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Rice blast, caused by the fungus Magnaporthe oryzae, reduces rice yields by 10% to 35%. Incorporating blast resistance genes into breeding programs is an effective strategy to combat this disease. Understanding the genetic variants that confer resistance is crucial to this strategy. The gene Bsr-d1 encodes a C2H2-like transcription factor, and its recessive allele confers broad-spectrum resistance against infections by various strains of M. oryzae. In this study, we investigated the molecular evolution of the rice blast resistance gene bsr-d1 in a representative population consisting of 827 cultivated and wild rice accessions. Our results revealed that wild rice exhibited significantly higher nucleotide diversity, with polymorphic regions primarily concentrated in the promoter region, in contrast to indica and japonica rice varieties. The Bsr-d1 gene displayed significant differentiation between indica and japonica rice varieties, with the bsr-d1 resistance allele being unique to indica rice. Haplotype network and phylogenetic analyses suggested that the bsr-d1 resistance allele most likely originated from Oryza nivara in the region adjacent to the Indian Peninsula and the Indochina Peninsula. Moreover, we explored the utilization of bsr-d1 resistance alleles in China and designed a pair of DNA primers based on the polymorphic sites for the detection of the bsr-d1 resistance gene. In summary, our study uncovering the origin and evolution of bsr-d1 will enhance our understanding of resistance gene variation and expedite the resistance breeding process.

Abstract Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15–11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

Abstract Objectives We aimed to develop MRI-based radiomic models (RMs) to improve the diagnostic accuracy of radiologists in characterizing intestinal fibrosis in patients with Crohn’s disease (CD). Methods This retrospective study included patients with refractory CD who underwent MR before surgery from November 2013 to September 2021. Resected bowel segments were histologically classified as none-mild or moderate-severe fibrosis. RMs based on different MR sequence combinations (RM1: T2WI and enhanced-T1WI; RM2: T2WI, enhanced-T1WI, diffusion-weighted imaging [DWI], and apparent diffusion coefficient [ADC]); RM3: T2WI, enhanced-T1WI, DWI, ADC, and magnetization transfer MRI [MTI]), were developed and validated in an independent test cohort. The RMs’ diagnostic performance was compared to that of visual interpretation using identical sequences and a clinical model. Results The final population included 123 patients (81 men, 42 women; mean age: 30.26 ± 7.98 years; training cohort, n = 93; test cohort, n = 30). The area under the receiver operating characteristic curve (AUC) of RM1, RM2, and RM3 was 0.86 (p = 0.001), 0.88 (p = 0.001), and 0.93 (p = 0.02), respectively. The decision curve analysis confirmed a progressive improvement in the diagnostic performance of three RMs with the addition of more specific sequences. All RMs performance surpassed the visual interpretation based on the same MR sequences (visual model 1, AUC = 0.65, p = 0.56; visual model 2, AUC = 0.63, p = 0.04; visual model 3, AUC = 0.77, p = 0.002), as well as the clinical model composed of C-reactive protein and erythrocyte sedimentation rate (AUC = 0.60, p = 0.13). Conclusions The RMs, utilizing various combinations of conventional, DWI and MTI sequences, significantly enhance radiologists’ ability to accurately characterize intestinal fibrosis in patients with CD. Critical relevance statement The utilization of MRI-based RMs significantly enhances the diagnostic accuracy of radiologists in characterizing intestinal fibrosis. Key Points MRI-based RMs can characterize CD intestinal fibrosis using conventional, diffusion, and MTI sequences. The RMs achieved AUCs of 0.86–0.93 for assessing fibrosis grade. MRI-radiomics outperformed visual interpretation for grading CD intestinal fibrosis. Graphical Abstract

