Identification of quantitative trait loci associated with flowering time in perilla using genotyping-by-sequencing

Improving the Traits of Perilla frutescens (L.) Britt Using Gene Editing Technology

Plant breeding has evolved significantly over time with the development of transformation and genome editing techniques. These new strategies help to improve desirable traits in plants. Perilla is a native oil crop grown in Korea. The leaves contain many secondary metabolites related to whitening, aging, antioxidants, and immunity, including rosmarinic acid, vitamin E, luteolin, anthocyanins, and beta-carotene. They are used as healthy and functional food ingredients. It is an industrially valuable cosmetics crop. In addition, perilla seeds are rich in polyunsaturated fatty acids, such as α-linolenic acid and linoleic acid. They are known to be effective in improving neutral lipids in the blood, improving blood circulation, and preventing dementia and cardiovascular diseases, making them excellent crops whose value can be increased through improved traits. This research will also benefit perilla seeds, which can increase their stock through various methods, such as the increased production of functional substances and improved productivity. Recently, significant attention has been paid to trait improvement research involving gene-editing technology. Among these strategies, CRISPR/Cas9 is highly adaptable, enabling accurate and efficient genome editing, targeted mutagenesis, gene knockouts, and the regulation of gene transcription. CRISPR/Cas9-based genome editing has enormous potential for improving perilla; however, the regulation of genome editing is still at an early stage. Therefore, this review summarizes the enhancement of perilla traits using genome editing technology and outlines future directions.

Assessing the Potential for Genome-Assisted Breeding in Red Perilla Using Quantitative Trait Locus Analysis and Genomic Prediction

Red perilla is an important medicinal plant used in Kampo medicine. The development of elite varieties of this species is urgently required. Medicinal compounds are generally considered target traits in medicinal plant breeding; however, selection based on compound phenotypes (i.e., conventional selection) is expensive and time consuming. Here, we propose genomic selection (GS) and marker-assisted selection (MAS), which use marker information for selection, as suitable selection methods for medicinal plants, and we evaluate the effectiveness of these methods in perilla breeding. Three breeding populations generated from crosses between one red and three green perilla genotypes were used to elucidate the genetic mechanisms underlying the production of major medicinal compounds using quantitative trait locus analysis and evaluating the accuracy of genomic prediction (GP). We found that GP had a sufficiently high accuracy for all traits, confirming that GS is an effective method for perilla breeding. Moreover, the three populations showed varying degrees of segregation, suggesting that using these populations in breeding may simultaneously enhance multiple target traits. This study contributes to research on the genetic mechanisms of the major medicinal compounds of red perilla, as well as the breeding efficiency of this medicinal plant.

Development of an SNP marker set for marker-assisted backcrossing using genotyping-by-sequencing in tetraploid perilla

High-quality molecular markers are essential for marker-assisted selection to accelerate breeding progress. Compared with diploid species, recently diverged polyploid crop species tend to have highly similar homeologous subgenomes, which is expected to limit the development of broadly applicable locus-specific single-nucleotide polymorphism (SNP) assays. Furthermore, it is particularly challenging to make genome-wide marker sets for species that lack a reference genome. Here, we report the development of a genome-wide set of kompetitive allele specific PCR (KASP) markers for marker-assisted recurrent selection (MARS) in the tetraploid minor crop perilla. To find locus-specific SNP markers across the perilla genome, we used genotyping-by-sequencing (GBS) to construct linkage maps of two F2 populations. The two resulting high-resolution linkage maps comprised 2326 and 2454 SNP markers that spanned a total genetic distance of 2133 cM across 16 linkage groups and 2169 cM across 21 linkage groups, respectively. We then obtained a final genetic map consisting of 22 linkage groups with 1123 common markers from the two genetic maps. We selected 96 genome-wide markers for MARS and confirmed the accuracy of markers in the two F2 populations using a high-throughput Fluidigm system. We confirmed that 91.8% of the SNP genotyping results from the Fluidigm assay were the same as the results obtained through GBS. These results provide a foundation for marker-assisted backcrossing and the development of new varieties of perilla.

Genome-wide association study of 23 flowering phenology traits and 4 floral agronomic traits in tree peony (Paeonia section Moutan DC.) reveals five genes known to regulate flowering time

Tree peony is a unique traditional flower in China, with large, fragrant, and colorful flowers. However, a relatively short and concentrated flowering period limits the applications and production of tree peony. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of flowering phenology traits and ornamental phenotypes in tree peony. A diverse panel of 451 tree peony accessions was phenotyped for 23 flowering phenology traits and 4 floral agronomic traits over 3 years. Genotyping by sequencing (GBS) was used to obtain a large number of genome-wide single-nucleotide polymorphisms (SNPs) (107 050) for the panel genotypes, and 1047 candidate genes were identified by association mapping. Eighty-two related genes were observed during at least 2 years for flowering, and seven SNPs repeatedly identified for multiple flowering phenology traits over multiple years were highly significantly associated with five genes known to regulate flowering time. We validated the temporal expression profiles of these candidate genes and highlighted their possible roles in the regulation of flower bud differentiation and flowering time in tree peony. This study shows that GWAS based on GBS can be used to identify the genetic determinants of complex traits in tree peony. The results expand our understanding of flowering time control in perennial woody plants. Identification of markers closely related to these flowering phenology traits can be used in tree peony breeding programs for important agronomic traits.

