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The Relative Pollen Productivities (RPPs) of common steppe species are estimated using Extended R-value (ERV) model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China. Artemisia, Chenopodiaceae, Poaceae, Cyperaceae, and Asteraceae are the dominant pollen types in pollen assemblages, reflecting the typical steppe communities well. The five dominant pollen types and six common types (Thalictrum, Iridaceae, Potentilla, Ephedra, Brassicaceae, and Ulmus) have strong wind transport abilities; the estimated Relevant Source Area of Pollen (RSAP) is ca. 1000 m when the sediment basin radius is set at 0.5 m. Ulmus, Artemisia, Brassicaceae, Chenopodiaceae, and Thalictrum have relative high RPPs; Poaceae, Cyperaceae, Potentilla, and Ephedra pollen have moderate RPPs; Asteraceae and Iridaceae have low RPPs. The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction. However, the RPPs of Asteraceae and Iridaceae are obviously underestimated, and those of Poaceae, Chenopodiaceae, and Ephedra are either slightly underestimated or slightly overestimated, suggesting that those RPPs should be considered with caution. These RPPs were applied to estimating plant abundances for two fossil pollen spectra (from the Lake Bayanchagan and Lake Haoluku) covering the Holocene in typical steppe area, using the "Regional Estimates of Vegetation Abundance from Large Sites" (REVEALS) model. The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae, Cyperaceae, and Artemisia plants flourished in this area before 6500-5600 cal yr BP, and then was replaced by present typical steppe.
A large-scale metabolic quantitative trait loci (mQTL) analysis was performed on the well-characterized Solanum pennellii introgression lines to investigate the genomic regions associated with secondary metabolism in tomato fruit pericarp. In total, 679 mQTLs were detected across the 76 introgression lines. Heritability analyses revealed that mQTLs of secondary metabolism were less affected by environment than mQTLs of primary metabolism. Network analysis allowed us to assess the interconnectivity of primary and secondary metabolism as well as to compare and contrast their respective associations with morphological traits. Additionally, we applied a recently established real-time quantitative PCR platform to gain insight into transcriptional control mechanisms of a subset of the mQTLs, including those for hydroxycinnamates, acyl-sugar, naringenin chalcone, and a range of glycoalkaloids. Intriguingly, many of these compounds displayed a dominant-negative mode of inheritance, which is contrary to the conventional wisdom that secondary metabolite contents decreased on domestication. We additionally performed an exemplary evaluation of two candidate genes for glycolalkaloid mQTLs via the use of virus-induced gene silencing. The combined data of this study were compared with previous results on primary metabolism obtained from the same material and to other studies of natural variance of secondary metabolism.