Abstract Objectives Soybean is an important feed and oil crop in the world due to its high protein and oil content. China has a collection of more than 43,000 soybean germplasm resources, which provides a rich genetic diversity for soybean breeding. However, the rich genetic diversity poses great challenges to the genetic improvement of soybean. This study reports on the de novo genome assembly of HJ117, a soybean variety with high protein content of 52.99%. These data will prove to be valuable resources for further soybean quality improvement research, and will aid in the elucidation of regulatory mechanisms underlying soybean protein content. Data description We generated a contiguous reference genome of 1041.94 Mb for HJ117 using a combination of Illumina short reads (23.38 Gb) and PacBio long reads (25.58 Gb), with high-quality sequence coverage of approximately 22.44× and 24.55×, respectively. HJ117 was developed through backcross breeding, using Jidou 12 as the recurrent parent and Chamoshidou as the donor parent. The assembly was further assisted by 114.5 Gb Hi-C data (109.9×), resulting in a contig N50 of 19.32 Mb and scaffold N50 of 51.43 Mb. Notably, Core Eukaryotic Genes Mapping Approach (CEGMA) assessment and Benchmarking Universal Single-Copy Orthologs (BUSCO) assessment results indicated that most core eukaryotic genes (97.18%) and genes in the BUSCO dataset (99.4%) were identified, and 96.44% of the genomic sequences were anchored onto twenty pseudochromosomes.

The global energy crisis is increasingly severe, and the construction industry, as a high-energy-consuming sector, is one of the main sources of carbon emissions. As a result, the development of green buildings has become imperative. Shear walls, as a common structural form in buildings, have their wall layout ratio significantly influencing the amount of building materials used, which is crucial for material reduction and carbon emission reduction during construction. This paper innovatively introduces the concept of the optimal shear wall layout ratio, focusing on the analysis of the variation patterns of wall ratios and their associated carbon emissions in both traditional and optimal models. Various optimal models are designed with shear wall length as the variable, and the relationship between shear wall layout ratio and carbon emissions is examined. Under a seismic fortification intensity of level 7 (0.1 g), the layout ratio of the optimal models does not exceed that of the traditional model (4.24%), and the carbon emissions are reduced by approximately 11%. A reasonable design of the shear wall layout ratio not only reduces carbon emissions in buildings and improves reverse performance but also promotes a dual enhancement in both economic and environmental benefits in the construction industry.

Abstract To evaluate the stability of a lined rock cavern (LRC) for compressed air energy storage (CAES) containing a weak interlayer during blasting in the adjacent cavern, a newly excavated tunnel-type LRC was taken as the research object. By combining similar model tests and numerical simulation, the dynamic responses and deformation characteristics of the LRC for CAES under joint action of factors including the gas storage pressure, weak interlayer, and blast load were studied. The influences of the thickness, dip angle, and location of the weak interlayer on deformation of the LRC were discussed. The results show that as the gas storage pressure increases, the rate of change in strains in regions of the LRC near the weak interlayer is accelerated, and the gas storage pressure more significantly influences the sealing layer and lining than the surrounding rocks. The presence of the weak interlayer causes stress concentration in the LRC and increases the circumferential strain and residual strain of the LRC. Under the blast load, the right-side wall of the LRC shows the poorest stability, and the presence of the weak interlayer results in the energy loss in the propagation process of stress waves and an increment of peak strain in regions of the LRC around the interlayer. When the weak interlayer is separated from the LRC, as the thickness of the weak interlayer increases, the confinement of surrounding rocks at the interlayer on the LRC reduces and the circumferential strain increases. As the dip angle of the interlayer increases, the peak strain in the right upper side of the LRC grows significantly. As the distance from the weak interlayer to the LRC boundary increases, the circumferential strain in regions of the LRC near the interlayer decreases significantly. If the distance is less than 0.2r, the increment of the distance significantly affects the peak strain.

