Comparative transcriptome analysis of two contrasting wolfberry genotypes during fruit development and ripening and characterization of the LrMYB1 transcription factor that regulates flavonoid biosynthesis

Transcriptional Response of Wolfberry to Infestation with the Endophytic Fusarium nematophilum Strain NQ8GII4

Fusarium nematophilum NQ8GII4 is an endophytic fungus isolated from the root of healthy wolfberry (Lycium barbarum). Previous studies have reported that NQ8GII4 could dwell in wolfberry roots and enhance the defense responses in wolfberry against root rot, which is caused by F. oxysporum. To further elucidate the molecular mechanism of wolfberry disease resistance induced by NQ8GII4, in the present study, we adopted RNA sequencing analysis to profile the transcriptome of wolfberry response to NQ8GII4 infestation over a time course of 3 and 7 days postinoculation. Gene ontology enrichment analysis revealed that differentially expressed genes (DEGs) were enriched in biological regulation, response to stimulus, signaling, detoxification, immune system process, transporter activity, electron carrier activity, transcription factor activity, nucleic acid binding transcription factor, and antioxidant activity. Through Kyoto Encyclopedia of Genes and Genomes analysis, it was found that many of these DEGs were enriched in pathways related to plant-pathogen interactions, hormone signal transduction, and the phenylpropanoid biosynthesis pathway in wolfberry. This result suggested that innate immunity, phytohormone signaling, and numerous phenylpropanoid compounds comprise a complex defense network in wolfberry. Chloroplast 50S ribosomal proteins were consistently located at the core position of the response in wolfberry following infestation with NQ8GII4 analyzed by the protein-protein interaction network. This study elucidated the molecular mechanism underlying the interaction between NQ8GII4 and wolfberry, clarified the wolfberry immune response network to endophytic fungi infestation, identified candidate resistance genes in wolfberry, and provided a fundamental date for subsequent work.

Mapping quantitative trait loci associated with self-(in)compatibility in goji berries (Lycium barbarum)

BACKGROUND

Goji (Lycium barbarum L.) is a perennial deciduous shrub widely distributed in arid and semiarid regions of Northwest China. It is highly valued for its medicinal and functional properties. Most goji varieties are naturally self-incompatible, posing challenges in breeding and cultivation. Self-incompatibility is a complex genetic trait, with ongoing debates regarding the number of self-incompatible loci. To date, no genetic mappings has been conducted for S loci or other loci related to self-incompatibility in goji.

RESULTS

We used genome resequencing to create a high-resolution map for detecting de novo single-nucleotide polymorphisms (SNP) in goji. We focused on 229 F1 individuals from self-compatible '13-19' and self-incompatible 'new 9' varieties. Subsequently, we conducted a quantitative trait locus (QTL) analysis on traits associated with self-compatibility in goji berries. The genetic map consisted of 249,327 SNPs distributed across 12 linkage groups (LGs), spanning a total distance of 1243.74 cM, with an average interval of 0.002 cM. Phenotypic data related to self-incompatibility, such as average fruit weight, fruit rate, compatibility index, and comparable compatibility index after self-pollination and geitonogamy, were collected for the years 2021-2022, as well as for an extra year representing the mean data from 2021 to 2022 (2021/22). A total of 43 significant QTL, corresponding to multiple traits were identified, accounting for more than 11% of the observed phenotypic variation. Notably, a specific QTL on chromosome 2 consistently appeared across different years, irrespective of the relationship between self-pollination and geitonogamy. Within the localization interval, 1180 genes were annotated, including Lba02g01102 (annotated as an S-RNase gene), which showed pistil-specific expression. Cloning of S-RNase genes revealed that the parents had two different S-RNase alleles, namely S1S11 and S2S8. S-genotype identification of the F1 population indicated segregation of the four S-alleles from the parents in the offspring, with the type of S-RNase gene significantly associated with self-compatibility.

CONCLUSIONS

In summary, our study provides valuable insights into the genetic mechanism underlying self-compatibility in goji berries. This highlights the importance of further positional cloning investigations and emphasizes the importance of integration of marker-assisted selection in goji breeding programs.

