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Identification of starch candidate genes using SLAF-seq and BSA strategies and development of related SNP-CAPS markers in tetraploid potato.

ABSTRACT: Potato starch is an essential nutrient for humans and is widely used worldwide. Locating relevant genomic regions, mining stable genes and developing candidate gene markers can promote the breeding of new high-starch potato varieties. A total of 106 F1 individuals and their parents (YSP-4 × MIN-021) were used as test materials, from which 20 plants with high starch content and 20 with low starch content were selected to construct DNA pools for site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). A genomic region related to the starch traits was first identified in the 0-5.62 Mb of chromosome 2 in tetraploid potato. In this section, a total of 41 non-synonymous genes, which were considered as candidate genes related to the starch trait, were annotated through a basic local alignment search tool (BLAST) search of multiple databases. Six candidate genes for starch (PGSC0003DMG400017793, PGSC0003DMG400035245, PGSC0003DMG400036713, PGSC0003DMG400040452, PGSC0003DMG400006636 and PGSC0003DMG400044547) were further explored. In addition, cleaved amplified polymorphic sequence (CAPS) markers were developed based on single nucleotide polymorphism (SNP) sites associated with the starch candidate genes. SNP-CAPS markers chr2-CAPS6 and chr2-CAPS21 were successfully developed and validated with the F2 population and 24 tetraploid potato varieties (lines). Functional analysis and cloning of the candidate genes associated with potato starch will be performed in further research, and the SNP-CAPS markers chr2-CAPS6 and chr2-CAPS21 can be further used in marker-assisted selection breeding of tetraploid potato varieties with high starch content.

SUBMITTER: Li J

PROVIDER: S-EPMC8691606 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.

Project description:Key messageGenomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato. Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30-0.31 and 0.42-0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.

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Identification of starch candidate genes using SLAF-seq and BSA strategies and development of related SNP-CAPS markers in tetraploid potato.

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