Integrated Untargeted Metabolome, Full-Length Sequencing and Transcriptome Analyses Reveal the Mechanism of Flavonoid Biosynthesis in Blueberry (Vaccinium spp.) Fruit.

As a highly economic berry fruit crop, blueberry is enjoyed by most people and has various potential health benefits, many of which are attributed to the relatively high concentrations of flavonoids. To obtain more accurate and comprehensive transcripts, the full-length transcriptome of half-highbush blueberry (Vaccinium corymbosum/angustifolium cultivar Northland) obtained using single molecule real-time and next-generation sequencing technologies was reported for the first time. Overall, 147,569 consensus transcripts (average length, 2738 bp; N50, 3176 bp) were obtained. After quality control steps, 63,425 high-quality isoforms were obtained and 5030 novel genes, 3002 long non-coding RNAs, 3946 transcription factor genes (TFs), 30,540 alternative splicing events, and 2285 fusion gene pairs were identified. To better explore the molecular mechanism of flavonoid biosynthesis in mature blueberry fruit, an integrative analysis of the metabolome and transcriptome was performed on the exocarp, sarcocarp, and seed. A relatively complete biosynthesis pathway map of phenylpropanoids, flavonoids, and proanthocyanins in blueberry was constructed. The results of the joint analysis showed that the 228 functional genes and 42 TFs regulated 78 differentially expressed metabolites within the biosynthesis pathway of phenylpropanoids/flavonoids. O2PLS analysis results showed that the key metabolites differentially accumulated in blueberry fruit tissues were albireodelphin, delphinidin 3,5-diglucoside, delphinidin 3-O-rutinoside, and delphinidin 3-O-sophoroside, and 10 structural genes (4 Vc4CLs, 3 VcBZ1s, 1 VcUGT75C1, 1 VcAT, and 1 VcUGAT), 4 transporter genes (1 VcGSTF and 3 VcMATEs), and 10 TFs (1 VcMYB, 2 VcbHLHs, 4 VcWD40s, and 3 VcNACs) exhibited strong correlations with 4 delphinidin glycosides. These findings provide insights into the molecular mechanisms of flavonoid biosynthesis and accumulation in blueberry fruit.

Classification of rice leaf blast severity using hyperspectral imaging.

Rice leaf blast is prevalent worldwide and a serious threat to rice yield and quality. Hyperspectral imaging is an emerging technology used in plant disease research. In this study, we calculated the standard deviation (STD) of the spectral reflectance of whole rice leaves and constructed support vector machine (SVM) and probabilistic neural network (PNN) models to classify the degree of rice leaf blast at different growth stages. Average accuracies at jointing, booting and heading stages under the full-spectrum-based SVM model were 88.89%, 85.26%, and 87.32%, respectively, versus 80%, 83.16%, and 83.41% under the PNN model. Average accuracies at jointing, booting and heading stages under the STD-based SVM model were 97.78%, 92.63%, and 92.20%, respectively, versus 88.89%, 91.58%, and 92.20% under the PNN model. The STD of the spectral reflectance of the whole leaf differed not only within samples with different disease grades, but also among those at the same disease level. Compared with raw spectral reflectance data, STDs performed better in assessing rice leaf blast severity.

Hyperspectral imaging-based classification of rice leaf blast severity over multiple growth stages.

BACKGROUND: Rice blast, which is prevalent worldwide, represents a serious threat to harvested crop yield and quality. Hyperspectral imaging, an emerging technology used in plant disease research, is a stable, repeatable method for disease grading. Current methods for assessing disease severity have mostly focused on individual growth stages rather than multiple ones. In this study, the spectral reflectance ratio (SRR) of whole leaves were calculated, the sensitive wave bands were selected using the successive projections algorithm (SPA) and the support vector machine (SVM) models were constructed to assess rice leaf blast severity over multiple growth stages. RESULTS: The average accuracy, micro F1 values, and macro F1 values of the full-spectrum-based SVM model were respectively 94.75%, 0.869, and 0.883 in 2019; 92.92%, 0.823, and 0.808 in 2021; and 88.09%, 0.702, and 0.757 under the 2019-2021 combined model. The SRR-SVM model could be used to evaluate rice leaf blast disease during multiple growth stages and had good generalizability. CONCLUSIONS: The proposed SRR data analysis method is able to eliminate differences among individuals to some extent, thus allowing for its application to assess rice leaf blast severity over multiple growth stages. Our approach, which can supplement single-stage disease-degree classification, provides a possible direction for future research on the assessment of plant disease severity during multiple growth stages.