Comparative metabolomics combined with genome sequencing provides insights into novel wolfberry-specific metabolites and their formation mechanisms

Wolfberry (Lycium, of the family Solanaceae) has special nutritional benefits due to its valuable metabolites. Here, 16 wolfberry-specific metabolites were identified by comparing the metabolome of wolfberry with those of six species, including maize, rice, wheat, soybean, tomato and grape. The copy numbers of the riboflavin and phenyllactate degradation genes riboflavin kinase (RFK) and phenyllactate UDP-glycosyltransferase (UGT1) were lower in wolfberry than in other species, while the copy number of the phenyllactate synthesis gene hydroxyphenyl-pyruvate reductase (HPPR) was higher in wolfberry, suggesting that the copy number variation of these genes among species may be the main reason for the specific accumulation of riboflavin and phenyllactate in wolfberry. Moreover, the metabolome-based neighbor-joining tree revealed distinct clustering of monocots and dicots, suggesting that metabolites could reflect the evolutionary relationship among those species. Taken together, we identified 16 specific metabolites in wolfberry and provided new insight into the accumulation mechanism of species-specific metabolites at the genomic level.

Major quality regulation network of flavonoid synthesis governing the bioactivity of black wolfberry

Black wolfberry (Lycium ruthenicum Murr.) contains various bioactive metabolites represented by flavonoids, which are quite different among production regions. However, the underlying regulation mechanism of flavonoid biosynthesis governing the bioactivity of black wolfberry remains unclear. Presently, we compared the bioactivity of black wolfberry from five production regions. Multi-omics were performed to construct the regulation network associated with the fruit bioactivity. The detailed regulation mechanisms were identified using genetic and molecular methods. Typically, Qinghai (QH) fruit exhibited higher antioxidant and anti-inflammatory activities. The higher medicinal activity of QH fruit was closely associated with the accumulation of eight flavonoids, especially Kaempferol-3-O-rutinoside (K3R) and Quercetin-3-O-rutinoside (rutin). Flavonoid biosynthesis was found to be more active in QH fruit, and the upregulation of LrFLS, LrCHS, LrF3H and LrCYP75B1 caused the accumulation of K3R and rutin, leading to high medicinal bioactivities of black wolfberry. Importantly, transcription factor LrMYB94 was found to regulate LrFLS, LrCHS and LrF3H, while LrWRKY32 directly triggered LrCYP75B1 expression. Moreover, LrMYB94 interacted with LrWRKY32 to promote LrWRKY32-regulated LrCYP75B1 expression and rutin synthesis in black wolfberry. Transgenic black wolfberry overexpressing LrMYB94/LrWRKY32 contained higher levels of K3R and rutin, and exhibited high medicinal bioactivities. Importantly, the LrMYB94/LrWRKY32-regulated flavonoid biosynthesis was light-responsive, showing the importance of light intensity for the medicinal quality of black wolfberry. Overall, our results elucidated the regulation mechanisms of K3R and rutin synthesis, providing the basis for the genetic breeding of high-quality black wolfberry.

Integrative transcriptome and metabolome analysis reveals the discrepancy in the accumulation of active ingredients between Lycium barbarum cultivars

MAIN CONCLUSION

The combined analysis of transcriptome and metabolome provided molecular insight into the dynamics of multiple active ingredients biosynthesis and accumulation across different cultivars of Lycium barbarum. Lycium barbarum L. has a high concentration of active ingredients and is well known in traditional Chinese herbal medicine for its therapeutic properties. However, there are many Lycium barbarum cultivars, and the content of active components varies, resulting in inconsistent quality between Lycium barbarum cultivars. At present, few research has been conducted to reveal the difference in active ingredient content among different cultivars of Lycium barbarum at the molecular level. Therefore, the transcriptome of 'Ningqi No.1' and 'Qixin No.1' during the three development stages (G, T, and M) was constructed in this study. A total of 797,570,278 clean reads were obtained. Between the two types of wolfberries, a total of 469, 2394, and 1531 differentially expressed genes (DEGs) were obtained in the 'G1 vs. G10,' 'T1 vs. T10,' and 'M1 vs. M10,' respectively, and were annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology identifiers. Using these transcriptome data, most DEGs related to the metabolism of the active ingredients in 'Ningqi No.1' and 'Qixin No.1' were identified. Moreover, a widely targeted metabolome analysis of the metabolites of 'Ningqi 1' and 'Qixin 1' fruits at the maturity stage revealed 1,135 differentially expressed metabolites (DEMs) in 'M1 vs. M10,' and many DEMs were associated with active ingredients such as flavonoids, alkaloids, terpenoids, and so on. We further quantified the flavonoid, lignin, and carotenoid contents of the two Lycium barbarum cultivars during the three developmental stages. The present outcome provided molecular insight into the dynamics of multiple active ingredients biosynthesis and accumulation across different cultivars of Lycium barbarum, which would provide the basic data for the formation of Lycium barbarum fruit quality and the breeding of outstanding strains.