Background: Transmural healing (TH) has emerged as a potential treatment goal for Crohn’s disease (CD). However, further research is needed to confirm its benefits and risk factors associated with TH remain unclear. Objectives: We aimed to assess the value of TH based on magnetic resonance enterography (MRE) in Chinese CD patients regarding the long-term outcomes and its associated factors. Design: Retrospective, observational cohort study. Methods: Patients with CD diagnosed by colonoscopy and MRE examination between 2015 and 2022 were included. All patients were evaluated with endoscopy together with MRE within 6–12 months after baseline and followed up for at least 6 months after evaluation. The primary endpoint was the occurrence of major outcomes during the follow-up, including drug escalation, hospitalization, and surgery. The cumulative probabilities of major outcomes were calculated using Kaplan–Meier survival curves. Logistic regression analyses were used to predict TH within 6–12 months after baseline. Results: A total of 175 patients were included in the study. Of these, 69 (39.4%) patients achieved mucosal healing (MH), but only 34 (19.4%) of them achieved TH. The median follow-up duration was 17.4 months (interquartile range, 11.6–25.5), and major outcomes occurred in 58.3% of patients. A lower occurrence rate of major outcomes was noted in patients who achieved TH than in those who achieved MH only ( p = 0.012). The baseline lymphocyte/C-reactive protein ratio (LCR) [odds ratio (OR), 1.60; 95% confidence interval (CI), 1.02–2.50; p = 0.039] and bowel wall thickness (BWT) (OR, 0.72; 95% CI, 0.59–0.90; p = 0.003) were independent predictors associated with TH. According to multivariate Cox regression analysis, low LCR [hazard ratio (HR), 2.34; 95% CI, 1.51–3.64; p

Reinforced concrete structures play a pivotal role in island and reef engineering projects. Given the resource constraints typical of island regions, substituting traditional manufactured sand aggregate with reef limestone not only reduces reliance on river sand but also addresses the issue of disposing of waste reef limestone slag generated during excavation. However, the performance characteristics of reef limestone concrete, particularly its bond strength with reinforcing steel, warrant further investigation. This is particularly true for the bond–slip behavior of the reinforcement. This study aims to elucidate the effects of various parameters on the bond performance between steel and reef limestone concrete through central pullout tests. These parameters include the type and diameter of the reinforcement, bond length, and loading rate. The investigation encompasses the analysis of load–slip curves, bond failure modes, and variations in bond stress. Additionally, using the Abaqus software, a numerical simulation was conducted to analyze the mesoscopic stress characteristics, thereby revealing the mechanisms of bond formation and failure modes between steel reinforcement and reef limestone concrete. The results indicate that the bond–slip curve for reef limestone concrete reinforced with ribbed rebars and Glass Fiber-Reinforced Polymer (GFRP) rebars can be broadly categorized into four phases: minor slip, slip, decline, and residual, with the residual phase exhibiting a wave-like pattern. The predominant failure modes in reef limestone concrete are either pulling out or splitting. The bond stress in reef limestone concrete decreases with an increase in rebar diameter and bond length; conversely, it increases with the loading rate, although the ultimate slip decreases. The mesoscopic failure characteristics of reinforced reef limestone concrete, as simulated in Abaqus, are consistent with the experimental outcomes.

Ideal plant architecture is essential for enhancing crop yields. Ideal soybean (Glycine max) architecture encompasses an appropriate plant height, increased node number, moderate seed weight, and compact architecture with smaller branch angles for growth under high-density planting. However, the functional genes regulating plant architecture are far not fully understood in soybean. In this study, we investigated the genetic basis of 12 agronomic traits in a panel of 496 soybean accessions with a wide geographical distribution in China. Analysis of phenotypic changes in 148 historical elite soybean varieties indicated that seed-related traits have mainly been improved over the past 60 years, with targeting plant architecture traits having the potential to further improve yields in future soybean breeding programs. In a genome-wide association study (GWAS) of 12 traits, we detected 169 significantly associated loci, of which 61 overlapped with previously reported loci and 108 new loci. By integrating the GWAS loci for different traits, we constructed a genetic association network and identified 90 loci that were associated with a single trait and 79 loci with pleiotropic effects. Of these 79 loci, 7 hub-nodes were strongly linked to at least three related agronomic traits. qHub_5, containing the previously characterized Determinate 1 (Dt1) locus, was associated not only with plant height and node number (as determined previously), but also with internode length and pod range. Furthermore, we identified qHub_7, which controls three branch angle-related traits; the candidate genes in this locus may be beneficial for breeding soybean with compact architecture. These findings provide insights into the genetic relationships among 12 important agronomic traits in soybean. In addition, these studies uncover valuable loci for further functional gene studies and will facilitate molecular design breeding of soybean architecture.

