Identification of QTLs and joint QTL segments of leaflet traits at different canopy layers in an interspecific RIL population of soybean.

KEY MESSAGE: A leaflet trait on different canopy layers may have different QTLs; leaflet trait QTLs may cluster to form joint QTL segments; all canopy layer QTLs form a complete QTL system for a leaflet trait. As the main part of the plant canopy structure, leaf/leaflet size and shape affect the plant architecture and yield. To explore the leaflet trait QTL system, a population composed of 199 recombinant inbred lines derived from Changling (annual wild, narrow leaflet) and Yiqianli (landrace, broad leaflet) with their parents was tested for leaflet length (LL), width (LW) and length to width (LLW). The population was genotyped with specific-locus amplified fragment sequencing (SLAF-seq) and applied for linkage mapping of the leaflet traits. The results showed that the leaflet traits varied greatly even within a plant, which supported a stratified leaflet sampling strategy to evaluate these traits at top, middle and bottom canopy layers. Altogether, 13 LL, 10 LW and 9 LLW in a total of 32 plus 3 duplicated QTLs were identified, in which, 17 QTLs were new ones, and 48.6%, 28.6% and 22.8% of QTLs were from the top, middle and bottom layers, respectively, indicating the genetic importance of the top layer leaves. Since a leaflet trait may have layer-specific QTLs, all layer QTLs form a complete QTL system. Five QTL clusters each with their QTL supporting intervals overlapped were designated as joint QTL segments (JQSs). In JQS-16, with its linkage map further validated using PCR markers, two QTLs, qLW-16-1 and qLLW-16-1 of the top layer leaflet, were identified six QTL·times. Six candidate genes were predicted, with Glyma.16G127900 as the most potential one for LW and LLW. Three PCR markers, Gm16PAV0653, BARCSOYSSR_16_0796 and YC-16-3, were suggested for marker-assisted selection for LW and LLW in JQS-16.

Identification of Additive-Epistatic QTLs Conferring Seed Traits in Soybean Using Recombinant Inbred Lines.

Seed weight and shape are important agronomic traits that affect soybean quality and yield. In the present study, we used image analysis software to evaluate 100-seed weight and seed shape traits (length, width, perimeter, projection area, length/width, and weight/projection area) of 155 novel recombinant inbred soybean lines (NJRISX) generated by crossing "Su88-M21" and "XYXHD". We examined quantitative trait loci (QTLs) associated with the six traits (except seed weight per projection area), and identified 42 additive QTLs (5-8 QTLs per trait) accounting for 24.9-37.5% of the phenotypic variation (PV). Meanwhile, 2-4 epistatic QTL pairs per trait out of a total of 18 accounted for 2.5-7.2% of the PV; and unmapped minor QTLs accounted for the remaining 35.0-56.7% of the PV. A total of 28 additive and 11 epistatic QTL pairs were concentrated in nine joint QTL segments (JQSs), indicating that QTLs associated with seed weight and shape are closely related and interacted. An interaction was also detected between additive and epistatic QTL pairs and environment, which made significant contributions of 1.4-9.5% and 0.4-0.8% to the PV, respectively. We annotated 18 candidate genes in the nine JQSs, which were important for interpreting the close relationships among the six traits. These findings indicate that examining the interactions between closely related traits rather than only analyzing individual trait provides more useful insight into the genetic system of the interrelated traits for which there has been limited QTL information.

Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks.

Interfacial energy between sludge foulants and rough membrane surface critically determines adhesive fouling in membrane bioreactors (MBRs). As a current available method, the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach cannot efficiently quantify the interfacial energy. In this study, novel methods including back propagation (BP) artificial neural network (ANN) and generalized regression neural network (GRNN) were proposed to quantify the interfacial energy associated with the membrane fouling in an MBR. Different levels of 5 apparent input factors and the resulted interfacial energies were used as training and testing databases for establishment of ANN models. The established BP ANN and GRNN models exhibited high regression coefficients and accuracies, suggesting the high capacity of ANN models to capture the complicated non-linear mapping relations between interfacial energy and various factors. As compared with the advanced XDLVO approach, both BP ANN and GRNN showed remarkably improved quantification efficiency. Meanwhile, BP ANN showed better prediction performance than GRNN model. Case study further demonstrated the robustness and feasibility of BP ANN for interfacial energy quantification. This study provided a new approach to quantify interfacial energy associated with membrane fouling.

Comparison of Morphologic Parameters of Temporomandibular Joint for Asymptomatic Subjects Using the Two-Dimensional and Three-Dimensional Measuring Methods.

The differences of temporomandibular joint (TMJ) morphologic parameters by using two-dimensional (2D) and three-dimensional (3D) measuring methods were compared. Ten asymptomatic subjects (26.75 ± 4.89 years) were randomly recruited. The 3D models of the maxilla, mandible, and teeth were reconstructed according to cone-beam computed tomography (CBCT) image data. The morphologic parameters of TMJs were measured by the 2D CBCT measuring method (group A) and the 3D reconstruction model measuring method (group B), respectively. The morphologic parameters in each group were assessed by paired samples t-test, and the statistical significance was achieved when p < 0.05. The horizontal condylar angle (HCA), sagittal ramus angle (SRA), medial joint space (MJS), lateral joint space (LJS), superior joint space (SJS), and anterior joint space (AJS) in group A were significantly smaller than those in group B (p < 0.05). The HCA on the left side was significantly smaller than that on the right side in group A (p < 0.05). However, all the morphologic parameters in group B were not significantly different between left and right sides. In conclusion, there were significant differences for the morphologic parameters of TMJ measured on 2D CBCT and 3D models. 3D measuring method should be used for the detection of TMJ morphology in clinical practice.

Morphologic Analysis of the Temporomandibular Joint Between Patients With Facial Asymmetry and Asymptomatic Subjects by 2D and 3D Evaluation: A Preliminary Study.

Signs and symptoms of temporomandibular joint (TMJ) dysfunction are commonly found in patients with facial asymmetry. Previous studies on the TMJ position have been limited to 2-dimensional (2D) radiographs, computed tomography (CT), or cone-beam computed tomography (CBCT). The purpose of this study was to compare the differences of TMJ position by using 2D CBCT and 3D model measurement methods. In addition, the differences of TMJ positions between patients with facial asymmetry and asymptomatic subjects were investigated. We prospectively recruited 5 patients (cases, mean age, 24.8 ±â€Š2.9 years) diagnosed with facial asymmetry and 5 asymptomatic subjects (controls, mean age, 26 ±â€Š1.2 years). The TMJ spaces, condylar and ramus angles were assessed by using 2D and 3D methods. The 3D models of mandible, maxilla, and teeth were reconstructed with the 3D image software. The variables in each group were assessed by t-test and the level of significance was 0.05. There was a significant difference in the horizontal condylar angle (HCA), coronal condylar angle (CCA), sagittal ramus angle (SRA), medial joint space (MJS), lateral joint space (LJS), superior joint space (SJS), and anterior joint space (AJS) measured in the 2D CBCT and in the 3D models (P < 0.05). The case group had significantly smaller SJS compared to the controls on both nondeviation side (P = 0.009) and deviation side (P = 0.004). In the case group, the nondeviation SRA was significantly larger than the deviation side (P = 0.009). There was no significant difference in the coronal condylar width (CCW) in either group. In addition, the anterior disc displacement (ADD) was more likely to occur on the deviated side in the case group. In conclusion, the 3D measurement method is more accurate and effective for clinicians to investigate the morphology of TMJ than the 2D method.