Diversity of fungal assemblages in rhizosphere and endosphere of blueberry (Vaccinium spp.) under field conditions revealed by culturing and culture-independent molecular methods.

Mycorrhizae are important to plants in improving nutrient absorption and stress resistance. To study mycorrhizal fungal diversity in blueberry, we combined culture method and culture-independent molecular method to analyze the root endosphere and rhizosphere fungi in three different cultivars. We obtained 212 isolates with a culture method and classified them into 40 types according to their morphological characteristics. Then, we amplified the internal transcribed spacer sequence and found rich species diversity. With high-throughput sequencing, 561 operational taxonomic units (OTUs) were annotated based on a 97% similarity level cutoff. The alpha diversity index revealed that the fungal abundance and diversity in the rhizosphere were higher than those in the endosphere. The dominant phyla were Ascomycota and Basidiomycota and the dominant genus was Oidiodendron. We also constructed the plant-fungus symbiotic system by inoculating in vitro stock shoots, which lays a theoretical foundation for further research to develop and utilize the dominant mycorrhizal fungi of blueberry.

Development of Novel Polymorphic EST-SSR Markers from the Cranberry Fruit Transcriptome.

BACKGROUND: Cranberry (Vaccinium macrocarpon Ait.) has high developmental prospects and great research value. Cranberry has a narrow genetic base, however, its morphological characteristics are not easily distinguishable. Besides, traditional breeding methods are limited, and breeding progress on cranberry cultivars has been slow. OBJECTIVE: The objective of this study was to assess polymorphic EST-SSR markers developed from a cranberry fruit transcriptomic sequencing library to provide candidate EST-SSR sequences for future research on stress resistance breeding of cranberry. MATERIALS AND METHODS: Thirteen cranberry accessions were used for EST-SSR analysis, and 16 accessions of other Vaccinium species were used to test primer transferability. Genomic DNA was extracted from young leaves of 6-year-old cranberry plants and subjected to PCR amplification. A binary matrix was established and analyzed in NTSYS-pc v.2.10e for calculation of the genetic similarity of cranberry cultivars and construction of a cluster dendrogram. RESULTS: A total of 47 stress-resistance-related primer pairs were designed, of which 7 pairs showed polymorphism. The average number of effective alleles was 1.844, and the average expected heterozygosity was 0.455. The average transfer rate was 63.39%. Genetic similarity coefficients ranged from 0.28 to 1.00, with an average of 0.76. UPGMA clustering divided the 13 cranberry accessions into four groups at a genetic similarity of 0.74. CONCLUSIONS: The seven polymorphic EST-SSR markers were able to reveal genetic relationships among 13 cranberry accessions and can be used for future research on stress resistance breeding of cranberry.

Ultrasound-assisted fast encapsulation of metal microparticles in SiO2 via an interface-confined sol-gel method.