Because plant mechanical strength influences plant growth and development, the regulatory mechanisms underlying cell-wall synthesis deserve investigation. Rice mutants are useful for such research. We have identified a novel brittle culm 25 (bc25) mutant with reduced growth and partial sterility. BC25 encodes an UDP-glucuronic acid decarboxylase involved in cellulose synthesis and belongs to the UXS family. A single-nucleotide mutation in BC25 accounts for its altered cell morphology and cell-wall composition. Transmission electron microscopy analysis showed that the thickness of the secondary cell wall was reduced in bc25. Monosaccharide analysis revealed significant increases in content of rhamnose and arabinose but not of other monosaccharides, indicating that BC25 was involved in xylose synthesis with some level of functional redundancy. Enzymatic assays suggested that BC25 functions with high activity to interconvert UDP-glucuronic acid (UDP-GlcA) and UDP-xylose. GUS staining showed that BC25 was ubiquitously expressed with higher expression in culm, root and sheath, in agreement with that shown by quantitative real-time (qRT)-PCR. RNA-seq further suggested that BC25 is involved in sugar metabolism. We conclude that BC25 strongly influences rice cell wall formation.

A Fe-Co dual-metal co-doped N containing the carbon composite (FeCo-HNC) was prepared by adjusting the ratio of iron to cobalt as well as the pyrolysis temperature with the assistance of functionalized silica template. Fe1Co-HNC, which was formed with 1D carbon nanotubes and 2D carbon nanosheets including a rich mesoporous structure, exhibited outstanding oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) catalytic activities. The ORR half-wave potential is 0.86 V (vs. reversible hydrogen electrode, RHE), and the OER overpotential is 0.76 V at 10 mA cm−2 with the Fe1Co-HNC catalyst. It also displayed superior performance in zinc–air batteries. This method provides a promising strategy for the fabrication of efficient transition metal-based carbon catalysts.

Genomic selection (GS) is a marker-based selection method used to improve the genetic gain of quantitative traits in plant breeding. A large number of breeding datasets are available in the soybean database, and the application of these public datasets in GS will improve breeding efficiency and reduce time and cost. However, the most important problem to be solved is how to improve the ability of across-population prediction. The objectives of this study were to perform genomic prediction (GP) and estimate the prediction ability (PA) for seed oil and protein contents in soybean using available public datasets to predict breeding populations in current, ongoing breeding programs. In this study, six public datasets of USDA GRIN soybean germplasm accessions with available phenotypic data of seed oil and protein contents from different experimental populations and their genotypic data of single-nucleotide polymorphisms (SNPs) were used to perform GP and to predict a bi-parent-derived breeding population in our experiment. The average PA was 0.55 and 0.50 for seed oil and protein contents within the bi-parents population according to the within-population prediction; and 0.45 for oil and 0.39 for protein content when the six USDA populations were combined and employed as training sets to predict the bi-parent-derived population. The results showed that four USDA-cultivated populations can be used as a training set individually or combined to predict oil and protein contents in GS when using 800 or more USDA germplasm accessions as a training set. The smaller the genetic distance between training population and testing population, the higher the PA. The PA increased as the population size increased. In across-population prediction, no significant difference was observed in PA for oil and protein content among different models. The PA increased as the SNP number increased until a marker set consisted of 10,000 SNPs. This study provides reasonable suggestions and methods for breeders to utilize public datasets for GS. It will aid breeders in developing GS-assisted breeding strategies to develop elite soybean cultivars with high oil and protein contents.

The pioneering work in finance by Black, Scholes and Merton during the 1970s led to the emergence of the Black-Scholes (B-S) equation, which offers a concise and transparent formula for determining the theoretical price of an option. The establishment of the B-S equation, however, relies on a set of rigorous assumptions that give rise to several limitations. The non-local property of the fractional derivative (FD) and the identification of fractal characteristics in financial markets have paved the way for the introduction and rapid development of fractional calculus in finance. In comparison to the classical B-S equation, the fractional B-S equations (FBSEs) offer a more flexible representation of market behavior by incorporating long-range dependence, heavy-tailed and leptokurtic distributions, as well as multifractality. This enables better modeling of extreme events and complex market phenomena, The fractional B-S equations can more accurately depict the price fluctuations in actual financial markets, thereby providing a more reliable basis for derivative pricing and risk management. This paper aims to offer a comprehensive review of various FBSEs for pricing European options, including associated solution techniques. It contributes to a deeper understanding of financial model development and its practical implications, thereby assisting researchers in making informed decisions about the most suitable approach for their needs.

