Analysis of Heterosis and Quantitative Trait Loci for Kernel Shape Related Traits Using Triple Testcross Population in Maize

<div><p>Kernel shape related traits (KSRTs) have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL) and kernel width (KW) lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17), 82 intermated B73 × Mo17 (IBM) individuals, and the corresponding triple testcross (TTC) populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL) for six KSRTs: KL, KW, length to width ratio (LWR), perimeter length (PL), kernel area (KA), and circularity (CS). The results showed that the mid-parent heterosis (MPH) for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson’s R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW). 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total <i>R²</i> for KW (78.8%), and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total <i>R²</i> (55.3%). Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.</p></div

Linkage map generated from 302 individuals.

<p>Each chromosome is comprised of one or more LGs and each LG is represented by one bar. The bars of each chromosome were aligned vertically and not according to the order of chromosome framework. The numbers on the left of the bar represent the genetic position of markers as evaluated by the distance function of Kosambi in cM. The names on the right side of the bar indicate the markers.</p

Maximum, minimum, and mean values of RIL and TC populations based on three blocks.

<p>** <i>P</i>≤0.01.</p><p>^a Comparison between TC(B) and TC(M) using <i>t</i> test.</p><p>^b Comparison between TC(F) and the mean of TC(B) and TC(M) using <i>t</i> test.</p><p>Maximum, minimum, and mean values of RIL and TC populations based on three blocks.</p

The relationship between heterozygosity and KSRTs based on TC(B) and TC(M) populations.

<p>The relationship between heterozygosity and KSRTs based on TC(B) and TC(M) populations.</p

Overview of genetic distance between two adjacent markers on the linkage groups.

<p>Overview of genetic distance between two adjacent markers on the linkage groups.</p

The genetic effect and contribution of epistatic QTL for KSRTs detected in <i>Z1</i> and <i>Z2</i>.

<p>** <i>P</i>≤0.01.</p><p>^a<i>a</i>_<i>i</i> and <i>a</i>_<i>j</i> represent the main effect of the loci <i>i</i> and <i>j</i>, and <i>a</i>_<i>ij</i> represents the epistatic effect between loci <i>i</i> and <i>j</i>.</p><p>^b<i>R</i>^<i>2</i>_<i>i</i>, <i>R</i>^<i>2</i>_<i>j</i>, <i>R</i>^<i>2</i>_<i>ij</i>, and <i>R</i>^<i>2</i> represent the genetic contribution via the percentage of the total variation explained by the <i>a</i>_<i>i</i>, <i>a</i>_<i>j</i>, <i>a</i>_<i>ij</i> and the total interactions for KSRTs respectively.</p><p>^{c, d} indicate marker intervals mapped to more than one QTL.</p><p>The genetic effect and contribution of epistatic QTL for KSRTs detected in <i>Z1</i> and <i>Z2</i>.</p

Mean values and heterosis based on the three blocks.

<p>* <i>P</i>≤0.05,</p><p>** <i>P</i>≤0.01.</p><p>^a Comparison between B73 and Mo17 using <i>t</i> test.</p><p>^b Comparison between MP and F1 using <i>t</i> test.</p><p>Mean values and heterosis based on the three blocks.</p

Images of kernel shape related traits detected by <i>SmartGrain</i>.

<p>(A) The loading image for <i>SmartGrain</i>. The gray wire in the center of the image is used as the reference length. (B) KSRTs recognized by <i>SmartGrain</i>. The red outline can be used for calculating PL and KA (areas within the red line); The yellow and green lines indicate the KL and KW, respectively, and can also be used for calculating LWR and CS; The small red circle and green circle represent the center of gravity and the intersection of length and width, respectively, as evaluated by <i>SmartGrain</i>. These values are not included in our analysis.</p

Effects of 24-epibrassinolide on the postharvest quality and antioxidant activities of blueberry fruits

In this study, blueberry fruits (Vaccinium corymbosum cv. ‘Bluerain’) were sprayed with different concentrations (0.25, 0.5, 0.75, and 1 mg/L) of exogenous 24-epibrassionolide (EBR) after harvest and kept at 18°C and relative humidity of 90∼95% for 8 d. By observing the decay incidence and firmness changes, the optimal treatment concentration (0.75 mg/L) was screened, and then the effects of 0.75 mg/L EBR treatment on fruit quality and antioxidant activities were further explored. The results showed that EBR treatment could delay the decrease in firmness, total soluble solids, and acidity; maintain the contents of nutritional components, such as ascorbic acid, total phenol, and the total anthocyanin; and promote the activities of antioxidant enzymes, especially SOD and PAL, thereby helping to maintain the balance of reactive oxygen species and reduce the degree of membrane lipid peroxidation, as reflected by the content of MDA, and delaying the senescence process of blueberry fruit. Taken together, EBR treatment could help maintain the nutritional components of blueberry fruit and could be used as a new alternative reagent for blueberry preservation.</p

Elucidating the role of <i>Rhodiola rosea</i> L. in sepsis-induced acute lung injury via network pharmacology: emphasis on inflammatory response, oxidative stress, and the PI3K-AKT pathway

Sepsis-induced acute lung injury (ALI) is associated with high morbidity and mortality. Rhodiola rosea L. (Crassulaceae) (RR) and its extracts have shown anti-inflammatory, antioxidant, immunomodulatory, and lung-protective effects. This study elucidates the molecular mechanisms of RR against sepsis-induced ALI. The pivotal targets of RR against sepsis-induced ALI and underlying mechanisms were revealed by network pharmacology and molecular docking. Human umbilical vein endothelial cells (HUVECs) were stimulated by 1 μg/mL lipopolysaccharide for 0.5 h and treated with 6.3, 12.5, 25, 50, 100, and 200 μg/mL RR for 24 h. Then, the lipopolysaccharide-stimulated HUVECs were subjected to cell counting kit-8 (CCK-8), enzyme-linked immunosorbent, apoptosis, and Western blot analyses. C57BL/6 mice were divided into sham, model, low-dose (40 mg/kg), mid-dose (80 mg/kg), and high-dose (160 mg/kg) RR groups. The mouse model was constructed through caecal ligation and puncture, and histological, apoptosis, and Western blot analyses were performed for further validation. We identified six hub targets (MPO, HRAS, PPARG, FGF2, JUN, and IL6), and the PI3K-AKT pathway was the core pathway. CCK-8 assays showed that RR promoted the viability of the lipopolysaccharide-stimulated HUVECs [median effective dose (ED50) = 18.98 μg/mL]. Furthermore, RR inhibited inflammation, oxidative stress, cell apoptosis, and PI3K-AKT activation in lipopolysaccharide-stimulated HUVECs and ALI mice, which was consistent with the network pharmacology results. This study provides foundational knowledge of the effective components, potential targets, and molecular mechanisms of RR against ALI, which could be critical for developing targeted therapeutic strategies for sepsis-induced ALI.</p