Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.).

BACKGROUND: Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2). METHODS AND RESULTS: The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait. CONCLUSION: Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k-mers.

The development of improved methods for genome-wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k-mers for GWAS has taken over as a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k-mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker-trait associations (MTAs) that are relevant to human healthcare and crop improvement.

r2mlm: An R package calculating R-squared measures for multilevel models.

Multilevel models are used ubiquitously in the social and behavioral sciences and effect sizes are critical for contextualizing results. A general framework of R-squared effect size measures for multilevel models has only recently been developed. Rights and Sterba (2019) distinguished each source of explained variance for each possible kind of outcome variance. Though researchers have long desired a comprehensive and coherent approach to computing R-squared measures for multilevel models, the use of this framework has a steep learning curve. The purpose of this tutorial is to introduce and demonstrate using a new R package - r2mlm - that automates the intensive computations involved in implementing the framework and provides accompanying graphics to visualize all multilevel R-squared measures together. We use accessible illustrations with open data and code to demonstrate how to use and interpret the R package output.

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study.

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Key parameter optimization using multivariable linear model for the evaluation of the in vitro estrogenic activity assay in T47D cell lines (CXCL-test).

In comparison with analytical tools, bioassays provide higher sensitivity and more complex evaluation of environmental samples and are indispensable tools for monitoring increasing in anthropogenic pollution. Nevertheless, the disadvantage in cellular assays stems from the material variability used within the assays, and an interlaboratory adaptation does not usually lead to satisfactory test sensitivities. The aim of this study was to evaluate the influence of material variability on CXCL12 secretion by T47D cells, the outcome of the CXCL-test (estrogenic activity assay). For this purpose, the cell line sources, sera suppliers, experimental and seeding media, and the amount of cell/well were tested. The multivariable linear model (MLM), employed as an innovative approach in this field for parameter evaluation, identified that all the tested parameters had significant effects. Knowledge of the contributions of each parameter has permitted step-by-step optimization. The most beneficial approach was seeding 20,000 cells/well directly in treatment medium and using DMEM for the treatment. Great differences in both basal and maximal cytokine secretions among the three tested cell lines and different impacts of each serum were also observed. Altogether, both these biologically based and highly variable inputs were additionally assessed by MLM and a subsequent two-step evaluation, which revealed a lower variability and satisfactory reproducibility of the test. This analysis showed that not only parameter and procedure optimization but also the evaluation methodology must be considered from the perspective of interlaboratory method adaptation. This overall methodology could be applied to all bioanalytical methods for fast multiparameter and accurate analysis.

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components.

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.

Multi-locus genome-wide association studies for five yield-related traits in rice.

BACKGROUND: Improving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In this study, one single-locus genome-wide association studies (SL-GWAS) method (MLM) in conjunction with five multi-locus genome-wide association studies (ML-GWAS) approaches (mrMLM, FASTmrMLM, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were conducted in a panel consisting of 529 rice core varieties with 607,201 SNPs. RESULTS: A total of 152, 106, 12, 111, and 64 SNPs were detected by the MLM model associated with the five yield-related traits, namely grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and yield per plant (YPP), respectively. Furthermore, 74 significant quantitative trait nucleotides (QTNs) were presented across at least two ML-GWAS methods to be associated with the above five traits successively. Finally, 20 common QTNs were simultaneously discovered by both SL-GWAS and ML-GWAS methods. Based on genome annotation, gene expression analysis, and previous studies, two candidate key genes (LOC_Os09g02830 and LOC_Os07g31450) were characterized to affect GW and TGW, separately. CONCLUSIONS: These outcomes will provide an indication for breeding high-yielding rice varieties in the immediate future.

Spin Exchanges Between Transition Metal Ions Governed by the Ligand p-Orbitals in Their Magnetic Orbitals.