Although the traditional Stoˇber process-based methods are widely used for encapsulation of metal nanoparticles in SiO2, these time-consuming methods are not effective for coating metal microparticles with a uniform SiO2 layer of desired thickness. Herein, an ultrasound-assisted, interface-confined sol-gel method is proposed for fast encapsulation of metal microparticles in SiO2, and the encapsulation of Sn microparticles is chosen as an example to illustrate its feasibility. The proposed method involves covering metal microparticles with liquid films that contain water, alcohol, surfactant (Span-80) and catalyst (NH4F) and then ultrasonically dispersing these particles into cyclohexane, where tetraethylorthosilicate (TEOS) is added. To ensure the hydrolysis-condensation reactions of TEOS occurring at the particle-cyclohexane interface so that the formed SiO2 is coated on the particles, the microparticles should be well dispersed into cyclohexane with the liquid films being not broken away from their surfaces. It is found that the assistance of probe sonication and the addition of surfactant are crucial to achievement of a good dispersion of metal microparticles in cyclohexane. And using high-viscosity alcohol (namely glycerol), controlling the volume ratio of water to alcohol and the amount of water, and choosing a suitable ultrasonic power are essential for preventing the formation of free SiO2 (namely SiO2 that is not coated on the particles), which is a result that the liquid films escape from the particle surfaces under ultrasonic cavitation. Our results have also revealed that the thickness of SiO2 layer can be adjusted by changing the reaction time or the total amount of water. In particular, the thickness of SiO2 layer can be easily raised by simply repeating the encapsulation procedure. Compared with the traditional Stoˇber process-based methods, the proposed method is time-saving (reaction time: about 30 min vs. more than 12 h) and extremely effective for coating microparticles with a continuous, uniform SiO2 layer of desired thickness.

Cloning and functional analysis of the VcCXIP4 and VcYSL6 genes as Cd-regulating genes in blueberry.

Blueberries (Vaccinium ssp.) show relatively high resistance to pollution and have been reported to successfully colonize acid and heavy metal-contaminated soils. Blueberries were subjected to cadmium stress using a simulated pot-culture method. The intact CDS regions of VcCXIP4 and VcYSL6 were obtained, VcCXIP4 was located in the nucleus, while VcYSL6 was located in the chloroplast. Both genes were constructed into a modified plant expression vector pCambia1301 for tobacco transformation with agrobacterium infection methods. Results showed that VcCXIP4 did not function alone in regulating cadmium (Cd) transport. Cd content of Cd in the leaves of VcYSL6 transgenic tobacco by 15.57% under high Cd concentration. Both, VcCXIP4 and VcYSL6 genes were up-regulated under Cd stress. Blueberry primarily accumulated excess Cd in the root, but Cd content in the fruit was almost independent of Cd content in the soil. Further, the effect of soil Cd content on fruit Cd content was not significant. VcCXIP4 is likely to interact with other proteins to regulate excess Cd in blueberry, while VcYSL6 is a Cd transporter required for excess Cd detoxification in blueberry.

De novo sequencing and analysis of the cranberry fruit transcriptome to identify putative genes involved in flavonoid biosynthesis, transport and regulation.

BACKGROUND: Cranberries (Vaccinium macrocarpon Ait.), renowned for their excellent health benefits, are an important berry crop. Here, we performed transcriptome sequencing of one cranberry cultivar, from fruits at two different developmental stages, on the Illumina HiSeq 2000 platform. Our main goals were to identify putative genes for major metabolic pathways of bioactive compounds and compare the expression patterns between white fruit (W) and red fruit (R) in cranberry. RESULTS: In this study, two cDNA libraries of W and R were constructed. Approximately 119 million raw sequencing reads were generated and assembled de novo, yielding 57,331 high quality unigenes with an average length of 739 bp. Using BLASTx, 38,460 unigenes were identified as putative homologs of annotated sequences in public protein databases, including NCBI NR, NT, Swiss-Prot, KEGG, COG and GO. Of these, 21,898 unigenes mapped to 128 KEGG pathways, with the metabolic pathways, secondary metabolites, glycerophospholipid metabolism, ether lipid metabolism, starch and sucrose metabolism, purine metabolism, and pyrimidine metabolism being well represented. Among them, many candidate genes were involved in flavonoid biosynthesis, transport and regulation. Furthermore, digital gene expression (DEG) analysis identified 3,257 unigenes that were differentially expressed between the two fruit developmental stages. In addition, 14,473 simple sequence repeats (SSRs) were detected. CONCLUSIONS: Our results present comprehensive gene expression information about the cranberry fruit transcriptome that could facilitate our understanding of the molecular mechanisms of fruit development in cranberries. Although it will be necessary to validate the functions carried out by these genes, these results could be used to improve the quality of breeding programs for the cranberry and related species.