Genome-wide analysis of the TIFY family in Lycium and the negative regulation of stomatal development by LrJAZ2 gene

Stomata are ports that facilitate gas and water vapor exchange during plant photosynthesis and transpiration. Stomatal development is strictly regulated by endogenous hormone. Jasmonate, an important signal that modulates multiple physiological processes in plants, has been found to negatively regulate stomatal development in Arabidopsis thaliana, yet the molecular mechanisms underlying stomata development signaling remain to be understood. Jasmonate ZIM-domain (JAZ) proteins are the members of TIFY family and the key component of JA signaling pathway. Its function in stomatal development is unclear to data. Here, we screened out 24 TIFY family members against the genome of Lycium, and identified a JAZ member by combination analyses of evolutionary tree, cis-elements in promoter and gene expression patterns. Overexpression of this gene (LrJAZ2) in Lycium ruthenicum and Arabidopsis thaliana indicated LrJAZ2 negatively regulates stomatal development. Microscopic observations revealed that overexpression of LrJAZ2 negatively regulated stomatal development by decreasing stomatal density and index, which may lead to lower leaf transpiration rates. Transcriptome data indicated the overexpression of LrJAZ2 up-regulated the stomatal related genes such as LrERL2, LrPYL4, and down-regulated the LrSPCH. Collectively, our study found that LrJAZ2 is a key gene in stomatal development regulation in L. ruthenicum and provided new insights into the regulation of stomatal development.

Integrated transcriptome and metabolome provide insight into flavonoid variation in goji berries (Lycium barbarum L.) from different areas in China

Goji berries (Lycium barbarum L.) were rich in flavonoids, showing high nutritional and medicinal value. However, a thorough evaluation and comparison of the flavonoids in goji berries from various regions and the possible biological regulation pathways with differences are scanty. Here, we investigated the flavonoid metabolites and gene expression levels of goji berries from three major production areas in China using transcriptomics sequencing and metabolomics. The total flavonoid content and total polyphenol content of goji berry in Ningxia (57.87 μg/g and 183.41 μg/g, respectively) were higher than in Qinghai (50.77 μg/g and 156.81 μg/g) and Gansu (47.86 μg/g and 111.17 μg/g). We identified the 105 differentially accumulated flavonoids (DAFs) and 1858 differentially expressed genes (DEGs) from the goji berries in three habitats. Interestingly, gossypetin-3-O-rutinoside and isorhamnetin were significantly expressed between Ningxia and Qinghai berries. The chalcone isomerase (CHI), chalcone synthase (CHS), and flavonol synthase (FLS) genes also played key roles in the regulation of flavonoid synthesis. In addition, MYB1 positively regulated the expression of quercetin-3-O-glucoside, quercetin-7-O-glucoside and isohyperoside. As a result, we speculated that CHI, CHS, FLS genes, and related transcription factors jointly controlled the variation of flavone accumulation in goji berries. These findings may provide a new perspective for understanding the accumulation and molecular mechanisms of goji flavonoids.

Transcriptional regulation mechanism of flavonoids biosynthesis gene during fruit development in astragalus membranaceus

Astragalus membranaceus, as an important medicinal plant, are an excellent source of flavonoids. Flavonoid compounds in A. membranaceus have been widely used in medicine and supplement, but known of the molecular mechanism of flavonoid biosynthesis is still very few. Here, we analyzed the association between flavonoid content and gene expression pattern during six different fruit developmental stages. Sixteen gene expression trends were significantly identified, involving 8,218 genes. The gene expression trend in profile 0 was positively correlated with flavonoid content, while the gene expression trend in profile 79 was negatively correlated with flavonoid content at six developmental stages. The expression level of genes involved in the general phenylpropane pathway was higher than that of genes involved in the flavonoid biosynthesis pathway. A total of 37 genes involved in flavonoid synthesis were identified in A. membranaceus. The expression pattern of flavonoid-related genes was highly correlated with flavonoid content. Our study deepened the understanding of the flavonoid synthesis mechanism and provided useful resources for future studies on the high flavonoid molecular breeding of A. membranaceus.