In this review on spin exchanges, written to provide guidelines useful for finding the spin lattice relevant for any given magnetic solid, we discuss how the values of spin exchanges in transition metal magnetic compounds are quantitatively determined from electronic structure calculations, which electronic factors control whether a spin exchange is antiferromagnetic or ferromagnetic, and how these factors are related to the geometrical parameters of the spin exchange path. In an extended solid containing transition metal magnetic ions, each metal ion M is surrounded with main-group ligands L to form an MLn polyhedron (typically, n = 3-6), and the unpaired spins of M are represented by the singly-occupied d-states (i.e., the magnetic orbitals) of MLn. Each magnetic orbital has the metal d-orbital combined out-of-phase with the ligand p-orbitals; therefore, the spin exchanges between adjacent metal ions M lead not only to the M-L-M-type exchanges, but also to the M-L…L-M-type exchanges in which the two metal ions do not share a common ligand. The latter can be further modified by d0 cations A such as V5+ and W6+ to bridge the L…L contact generating M-L…A…L-M-type exchanges. We describe several qualitative rules for predicting whether the M-L…L-M and M-L…A…L-M-type exchanges are antiferromagnetic or ferromagnetic by analyzing how the ligand p-orbitals in their magnetic orbitals (the ligand p-orbital tails, for short) are arranged in the exchange paths. Finally, we illustrate how these rules work by analyzing the crystal structures and magnetic properties of four cuprates of current interest: -CuV2O6, LiCuVO4, (CuCl)LaNb2O7, and Cu3(CO3)2(OH)2.

Association analysis between agronomic traits and AFLP markers in a wide germplasm of proso millet (Panicum miliaceum L.) under normal and salinity stress conditions.

BACKGROUND: Proso millet is a highly nutritious cereal considered an essential component of processed foods. It is also recognized with high water-use efficiency as well as short growing seasons. This research was primarily aimed at investigating the genetic diversity among genotypes based on evaluating those important traits proposed in previous researches under both normal and salinity- stress conditions. Use of Amplified fragment length polymorphism (AFLP) molecular markers as well as evaluating the association between markers and the investigated traits under both conditions was also another purpose of this research. RESULTS: According to the phenotypic correlation coefficients, the seed yield had the highest correlation with the forage and biological yields under both conditions. By disintegrating those traits investigated under normal and salinity-stress conditions into principal component analysis, it was found that the first four principal components justified more than 59.94 and 62.48% of the whole variance, respectively. The dendrogram obtained by cluster analysis displayed three groups of genotypes under both normal and salinity- stress conditions. Then, association analyses were conducted on 143 proso millet genotypes and 15 agronomic traits as well as 514 polymorphic AFLP markers (out of 866 created bands) generated by 11 primer combinations (out of the initial 20 primer combinations) EcoRI/MseI. The results obtained by mixed linear model (MLM) indicated that under normal conditions, the M14/E10-45 and M14/E10-60 markers had strong associations with seed yield. A similar trend was also observed for M14/E10-45 and M14/E11-44 markers in relation to forage yield. On the other hand, M14/E10-14, M14/E10-64 markers (for seed yield) and M14/E10-64 marker (for forage yield), had significant and stable association in all environments under salinity-stress conditions. Moreover, a number of markers showed considerable associations and stability under both normal and salinity stress conditions. CONCLUSIONS: According to the analysis of phenotypic data, the wide germplasm of Iranian proso millet has significant variation in terms of measured traits. It can be concluded that markers showing strong associations with traits under salinity-stress conditions are suitable candidates to be used in future marker-assisted selection (MAS) studies to improve salinity-resistance genotypes of Panicum miliaceum in arid and semiarid areas.

Genome-wide association mapping revealed syntenic loci QFhb-4AL and QFhb-5DL for Fusarium head blight resistance in common wheat (Triticum aestivum L.).

BACKGROUND: Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a major threat to wheat production and food security worldwide. Breeding stably and durably resistant cultivars is the most effective approach for managing and controlling the disease. The success of FHB resistance breeding relies on identification of an effective resistant germplasm. We conducted a genome-wide association study (GWAS) using the high-density wheat 90 K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of FHB resistance in natural population and identify associated molecular markers. RESULTS: The resistance to FHB fungal spread along the rachis (Type II resistance) was evaluated on 171 wheat cultivars in the 2016-2017 (abbr. as 2017) and 2017-2018 (abbr. as 2018) growing seasons. Using Illumina Infinum iSelect 90 K SNP genotyping data, a genome-wide association study (GWAS) identified 26 loci (88 marker-trait associations), which explained 6.65-14.18% of the phenotypic variances. The associated loci distributed across all chromosomes except 2D, 6A, 6D and 7D, with those on chromosomes 1B, 4A, 5D and 7A being detected in both years. New loci for Type II resistance were found on syntenic genomic regions of chromsome 4AL (QFhb-4AL, 621.85-622.24 Mb) and chromosome 5DL (QFhb-5DL, 546.09-547.27 Mb) which showed high collinearity in gene content and order. SNP markers wsnp_JD_c4438_5568170 and wsnp_CAP11_c209_198467 of 5D, reported previously linked to a soil-borne wheat mosaic virus (SBWMV) resistance gene, were also associated with FHB resistance in this study. CONCLUSION: The syntenic FHB resistant loci and associated SNP markers identified in this study are valuable for FHB resistance breeding via marker-assisted selection.