ATP-dependent SWI/SNF chromatin remodeling complexes (CRCs) are evolutionarily conserved multi-component machines that regulate transcription, replication, and genome stability in eukaryotes. SWI/SNF components play pivotal roles in development and various stress responses in plants. However, the compositions and biological functions of SWI/SNF complex subunits remain poorly understood in soybean. In this study, we used bioinformatics to identify 39 genes encoding SWI/SNF subunit distributed on the 19 chromosomes of soybean. The promoter regions of the genes were enriched with several cis-regulatory elements that are responsive to various hormones and stresses. Digital expression profiling and qRT-PCR revealed that most of the SWI/SNF subunit genes were expressed in multiple tissues of soybean and were sensitive to drought stress. Phenotypical, physiological, and molecular genetic analyses revealed that GmLFR1 (Leaf and Flower-Related1) plays a negative role in drought tolerance in soybean and Arabidopsis thaliana. Together, our findings characterize putative components of soybean SWI/SNF complex and indicate possible roles for GmLFR1 in plants under drought stress. This study offers a foundation for comprehensive analyses of soybean SWI/SNF subunit and provides mechanistic insight into the epigenetic regulation of drought tolerance in soybean.

Background: As distinct marker of proliferating cells, chromatin assembly factor-1 (CAF-1) was critical in DNA replication. However, there is paucity information about the clinical significance, functions and co-expressed gene network of CHAF1A, the major subunit in CAF-1, in cancer.Methods: Bioinformatic analysis of CHAF1A and its co-expression gene network were performed using various public databases. Functional validation of CHAF1A was applied in breast cancer.Results: Overexpression of CHAF1A was found in 20 types of cancer tissues. Elevated expression of CHAF1A was positively correlated with breast cancer progression and poor patients’ outcome. The analysis of co-expression gene network demonstrated CHAF1A was associated with not only cell proliferation, DNA repair, apoptosis, but cancer metabolism, immune system, and drug resistance. More importantly, higher expression of CHAF1A was positively correlated with immunosuppressive microenvironment and resistance to endocrine therapy and chemotherapy. Elevated expression of CHAF1A was confirmed in breast cancer tissues. Silencing of CHAF1A can significantly inhibit cell proliferation in MDA-MB-231 cells.Conclusion: The current work suggested that overexpression of CHAF1A can be used as diagnostic and poor prognostic biomarker of breast cancer. Higher expression of CHAF1A induced fast resistance to endocrine therapy and chemotherapy, it may be a promising therapeutic target and a biomarker to predict the sensitivity of immunotherapy in breast cancer.

IntroductionGenomic selection (GS) is a potential breeding approach for soybean improvement.MethodsIn this study, GS was performed on soybean protein and oil content using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) based on 1,007 soybean accessions. The SoySNP50K SNP dataset of the accessions was obtained from the USDA-ARS, Beltsville, MD lab, and the protein and oil content of the accessions were obtained from GRIN.ResultsOur results showed that the prediction accuracy of oil content was higher than that of protein content. When the training population size was 100, the prediction accuracies for protein content and oil content were 0.60 and 0.79, respectively. The prediction accuracy increased with the size of the training population. Training populations with similar phenotype or with close genetic relationships to the prediction population exhibited better prediction accuracy. A greatest prediction accuracy for both protein and oil content was observed when approximately 3,000 markers with -log10(P) greater than 1 were included.DiscussionThis information will help improve GS efficiency and facilitate the application of GS.