Comparative transcriptome analyses of different Salvia miltiorrhiza varieties during the accumulation of tanshinones

Salvia miltiorrhiza (Labiatae) is an important medicinal plant in traditional Chinese medicine. Tanshinones are one of the main active components of S. miltiorrhiza. It has been found that the intraspecific variation of S. miltiorrhiza is relatively large and the content of tanshinones in its roots of different varieties is also relatively different. To investigate the molecular mechanisms that responsible for the differences among these varieties, the tanshinones content was determined and comparative transcriptomics analysis was carried out during the tanshinones accumulation stage. A total of 52,216 unigenes were obtained from the transcriptome by RNA sequencing among which 23,369 genes were differentially expressed among different varieties, and 2,016 genes including 18 diterpenoid biosynthesis-related genes were differentially expressed during the tanshinones accumulation stage. Functional categorization of the differentially expressed genes (DEGs) among these varieties revealed that the pathway related to photosynthesis, oxidative phosphorylation, secondary metabolite biosynthesis, diterpenoid biosynthesis, terpenoid backbone biosynthesis, sesquiterpenoid and triterpenoid biosynthesis are the most differentially regulated processes in these varieties. The six tanshinone components in these varieties showed different dynamic changes in tanshinone accumulation stage. In addition, combined with the analysis of the dynamic changes, 277 DEGs (including one dehydrogenase, three CYP450 and 24 transcription factors belonging to 12 transcription factor families) related to the accumulation of tanshinones components were obtained. Furthermore, the KEGG pathway enrichment analysis of these 277 DEGs suggested that there might be an interconnection between the primary metabolic processes, signaling processes and the accumulation of tanshinones components. This study expands the vision of intraspecific variation and gene regulation mechanism of secondary metabolite biosynthesis pathways in medicinal plants from the “omics” perspective.

Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening

BACKGROUND

Fruit ripening in Prunus persica melting varieties involves several physiological changes that have a direct impact on the fruit organoleptic quality and storage potential. By studying the proteomic differences between the mesocarp of mature and ripe fruit, it would be possible to highlight critical molecular processes involved in the fruit ripening.

RESULTS

To accomplish this goal, the proteome from mature and ripe fruit was assessed from the variety O'Henry through shotgun proteomics using 1D-gel (PAGE-SDS) as fractionation method followed by LC/MS-MS analysis. Data from the 131,435 spectra could be matched to 2740 proteins, using the peach genome reference v1. After data pre-treatment, 1663 proteins could be used for comparison with datasets assessed using transcriptomic approaches and for quantitative protein accumulation analysis. Close to 26% of the genes that code for the proteins assessed displayed higher expression at ripe fruit compared to other fruit developmental stages, based on published transcriptomic data. Differential accumulation analysis between mature and ripe fruit revealed that 15% of the proteins identified were modulated by the ripening process, with glycogen and isocitrate metabolism, and protein localization overrepresented in mature fruit, as well as cell wall modification in ripe fruit. Potential biomarkers for the ripening process, due to their differential accumulation and gene expression pattern, included a pectin methylesterase inhibitor, a gibbellerin 2-beta-dioxygenase, an omega-6 fatty acid desaturase, a homeobox-leucine zipper protein and an ACC oxidase. Transcription factors enriched in NAC and Myb protein domains would target preferentially the genes encoding proteins more abundant in mature and ripe fruit, respectively.

CONCLUSIONS

Shotgun proteomics is an unbiased approach to get deeper into the proteome allowing to detect differences in protein abundance between samples. This technique provided a resolution so that individual gene products could be identified. Many proteins likely involved in cell wall and sugar metabolism, aroma and color, change their abundance during the transition from mature to ripe fruit.

Floral transcriptomes reveal gene networks in pineapple floral growth and fruit development

Proper flower development is essential for sexual reproductive success and the setting of fruits and seeds. The availability of a high quality genome sequence for pineapple makes it an excellent model for studying fruit and floral organ development. In this study, we sequenced 27 different pineapple floral samples and integrated nine published RNA-seq datasets to generate tissue- and stage-specific transcriptomic profiles. Pairwise comparisons and weighted gene co-expression network analysis successfully identified ovule-, stamen-, petal- and fruit-specific modules as well as hub genes involved in ovule, fruit and petal development. In situ hybridization confirmed the enriched expression of six genes in developing ovules and stamens. Mutant characterization and complementation analysis revealed the important role of the subtilase gene AcSBT1.8 in petal development. This work provides an important genomic resource for functional analysis of pineapple floral organ growth and fruit development and sheds light on molecular networks underlying pineapple reproductive organ growth.

Wang et al. perform RNA-Seq on pineapple floral samples and also use previously published RNA-Seq datasets to generate tissue- and stage-specific transcriptomic profiles. The authors use weighted gene co-expression network analysis to identify gene networks, bringing insight to underlying pineapple reproductive organ growth.