Synthesis and In Vitro Evaluation of 8-Pyridinyl-Substituted Benzo[e]imidazo[2,1-c][1,2,4]triazines as Phosphodiesterase 2A Inhibitors.

Phosphodiesterase 2A (PDE2A) is highly expressed in distinct areas of the brain, which are known to be related to neuropsychiatric diseases. The development of suitable PDE2A tracers for Positron Emission Tomography (PET) would permit the in vivo imaging of the PDE2A and evaluation of disease-mediated alterations of its expression. A series of novel fluorinated PDE2A inhibitors on the basis of a Benzoimidazotriazine (BIT) scaffold was prepared leading to a prospective inhibitor for further development of a PDE2A PET imaging agent. BIT derivatives (BIT1-9) were obtained by a seven-step synthesis route, and their inhibitory potency towards PDE2A and selectivity over other PDEs were evaluated. BIT1 demonstrated much higher inhibition than other BIT derivatives (82.9% inhibition of PDE2A at 10 nM). BIT1 displayed an IC50 for PDE2A of 3.33 nM with 16-fold selectivity over PDE10A. This finding revealed that a derivative bearing both a 2-fluoro-pyridin-4-yl and 2-chloro-5-methoxy-phenyl unit at the 8- and 1-position, respectively, appeared to be the most potent inhibitor. In vitro studies of BIT1 using mouse liver microsomes (MLM) disclosed BIT1 as a suitable ligand for 18F-labeling. Nevertheless, future in vivo metabolism studies are required.

MTD-like motif of a BH3-only protein, BNIP1, induces necrosis accompanied by an intracellular calcium spike.

The mitochondrial targeting domain (MTD) of Noxa has necrosis-inducing activity when conjugated with cell-penetrating peptide (CPP). In this study, we report another MTD-like motif, B1MLM, found in BNIP1, a pro-apoptotic BH3-only protein found in the endoplasmic reticulum membrane. The B1MLM peptide, conjugated with CPP, induced necrosis in a way similar to that of R8:MTD. R8:B1MLM caused an intracellular calcium spike, mitochondrial reactive oxygen species generation, and mitochondrial fragmentation. The cytosolic calcium spike was likely due to the opening of the mitochondrial permeability transition pore.

Genome-wide association study of rice grain width variation.

Seed size is variable within many plant species, and understanding the underlying genetic factors can provide insights into mechanisms of local environmental adaptation. Here we make use of the abundant genomic and germplasm resources available for rice (Oryza sativa) to perform a large-scale genome-wide association study (GWAS) of grain width. Grain width varies widely within the crop and is also known to show climate-associated variation across populations of its wild progenitor. Using a filtered dataset of >1.9 million genome-wide SNPs in a sample of 570 cultivated and wild rice accessions, we performed GWAS with two complementary models, GLM and MLM. The models yielded 10 and 33 significant associations, respectively, and jointly yielded seven candidate locus regions, two of which have been previously identified. Analyses of nucleotide diversity and haplotype distributions at these loci revealed signatures of selection and patterns consistent with adaptive introgression of grain width alleles across rice variety groups. The results provide a 50% increase in the total number of rice grain width loci mapped to date and support a polygenic model whereby grain width is shaped by gene-by-environment interactions. These loci can potentially serve as candidates for studies of adaptive seed size variation in wild grass species.

Classification and Clinical Management of Variants of Uncertain Significance in High Penetrance Cancer Predisposition Genes.