Genome-edited HEADING DATE 3a knockout enhances leaf production in Perilla frutescens

Environmental cues regulate the transition of many plants from vegetative to flowering development. Day length, or photoperiod, is one cue that synchronizes flowering by changing seasons. Consequently, the molecular mechanism of flowering control is prominent in Arabidopsis and rice, where essential genes like FLOWERING LOCUS T (FT) homolog, HEADING DATE 3a (Hd3a), have been connected to flowering regulation. Perilla is a nutrient-rich leaf vegetable, and the flowering mechanism remains largely elusive. We identified flowering-related genes under short-day conditions using RNA sequencing to develop an enhanced leaf production trait using the flowering mechanism in the perilla. Initially, an Hd3a-like gene was cloned from the perilla and defined as PfHd3a. Furthermore, PfHd3a is highly rhythmically expressed in mature leaves under short-day and long-day conditions. Ectopic expression of PfHd3a in Atft-1 mutant plants has been shown to complement Arabidopsis FT function, resulting in early flowering. In addition, our genetic approaches revealed that overexpression of PfHd3a in perilla caused early flowering. In contrast, the CRISPR/Cas9 generated PfHd3a-mutant perilla showed significantly late flowering, resulting in approximately 50% leaf production enhancement compared to the control. Our results suggest that PfHd3a plays a vital role in regulating flowering in the perilla and is a potential target for molecular breeding in the perilla.

QTL Mapping of Resistance to Bacterial Wilt in Pepper Plants (Capsicum annuum) Using Genotyping-by-Sequencing (GBS)

Bacterial wilt (BW) disease, which is caused by Ralstonia solanacearum, is one globally prevalent plant disease leading to significant losses of crop production and yield with the involvement of a diverse variety of monocot and dicot host plants. In particular, the BW of the soil-borne disease seriously influences solanaceous crops, including peppers (sweet and chili peppers), paprika, tomatoes, potatoes, and eggplants. Recent studies have explored genetic regions that are associated with BW resistance for pepper crops. However, owing to the complexity of BW resistance, the identification of the genomic regions controlling BW resistance is poorly understood and still remains to be unraveled in the pepper cultivars. In this study, we performed the quantitative trait loci (QTL) analysis to identify genomic loci and alleles, which play a critical role in the resistance to BW in pepper plants. The disease symptoms and resistance levels for BW were assessed by inoculation with R. solanacearum. Genotyping-by-sequencing (GBS) was utilized in 94 F2 segregating populations originated from a cross between a resistant line, KC352, and a susceptible line, 14F6002-14. A total of 628,437 single-nucleotide polymorphism (SNP) was obtained, and a pepper genetic linkage map was constructed with putative 1550 SNP markers via the filtering criteria. The linkage map exhibited 16 linkage groups (LG) with a total linkage distance of 828.449 cM. Notably, QTL analysis with CIM (composite interval mapping) method uncovered pBWR-1 QTL underlying on chromosome 01 and explained 20.13 to 25.16% by R2 (proportion of explained phenotyphic variance by the QTL) values. These results will be valuable for developing SNP markers associated with BW-resistant QTLs as well as for developing elite BW-resistant cultivars in pepper breeding programs.

Bulk segregant analysis identifies SSR markers associated with leaf- and seed-related traits in Perilla crop (Perilla frutescens L.)

BACKGROUND

Bulk segregant analysis (BSA) is another method of identifying significant molecular markers linked to the target gene or region for specific traits. BSA is easier and less expensive than other methods; it does not require genetic map construction and needs fewer markers than the number needed to construct a genetic map for QTL mapping.

OBJECTIVES

The purpose of our study was to identify simple sequence repeat (SSR) markers linked with leaf- and seed-related traits in Perilla crop, and to allow the selection of better accessions in Perilla breeding programs with marker-assisted selection (MAS).

METHODS

The genotypes of the 25 SSR markers and phenotypic data for the eight qualitative traits were used to confirm significant marker-trait associations (SMTAs) using TASSEL software. To detect SSR markers associated with leaf color, the 16 individuals of the F₃ population were divided into three bulk groups based on the colors of the surface and reverse sides of the leaf, respectively: six in the green/green group, five in the green/purple group and five in the purple/purple group.

RESULTS

This study detected 18 significant marker-trait associations (SMTAs) involving 12 SSR markers associated with six agronomic traits. The SSR markers KNUPF15, KNUPF21, KNUPF29, and KNUPF60 were associated with leaf surface color, and KNUPF11, KNUPF15, KNUPF21, and KNUPF60 were associated with leaf reverse side color. In addition, five SSR markers were associated with seed-related traits. KNUPF11 and KNUPF29 were associated with seed coat color, while KNUPF29 was associated with seed size. KNUPF12, KNUPF16, and KNUPF42 were associated with seed hardness. To verify the selected significant SSR markers associated with leaf color and seed-related traits, a UPGMA dendrogram for 11 individuals in the F₃ population, which formed two bulk groups consisting of 6 green/green and 5 purple/purple individuals, was constructed using six SSR marker-related LC and RLC traits.

CONCLUSION

These results are very important for understanding the characteristics of Perilla leaves and seeds; they may also support opportunities to effectively preserve and utilize existing accessions and to allow Perilla breeders to improve crop quality by mean of MAS.