Metabolomics and transcriptomics provide insights into the flavonoid biosynthesis pathway in the roots of developing Aster tataricus.

Aster tataricus (L.) is an important medicinal plant in China. Its roots are rich in flavonoids, the main medicinal components. However, the molecular basis of flavonoid biosynthesis in the roots of A. tataricus remains unclear. In this study, the content of total flavonoid of A. tataricus roots at different developmental stages was measured first, and the results showed that the content of total flavonoid gradually decreased from September to November, which may be caused by the stagnation of A. tataricus growth due to the decrease in temperature after September. Then, an integrated analysis of transcriptome and metabolome was conducted on five developing stages of A. tataricus roots to identify flavonoid compositions and potential genes involved in flavonoid biosynthesis. A total of 80 flavonoid metabolites, of which 75% were flavonols and flavonoids, were identified in metabolomic analyses, among which isorhamnetin, kaempferol, quercetin, and myricetin were the main skeletons of these flavonoids. Cluster analysis divided these 80 flavonoids into 3 clusters. The compounds in cluster I mainly accumulated in S1, S3, and S5. In cluster II, the relative content of the flavonoid metabolites showed an upward trend from S2 to S4. In cluster III, the flavonoids decreased from S1 to S5. A total of 129 structural genes, including 43 PAL, 23 4CL, 9 C4H, 4 CHS, 18 CHI, 3 F3H, 5 F3'H, 1 F3'5'H, 21 FLS, and 2 FSII, and 65 transcription factors, including 22 AP2/ERF, 7 bHLH, 5 bZIP, 8 MYB, 11 NAC, and 12 WRKY, showed significant correlation with total flavonoid content. Eighteen genes (7 4CL, 5 C4H, 2 CHI, 1 F3H, and 3 FLS) and 30 genes (5 PAL, 9 4CL, 1 C4H, 2 CHI, 1 F3H, 1 DFR, 7 3AT, 1 BZ1, and 3 UGT79B1) were identified as key structural genes for kaempferol and anthocyanins biosynthesis, respectively. Our study provides valuable information for understanding the mechanism of flavonoid biosynthesis in A. tataricus root.

The genetic mechanism of heterosis utilization in maize improvement.

BACKGROUND: In maize hybrid breeding, complementary pools of parental lines with reshuffled genetic variants are established for superior hybrid performance. To comprehensively decipher the genetics of heterosis, we present a new design of multiple linked F1 populations with 42,840 F1 maize hybrids, generated by crossing a synthetic population of 1428 maternal lines with 30 elite testers from diverse genetic backgrounds and phenotyped for agronomic traits. RESULTS: We show that, although yield heterosis is correlated with the widespread, minor-effect epistatic QTLs, it may be resulted from a few major-effect additive and dominant QTLs in early developmental stages. Floral transition is probably one critical stage for heterosis formation, in which epistatic QTLs are activated by paternal contributions of alleles that counteract the recessive, deleterious maternal alleles. These deleterious alleles, while rare, epistatically repress other favorable QTLs. We demonstrate this with one example, showing that Brachytic2 represses the Ubiquitin3 locus in the maternal lines; in hybrids, the paternal allele alleviates this repression, which in turn recovers the height of the plant and enhances the weight of the ear. Finally, we propose a molecular design breeding by manipulating key genes underlying the transition from vegetative-to-reproductive growth. CONCLUSION: The new population design is used to dissect the genetic basis of heterosis which accelerates maize molecular design breeding by diminishing deleterious epistatic interactions.

CUBIC: an atlas of genetic architecture promises directed maize improvement.

BACKGROUND: Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders. RESULTS: Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width. CONCLUSIONS: Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits.

Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection.

Association mapping based on the linkage disequilibrium provides a promising tool to identify genes responsible for quantitative variations underlying complex traits. Presented here is a maize association mapping panel consisting of 155 inbred lines with mainly temperate germplasm, which was phenotyped for 34 traits and genotyped using 82 SSRs and 1,536 SNPs. Abundant phenotypic and genetic diversities were observed within the panel based on the phenotypic and genotypic analysis. A model-based analysis using 82 SSRs assigned all inbred lines to two groups with eight subgroups. The relative kinship matrix was calculated using 884 SNPs with minor allele frequency > or = 20% indicating that no or weak relationships were identified for most individual pairs. Three traits (total tocopherol content in maize kernel, plant height and kernel length) and 1,414 SNPs with missing data < 20% were used to evaluate the performance of four models for association mapping analysis. For all traits, the model controlling relative kinship (K) performed better than the model controlling population structure (Q), and similarly to the model controlling both population structure and relative kinship (Q + K) in this panel. Our results suggest this maize panel can be used for association mapping analysis targeting multiple agronomic and quality traits with optimal association model.

Comparison of nutritional traits variability in selected eighty-seven inbreds from Chinese maize (Zea mays L.) germplasm.

Among cereals, only maize has not only a high amount of carotenoids, tocopherols, and oil content but also is rich in starch and protein content compared with other major food crops, such as rice and wheat. The present investigation was made primarily to assess the genetic variability for nutritionally important traits in 87 elite maize inbreds representing major heterotic groups in China. Carotenoid and tocopherol fractions were measured by high-performance liquid chromatography (HPLC), whereas oil, starch, and protein contents were detected by a VECTER22/N near-infrared analyzer. Significant interactions between genotypes and years were observed for all the traits. The pooled mean values of beta-carotene, beta-cryptoxanthin, alpha-carotene, lutein, zeaxanthin, and total carotenoids were 0.449, 0.876, 0.121, 5.803, 3.048, and 10.298 microg g (-1), respectively, whereas the combined mean performance of alpha-tocopherol, gamma-tocopherol, delta-tocopherol, and total tocopherols were 23.98, 32.90, 2.189, and 59.55 microg g (-1), respectively. The average protein, starch, and oil contents were observed to be 12.28, 64.51, and 3.55%, respectively. High level of heritability estimates were observed for all the traits and ranged from 65.6% (protein content) to 92.5% (alpha/gamma-tocopherol ratio). Most of the traits studied in this experiment were either significantly positive correlated or independent. The present finding exhibits substantial opportunities to the breeders for improvement of these traits in maize cultivars and also suggests further exploration of a new source of elite breeding stocks containing a high level of these nutritionally important compounds. Finally, these findings may also help in biofortification of maize.

Improving QTL mapping resolution based on genotypic sampling--a case using a RIL population.

The QTL mapping results were compared with the genotypically selected and random samples of the same size on the base of a RIL population. The results demonstrated that there were no obvious differences in the trait distribution and marker segregation distortion between the genotypically selected and random samples with the same population size. However, a significant increase in QTL detection power, sensitivity, specificity, and QTL resolution in the genotypically selected samples were observed. Moreover, the highly significant effect was detected in small size of genotypically selected samples. In QTL mapping, phenotyping is a more sensitive limiting factor than genotyping so that the selection of samples could be an attractive strategy for increasing genome-wide QTL mapping resolution. The efficient selection of samples should be more helpful for QTL maker assistant selection, fine mapping, and QTL cloning.