In 2008, the International Agency for Research on Cancer (IARC) proposed a system for classifying sequence variants in highly penetrant breast and colon cancer susceptibility genes, linked to clinical actions. This system uses a multifactorial likelihood model to calculate the posterior probability that an altered DNA sequence is pathogenic. Variants between 5%-94.9% (class 3) are categorized as variants of uncertain significance (VUS). This interval is wide and might include variants with a substantial difference in pathogenicity at either end of the spectrum. We think that carriers of class 3 variants would benefit from a fine-tuning of this classification. Classification of VUS to a category with a defined clinical significance is very important because for carriers of a pathogenic mutation full surveillance and risk-reducing surgery can reduce cancer incidence. Counselees who are not carriers of a pathogenic mutation can be discharged from intensive follow-up and avoid unnecessary risk-reducing surgery. By means of examples, we show how, in selected cases, additional data can lead to reclassification of some variants to a different class with different recommendations for surveillance and therapy. To improve the clinical utility of this classification system, we suggest a pragmatic adaptation to clinical practice.

Pessimism and Homework in CBT for Depression.

OBJECTIVE: To investigate the moderating effects of attributional style on the relationship between client-rated benefits of homework completion and depression throughout a course of cognitive behavior therapy (CBT). METHOD: A total of 28 clients, aged 20 to 65 years, experiencing their first major depressive episode completed up to 20 sessions of CBT plus a follow-up session at 2 months. Clients, therapists, and independent observers completed the measures. Multilevel modeling was used for a within-person longitudinal analysis of data. RESULTS: Pessimism slightly moderated the relationship between quantity-quality of homework completion and depression severity over time. Decreases in depression severity were largely independent of level of homework completion. CONCLUSION: While CBT is effective in reducing depression, pessimistic attributional style can affect the perception that clients bring to the quantity and quality of homework completion. Clinicians could thus focus on dealing with pessimistic style for treatment and homework to moderate the severity of depression.

Head-to-Head Comparison of SSTR Antagonist [68Ga]Ga-DATA5m-LM4 with SSTR Agonist [68Ga]Ga-DOTANOC PET/CT in Patients with Well Differentiated Gastroenteropancreatic Neuroendocrine Tumors: A Prospective Imaging Study.

Neuroendocrine tumors (NETs) are slow-growing tumors that express high levels of somatostatin receptors (SSTRs). Recent studies have shown the superiority of radiolabeled SSTR antagonists in theranostics compared to agonists. In this prospective study, we compared the diagnostic efficacy between [68Ga]Ga-DOTANOC and [68Ga]Ga-DATA5m-LM4 in the detection of primary and metastatic lesions in patients with well differentiated gastroenteropancreatic (GEP) NETs. Histologically proven GEP-NET patients underwent [68Ga]Ga-DOTANOC & [68Ga]Ga-DATA5m-LM4 PET/CT scans, which were analyzed. The qualitative analysis involved the visual judgment of radiotracer uptake validated by the morphological findings using CT, which was considered as the reference standard. Quantitative comparisons were presented as the standardized uptake value (SUV) corrected for lean body mass: SULpeak, SULavg, and tumor-to-background ratios (TBR). In total, 490 lesions were confirmed via diagnostic CT. The lesion-based sensitivity of [68Ga]Ga-DATA5m-LM4 PET/CT was 94.28% (462/490) and 83.46% (409/490) for [68Ga]Ga-DOTANOC PET/CT (p < 0.0001). [68Ga]Ga-DATA5m-LM4 had statistical significance over [68Ga]Ga-DOTANOC in liver metastases [100% vs. 89.4%; p < 0.0001 (292 vs. 253 {283 lesions on CT})] and bone metastases [100% vs. 82.9%; p = 0.005 (45 vs. 34 {41 lesions on CT})]. Statistical significance was also noted for the TBR SULpeak of the primary and liver lesions. [68Ga]Ga-DATA5m-LM4 showed better sensitivity and a higher target-to-background ratio than [68Ga]Ga-DOTANOC PET/CT. [68Ga]Ga-DATA5m-LM4 PET/CT can be used to quantify the extent of skeletal and liver metastases for better planning of SSTR agonist- or antagonist-based therapy.

Synthesis and SAR studies of 5-(pyridin-4-yl)-1,3,4-thiadiazol-2-amine derivatives as potent inhibitors of Bloom helicase.