Objective: This review aims to provide some theoretical guidance for the precise treatment of ovarian cancer and the development of estrogen-related drugs. Mechanism: Ovarian cancer is one of the leading causes of death in gynecological cancer patients, mainly affecting middle-aged and elderly women. It has the characteristics of hidden location, strong heterogeneity and lack of specific symptoms in the early stage. Numerous studies have shown that estrogen receptor (ER) plays an important role in different types of cancer, including ovarian cancer. Accordingly, the study of ER signaling pathways and related regulatory factors in ovarian cancer cells should help us understand the pathogenesis of ovarian cancer. Findings in Brief: The expression of estrogen receptor subtypes is related to ovarian cancer gene and leads to ovarian cancer. Estrogen receptor modulators appear to be an important factor in the prognosis of patients with ovarian cancer after hormone therapy. Conclusions: This review summarizes the regulatory mechanism of ER in the occurrence and development of ovarian cancer and outlines the specific role of estrogen receptor modulators (SERMs) in the treatment and prevention of ovarian cancer.

Abstract Background Grain size and weight are important target traits determining grain yield and quality in rice. Wild rice species possess substantial elite genes that can be served as an important resource for genetic improvement of rice. In this study, we identify and validate a novel QTL on chromosome 7 affecting the grain size and weight using introgression lines from cross of Oryza sativa and Oryza minuta. Results An introgression line ‘IL188’ has been achieved from a wild species Oryza minuta (2n = 48, BBCC, W303) into O. sativa japonica Nipponbare. The F2 and F2:3 populations derived from a cross between IL188 and Nipponbare were used to map QTLs for five grain size traits, including grain length (GL), grain width (GW), grain length to width ratio (LWR), grain thickness (GT) and thousand grain weight (TGW). A total of 12 QTLs for the five grain traits were identified on chromosomes 1, 2, 3, 6, 7, and 8. The QTL-qGL7 controlling GL on chromosome 7 was detected stably in the F2 and F2:3 populations, and explained 15.09–16.30% of the phenotypic variance. To validate the effect of qGL7, eight residual heterozygous line (RHL) populations were developed through selfing four F2:3 and four F2:4 plants with different heterozygous segments for the target region. By further developing SSR and Indel markers in the target interval, qGL7 was delimited to a ~ 261 kb region between Indel marker Y7–12 and SSR marker Y7–38, which also showed significant effects on grain width and thousand grain weight. Comparing with the reference genome of Nipponbare, stop or frameshift mutations in the exon of the three putative genes LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. Scanning electron microscopy analysis of the glume’s epidermal cells showed that the cell length and width of NIL-qGL7 IL188 was higher than NIL-qGL7 Nip, indicating that qGL7 increases grain size and weight by regulating cell expansion. Conclusions In this study, we detected 12 QTLs regulating grain size and weight using an introgression line from a cross between Oryza sativa and Oryza minuta. Of these loci, we confirmed and delimited the qGL7 to a ~ 261 kb region. Three putative genes, LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. These results provide a basis for map-based cloning of the qGL7 gene and useful information for marker assisted selection in rice grain quality improvement.

High-density planting is a major way to improve crop yields. However, shade-avoidance syndrome (SAS) is a major factor limiting increased planting density. First Green Revolution addressed grass lodging problem by using dwarf/semi-dwarf genes. However, it is not suitable for soybean, which bear seeds on stalk and whose seed yield depends on plant height. Hence, mining shade-tolerant germplasms and elucidating the underlying mechanism could provide meaningful resources and information for high-yield breeding. Here, we report a high-plant density-tolerant soybean cultivar, JiDou 17, which exhibited an inactive SAS (iSAS) phenotype under high-plant density or low-light conditions at the seedling stage. A quantitative trait locus (QTL) mapping analysis using a recombinant inbred line (RIL) population showed that this iSAS phenotype is related to a major QTL, named shade-avoidance response 1 (qSAR1), which was detected. The mapping region was narrowed by a haplotype analysis into a 554 kb interval harboring 44 genes, including 4 known to be key regulators of the SAS network and 4 with a variance response to low-light conditions between near isogenic line (NIL) stems. Via RNA-seq, we identified iSAS-specific genes based on one pair of near isogenic lines (NILs) and their parents. The iSAS-specific genes expressed in the stems were significantly enriched in the “proteasomal protein catabolic” process and the proteasome pathway, which were recently suggested to promote the shade-avoidance response by enhancing PIF7 stability. Most iSAS-specific proteasome-related genes were downregulated under low-light conditions. The expression of genes related to ABA, CK, and GA significantly varied between the low- and normal-light conditions. This finding is meaningful for the cloning of genes that harbor beneficial variation(s) conferring the iSAS phenotype fixed in domestication and breeding practice.

