94%) in Guiding (negative for Hongda and positive for Zunyan 6) together with miRNA775. mRNA1218 × miRNA183 had negative main epistasis (hq2 = 10.44%) and treatment-specific epistasis (hqqe2 = 18.44%) in Xingyi for Zunyan 6. Therefore, epistasis might be useful as an efficient genetic tool for increasing total sugar content in tobacco leaf. In QTP mapping, lysine was detected to have a large individual negative main effect (q) on total sugar content in tobacco leaves (− log10P = 62.55 and hqq2 46.90%), but positive epistasis effects (qq) along with phenylalanine (− log10P = 53.47 and

hqq2 = 33.27%) ( Table 2, Fig. 1 and Fig. 2). Meanwhile, for QTM mapping, fructose was detected with large positive individual effects (q) (− log10P = 80.45 and hqq2 52.30%), while linolenic and linoleic acids had lower negative individual effects (q) (− log10P = 13.20 and hqq2 6.22%) ( Table 2, Fig. 1 and Fig. 2). Epistasis effects of these two QTMs were Pirfenidone also significant (− log10P = 38.29 and hqq2 26.02%). The principal feat of this research was to implement QTXNetwork, a software program based on a mixed linear model, for analysis of -omics

data. This research was able to take advantage of an abundance of data on gene methylation, transcript expression, protein content and metabolite characterization to find associations of QTS, QTT, QTP and QTM with two complex traits. Our goal in these analyses was to directly estimate the genetic effects of each type of loci on the genetic architecture of these traits. We believe this to be the first time that these new methods have been used

to detect genome methylated loci, transcripts, check details proteins and metabolites associated with chromium content and total sugar content in tobacco leaves. The results showed that various Quisqualic acid types of genetic effects contributed to the two traits at different levels of -omics data, but that the composition and proportion of each type varied among -omics levels (Table 1 and Table 2). For example we observed that total heritability increased consecutively for genomic, transcriptomic, proteomic and metabolomic loci, which was consistent with the central genetic dogma of gene expression through transcripts and their resulting proteins and metabolites in the transfer of genetic information to phenotype. Another discovery of this study was that the proportion of total heritability of epistasis and treatment interaction was very significant in the combination of trait and -omic evaluation, and that the total proportion of heritability based on epistasis and treatment interaction was nearly equal to that of the main factors. There was one QTS epistasis detected only in location 2 (hqqe2 11.24%) for chromium content among the four -omics levels. The proportions of total treatment interaction (hqe + qqe2) were 35.97%, 20.46%, 0.70% and 3.84% in genomic, transcriptomic, proteomic, and metabolic levels, respectively.