-products.…”

“…Consequently, innovative firms in the industry are keen to use protein-rich potato varieties and therefore high protein content has emerged as a key quality trait for breeders. However, breeding for protein content in potato is challenging due to the complex genetic basis underlying the trait (Klaassen et al 2019). To facilitate breeding for protein content in potato, improved comprehension of the inheritance, quantitative trait loci (QTLs) and relationships with other agronomical relevant traits are useful.…”

Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population

“…Trying to add more QTL into FEIM could rapidly lead the model to over-parameterization, since each QTL requires as much as six (for tetraploids), ten (for hexaploids) or 14 (for octoploids) parameters to be estimated. Furthermore, new rounds of permutation, based on a model with QTL, would need to be carried out in order to provide an updated LOD score threshold (Klaassen et al . 2019).…”

“…However, limitations in fitting multiple-QTL models have been presented mostly due to the possibility of over-parameterization or the lack of optimized algorithms for model selection (Mengist et al . 2018; Klaassen et al . 2019).…”