No abstract

Despite the well-recognized importance of grain yield in high-oil maize (Zea mays L.) breeding and production, few studies have reported the application of QTL mapping of such traits. An inbred line of high-oil maize designated 'GY220' was crossed with two dent maize inbred lines to generate two connected F 2:3 populations with 284 and 265 F 2:3 families. Our main objective was to evaluate the influence of genetic background on QTL detection of grain yield traits through comparisons between the F 2:3 populations. The field experiments were conducted during the spring in Luoyang and summer in Xuchang, Henan, China. Two genetic linkage maps were constructed with a genetic distance of 2111.7 and 2298.5 cM using 185 and 173 polymorphic SSR markers, respectively. In total, 18 and 15 QTL were detected for six grain yield traits in the two populations. Only one common QTL marker was shared between the two populations. A QTL cluster associated with five traits was identified at bin 1.05-1.06, including the shared QTL for 100GW, which demonstrated the largest effect (16.7%). Among the detected QTL, 12 digenic interactions were identified. Our results reflect the substantial influence of dent maize genetic background on QTL detection of grain yield traits.

This study aimed to investigate the effect of strains on quality improvement of bog bilberry juice. Bog bilberry juice with different pH conditions was fermented by B7 or C8-1 strain. Physicochemical index, amino acids, phenolic compounds, and volatiles of these fermented juices were compared. Results indicated that strains preferred to metabolize malic acid and reducing sugar in non-pH-adjusted juice (NJ, pH 2.65), whereas quinic and citric acids were largely consumed in pH-adjusted juice (AJ, pH 3.50). Shikimic acid and aromatic amino acids were significantly accumulated in pH-adjusted juice, and phenolic compounds in both juices were significantly reduced. These strains enhanced the composition and concentration of volatiles compounds in non-pH-adjusted juice and improved the floral and fruity flavors. However, concentration and complexity of volatiles were reduced in pH-adjusted juices.

High-oil maize (Zea mays L.) has special value in animal feed and human food. Two hundred and eight-four and 265 F 2:3 families developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for grain oil and starch contents under two environments. Using composite interval mapping, 1-6 QTL for each trait were detected under each environment and in combined analysis in both populations. Only one common QTL across two environments in each population and across two populations were found for starch content. Among the detected QTL, nine digenic interactions with small effects were identified. Comparison of single-trait QTL and the results of multiple-trait QTL mapping showed that oil content might be complicatedly correlated with starch content. Although singletrait QTL with the same parental effects for both traits and oil-starch QTL were all detected at the same genetic bin 6.04 as the cloned high-oil QTL (qHO6) with no unfavorable effects on grain weight, our results did reflect the difficulty to realize simultaneous improvement on grain oil and starch contents. Of course, these results should be validated in further experiments under more environments using RILs, NILs and other permanent populations.

Protein is one of the three main storage chemical components in maize grains, and is negatively correlated with starch concentration (SC). Our objective was to analyse the influence of genetic backgrounds on QTL detection for protein concentration (PC) and to reveal the molecular genetic associations between PC and both SC and grain weight (GWP). Two hundred and eighty-four (Pop1) and 265 (Pop2) F(2:3) families were developed from two crosses between one high-oil maize inbred GY220 and two normal maize inbreds 8984 and 8622 respectively, and were genotyped with 185 and 173 pairs of SSR markers. PC, SC and GWP were evaluated under two environments. Composite interval mapping (CIM) and multiple interval mapping (MIM) methods were used to detect single-trait QTL for PC, and multiple-trait QTL for PC with both SC and GWP. No common QTL were shared between the two populations for their four and one PC QTL. Common QTL with opposite signs of effects for PC and SCGWP were detected on three marker intervals at bins 6.07-6.08, 8.03 and 8.03-8.04. Multiple-traits QTL mapping showed that tightly-linked QTL, pleiotropic QTL and QTL having effects with opposite directions for PC and SCGWP were all observed in Pop1, while all QTL reflected opposite effects in Pop2.