Human cells utilize a variety of complex DNA repair mechanisms in order to combat constant mutagenic and cytotoxic threats from both exogenous and endogenous sources. The RecQ family of DNA helicases, which includes Bloom helicase (BLM), plays an important function in DNA repair by unwinding complementary strands of duplex DNA as well as atypical DNA structures such as Holliday junctions. Mutations of the BLM gene can result in Bloom syndrome, an autosomal recessive disorder associated with cancer predisposition. BLM-deficient cells exhibit increased sensitivity to DNA damaging agents indicating that a selective BLM inhibitor could be useful in potentiating the anticancer activity of these agents. In this work, we describe the medicinal chemistry optimization of the hit molecule following a quantitative high-throughput screen of >355,000 compounds. These efforts lead to the identification of ML216 and related analogs, which possess potent BLM inhibition and exhibit selectivity over related helicases. Moreover, these compounds demonstrated cellular activity by inducing sister chromatid exchanges, a hallmark of Bloom syndrome.

Genome-Wide Association Study of Body Conformation Traits in a Three-Way Crossbred Commercial Pig Population.

Body conformation is the most direct production index, which can fully reflect pig growth status and is closely related to critical economic traits. In this study, we conducted a genome-wide association study (GWAS) on body conformation traits in a population of 1518 Duroc × (Landrace × Yorkshire) commercial pigs. These traits included body length (BL), body height (BH), chest circumference (CC), abdominal circumference (AC), and waist circumference (WC). Both the mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) approaches were employed for the analysis. Our findings revealed 60 significant single nucleotide polymorphisms (SNPs) associated with these body conformation traits in the crossbred pig population. Specifically, sixteen SNPs were significantly associated with BL, three SNPs with BH, thirteen SNPs with CC, twelve SNPs with AC, and sixteen SNPs with WC. Moreover, we identified several promising candidate genes located within the genomic regions associated with body conformation traits. These candidate genes include INTS10, KIRREL3, SOX21, BMP2, MAP4K3, SOD3, FAM160B1, ATL2, SPRED2, SEC16B, and RASAL2. Furthermore, our analysis revealed a novel significant quantitative trait locus (QTL) on SSC7 specifically associated with waist circumference, spanning an 84 kb interval. Overall, the identification of these significant SNPs and potential candidate genes in crossbred commercial pigs enhances our understanding of the genetic basis underlying body conformation traits. Additionally, these findings provide valuable genetic resources for pig breeding programs.

Experimental Study on Repairing the Mechanical Characteristics of Oil-Contaminated Silty Clay in Ancient Dike with Modified Lime Mortar.

Flood-controlled ancient dikes play a significant role in flood control and have received widespread attention as historical and cultural symbols. Flood-controlled ancient dikes often undergo disasters, and research on their repair is receiving increasing attention from experts and scholars. This article studies the control of seepage and bank slope instability in flood-controlled ancient dikes. Starting from the repair of ancient dike materials, three types of work are carried out: a test of soil's mechanical properties, finite element numerical simulation, and repair technology research. The research results show that the soil of the ancient dike site has hardened after being contaminated with waste oil from catering. The strength index of the ancient dike soil decreases and shows brittleness when the water content is 15% and the oil content exceeds 6%. The strength index and permeability coefficient of oil-contaminated soil improved using modified lime mortar (MLM), which was achieved using the method of MLM to repair oil contaminated soil. When the MLM content was 10% and the oil content was 6%, the friction angle of the soil sample reached its maximum value. When the MLM content was the same, the higher the density of the soil sample, the greater the friction angle and cohesion and the smaller the permeability coefficient. Establishing a finite element numerical model, through comparative analysis, it was found that after MLM remediation of oil-contaminated soil, the extreme hydraulic gradient of the ancient dike decreased by 31.3%, and the extreme safety factor of the bank slope stability increased by 31.2%. MLM pressure grouting technology was used to improve the soil during the remediation of contaminated soil at the ancient dike site. Through on-site drilling inspection, the effective diffusion radius of MLM grouting was obtained, and the plane layout and grouting depth of MLM pressure grouting were determined. The on-site water injection permeability test showed that using MLM pressure grouting technology can effectively repair oil-contaminated soil in the ancient dike while reducing the permeability coefficient by 8-15%.

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes.

Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.