Starch content differences between two sweet potato accessions are associated with specific changes in gene expression

Towards rapidly quantifying and visualizing starch content of sweet potato [Ipomoea batatas (L.) Lam] based on NIR spectral and image data fusion

This study aimed to achieve the rapid quantification and visualization of the starch content in sweet potato via near-infrared (NIR) spectral and image data fusion. The hyperspectral images of the sweet potato samples containing 900-1700 nm spectral information within every pixel were collected. The spectra were preprocessed, analyzed and the 18 informative wavelengths were finally extracted to relate to the measured starch content using the multiple linear regression (MLR) algorithm, producing a good quantitative prediction accuracy with a correlation coefficient of prediction (rP) of 0.970 and a root-mean-square error of prediction (RMSEP) of 0.874 g/100 g by an external validation using a set of dependent samples. The MLR model was further verified in terms of soundness and predictive validity via F-test and t-test, and then transferred to each pixel of the original two dimensional images with the help of a developed algorithm, generating color distribution maps to achieve the vivid visualization of the starch distribution. The study demonstrated that the fusion of the NIR spectral and image data provided a good strategy for the rapidly and nondestructively monitoring the starch content of sweet potato. This technique can be applied to industrial use in the future.

Development of a multicriteria decision-making model for evaluating hybrid offspring in the sweetpotato (Ipomoea batatas L.) breeding process

Sweetpotato variety breeding is always a long process. Screening of hybrid offspring is dominated by empirical judgment in this process. Data analysis and decision fatigue have been troubling breeders. In recent years, the low-efficiency screening mode has been unable to meet the requirements of sweetpotato germplasm innovation. Therefore, it is necessary to construct a high-efficiency method that can screen germplasms for different usages, for mining elite genotypes, and to create dedicated sweetpotato varieties. In this article, the multicriteria decision-making (MCDM) model was constructed based on six agronomic traits, including fresh root yield, vine length, vine diameter, branch number, root number and the spatial distribution of storage roots, and five quality traits, including dry matter content, marketable root yield, uniformity of roots, starch content and the edible quality score. Among these, the edible quality score was calculated by using fuzzy comprehensive evaluation to integrate the sensory scores of color, odor, sweetness, stickiness and fibrous taste. The MCDM model was compared with the traditional screening method via an evaluation in 25 sweetpotato materials. The interference of subjective factors on the evaluation results was significantly reduced. The MCDM model is more overall, more accurate and faster than the traditional screening method in the selection of elite sweetpotato materials. It could be programmed to serve the breeders in combination with the traditional screening method.

Split application enhances sweetpotato starch production by regulating the conversion of sucrose to starch under reduced nitrogen supply

Split application could improve nitrogen (N) uptake and increase sweetpotato yields under reduced N supply; however, little is known about how it affects the process of starch production in storage roots. An experiment was conducted to determine the effects of three N management strategies [conventional basal N management; 80% of the conventional N rate applied as a basal fertilizer; 80% of the conventional N rate equally split at transplanting and 35 days after transplanting] on starch accumulation, enzyme activity and genes expression in the conversion of sucrose to starch and the relationships among them. The results showed that, compared with conventional basal N management, split application decreased sucrose accumulation by 11.78%, but increased starch accumulation by 11.12% through improving the starch accumulation rate under reduced N supply. The ratio of sucrose synthetase to sucrose phosphate synthase, the enzymatic activity of ADP-glucose pyrophosphorylase (AGPP), starch synthase, and the expression of their corresponding genes were promoted by split application under reduced N supply and were positively correlated with starch accumulation rate. AGPP is the rate-limiting enzyme in starch synthesis in storage roots under different N management strategies. These results indicate that starch accumulation was enhanced by split application through regulating the activity and gene expression of key enzymes involved in the conversion of sucrose to starch under reduced N supply.

Genome-wide genetic diversity detection and population structure analysis in sweetpotato (Ipomoea batatas) using RAD-seq

Sweetpotato (Ipomoea batatas L.) is one of the most important food and grain-forage crops globally. It has been planted in >100 countries. Due to the complexity of the sweetpotato genome, its research is far behind other major food crops. At present, limited information about the sweetpotato genome is available. Thus, it is central to find an efficient approach for the investigation of sweetpotato genome. In this study, RAD-seq (Restriction site-associated DNA sequencing) was used to evaluate sweetpotato genetic structure diversity and to develop relevant SSR markers. The study yielded >128 Gb reliable sequence data from 81 sweetpotato accessions. By analyzing polymorphic tags from each accession, a total of 55,622 restriction-site associated DNA sequencing tags (RAD-seq) were found, containing 907,010 SNP. Genetic analysis divided 81 accessions into five major clusters based on their SNP genotype, which matches the results of genetic analysis and the genetic family tree. In addition, 18,320 SSRs loci were detected and 9336 SSR primer pairs were developed. Eighty-three primer pairs were amplified in different sweetpotato genotypes, 76 of which successfully amplified polymorphism bands. These results provide significant information about sweetpotato genome, which can be used to identify novel gene and to further develop the gene chip. And more significant, clustering results based on the SNP genotype provide an essential reference for breeders to match parent plants in breeding program. Additionally, SSR markers developed in this study will supply a wealth of markers for marker-assisted selection in sweetpotato breeding.

The wild sweetpotato (Ipomoea trifida) genome provides insights into storage root development

BACKGROUND

Sweetpotato (Ipomoea batatas (L.) Lam.) is the seventh most important crop in the world and is mainly cultivated for its underground storage root (SR). The genetic studies of this species have been hindered by a lack of high-quality reference sequence due to its complex genome structure. Diploid Ipomoea trifida is the closest relative and putative progenitor of sweetpotato, which is considered a model species for sweetpotato, including genetic, cytological, and physiological analyses.

RESULTS

Here, we generated the chromosome-scale genome sequence of SR-forming diploid I. trifida var. Y22 with high heterozygosity (2.20%). Although the chromosome-based synteny analysis revealed that the I. trifida shared conserved karyotype with Ipomoea nil after the separation, I. trifida had a much smaller genome than I. nil due to more efficient eliminations of LTR-retrotransposons and lack of species-specific amplification bursts of LTR-RTs. A comparison with four non-SR-forming species showed that the evolution of the beta-amylase gene family may be related to SR formation. We further investigated the relationship of the key gene BMY11 (with identity 47.12% to beta-amylase 1) with this important agronomic trait by both gene expression profiling and quantitative trait locus (QTL) mapping. And combining SR morphology and structure, gene expression profiling and qPCR results, we deduced that the products of the activity of BMY11 in splitting starch granules and be recycled to synthesize larger granules, contributing to starch accumulation and SR swelling. Moreover, we found the expression pattern of BMY11, sporamin proteins and the key genes involved in carbohydrate metabolism and stele lignification were similar to that of sweetpotato during the SR development.

CONCLUSIONS

We constructed the high-quality genome reference of the highly heterozygous I. trifida through a combined approach and this genome enables a better resolution of the genomics feature and genome evolutions of this species. Sweetpotato SR development genes can be identified in I. trifida and these genes perform similar functions and patterns, showed that the diploid I. trifida var. Y22 with typical SR could be considered an ideal model for the studies of sweetpotato SR development.