Heterophylly, the existence of different leaf shapes and sizes on the same plant, has been observed in many flowering plant species. Yet, the genetic characteristics and genetic basis of heterophylly in soybean remain unknown. Here, two populations of recombinant inbred lines (RILs) with distinctly different leaf shapes were used to identify loci controlling heterophylly in two environments. The ratio of apical leaf shape (LSUP) to basal leaf shape (LSDOWN) at the reproductive growth stage (RLS) was used as a parameter for classifying heterophylly. A total of eight QTL were detected for RLS between the two populations and four of them were stably identified in both environments. Among them, qRLS20 had the largest effect in the JS population, with a maximum LOD value of 46.9 explaining up to 47.2% of phenotypic variance. This locus was located in the same genomic region as the basal leaf shape QTL qLSDOWN20 on chromosome 20. The locus qRLS19 had the largest effect in the JJ population, with a maximum LOD value of 15.2 explaining up to 27.0% of phenotypic variance. This locus was located in the same genomic region as the apical leaf shape QTL qLSUP19 on chromosome 19. Four candidate genes for heterophylly were identified based on sequence differences among the three parents of the two mapping populations, RT-qPCR analysis, and gene functional annotation analysis. The QTL and candidate genes detected in this study lay a foundation for further understanding the genetic mechanism of heterophylly and are invaluable in marker-assisted breeding.

Abstract Light metal hydrolysis for hydrogen supply is well suited for portable hydrogen fuel cells. The addition of catalysts can substantially aid Mg hydrolysis. However, there is a lack of clear catalytic mechanism to guide the design of efficient catalysts. In this work, the essential role of nanosized catalyst (Ni3Fe/rGO) in activating micro‐sized Mg with ultra‐rapid hydrolysis process is investigated for the first time. Here, an unprecedented content of 0.2 wt% Ni3Fe/rGO added Mg can release 812.4 mL g−1 hydrogen in just 60 s at 30 °C. Notably, an impressive performance with a hydrogen yield of 826.4 mL g−1 at 0 °C in only 30 s is achieved by the Mg‐2 wt% Ni3Fe/rGO, extending the temperature range for practical applications of hydrolysis. Moreover, the four catalysts (Ni3Fe/rGO, Ni3Fe, Ni/rGO, Fe/rGO) are designed to reveal the influence of composition, particle size, and dispersion on catalytic behavior. Theoretical studies corroborate that the addition of Ni3Fe/rGO accelerates the electron transfer and coupling processes and further provides a lower energy barrier diffusion path for hydrogen. Thus, a mechanism concerning the catalyst as migration relay is proposed. This work offers guidelines designing high‐performance catalysts especially for activating the hydrolysis of micro‐sized light weight metals.

Abstract Background Rice rooting ability is a complex agronomical trait that displays heterosis and plays an important role in rice growth and production. Only a few quantitative trait loci (QTLs) have been identified by bi-parental population. More genes or QTLs are required to dissect the genetic architecture of rice rooting ability. Results To characterize the genetic basis for rice rooting ability, we used a natural rice population, genotyped by a 90 K single nucleotide polymorphism (SNP) array, to identify the loci associated with rooting-related traits through the genome-wide association study (GWAS). Population structure analysis divided the natural population into two subgroups: indica and japonica. We measured four traits for evaluating rice rooting ability, namely root growth ability (RGA), maximum root length (MRL), root length (RL), and root number (RN). Using the association study in three panels consisting of one for the full population, one for indica, and one for japonica, 24 SNPs associated with rooting ability-related traits were identified. Through comparison of the relative expression levels and DNA sequences between germplasm with extreme phenotypes, results showed that LOC_Os05g11810 had non-synonymous variations at the coding region, which may cause differences in root number, and that the expression levels of LOC_Os04g09900 and LOC_Os04g10060 are closely associated with root length variation. Conclusions Through evaluation of the rice rooting ability-related traits and the association mapping, we provided useful information for understanding the genetic basis of rice rooting ability and also identified some candidate genes and molecular markers for rice root breeding.

Beany flavor induced by three lipoxygenases (LOXs, including LOX1, LOX2, and LOX3) restricts human consumption of soybean. It is desirable to generate lipoxygenase-free new mutant lines to improve the eating quality of soybean oil and protein products. In this study, a pooled clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) strategy targeting three GmLox genes (GmLox1, GmLox2, and GmLox3) was applied and 60 T0 positive transgenic plants were generated, carrying combinations of sgRNAs and mutations. Among them, GmLox-28 and GmLox-60 were gmlox1gmlox2gmlox3 triple mutants and GmLox-40 was a gmlox1gmlox2 double mutant. Sequencing of T1 mutant plants derived from GmLox-28, GmLox-60, and GmLox-40 showed that mutation in the GmLox gene was inherited by the next generation. Colorimetric assay revealed that plants carrying different combinations of mutations lost the corresponding lipoxygenase activities. Transgene-free mutants were obtained by screening the T2 generation of lipoxygenase-free mutant lines (GmLox-28 and GmLox-60). These transgene- and lipoxygenase-free mutants could be used for soybean beany flavor reduction without restriction by regulatory frameworks governing transgenic organisms.

Soybean is a primary meal protein for human consumption, poultry, and livestock feed. In this study, quantitative trait locus (QTL) controlling protein content was explored via genome-wide association studies (GWAS) and linkage mapping approaches based on 284 soybean accessions and 180 recombinant inbred lines (RILs), respectively, which were evaluated for protein content for 4 years. A total of 22 single nucleotide polymorphisms (SNPs) associated with protein content were detected using mixed linear model (MLM) and general linear model (GLM) methods in Tassel and 5 QTLs using Bayesian interval mapping (IM), single-trait multiple interval mapping (SMIM), single-trait composite interval mapping maximum likelihood estimation (SMLE), and single marker regression (SMR) models in Q-Gene and IciMapping. Major QTLs were detected on chromosomes 6 and 20 in both populations. The new QTL genomic region on chromosome 6 (Chr6_18844283–19315351) included 7 candidate genes and the Hap.XAA at the Chr6_19172961 position was associated with high protein content. Genomic selection (GS) of protein content was performed using Bayesian Lasso (BL) and ridge regression best linear unbiased prediction (rrBULP) based on all the SNPs and the SNPs significantly associated with protein content resulted from GWAS. The results showed that BL and rrBLUP performed similarly; GS accuracy was dependent on the SNP set and training population size. GS efficiency was higher for the SNPs derived from GWAS than random SNPs and reached a plateau when the number of markers was >2,000. The SNP markers identified in this study and other information were essential in establishing an efficient marker-assisted selection (MAS) and GS pipelines for improving soybean protein content.

Grain size, grain number per panicle, and grain weight are key agronomic traits that determine grain yield in rice. However, the molecular mechanisms coordinately controlling these traits remain largely unknown. In this study, we identified a major QTL, SMG3, that is responsible for grain size, grain number per panicle, and grain weight in rice, which encodes a MYB-like protein. The SMG3 allele from M494 causes an increase in the number of grains per panicle but produces smaller grain size and thousand grain weight. The SMG3 is constitutively expressed in various organs in rice, and the SMG3 protein is located in the nucleus. Microscopy analysis shows that SMG3 mainly produces long grains by increasing in both cell length and cell number in the length direction, which thus enhances grain weight by promoting cell expansion and cell proliferation. Overexpression of SMG3 in rice produces a phenotype with more grains but reduces grain length and weight. Our results reveal that SMG3 plays an important role in the coordinated regulation of grain size, grain number per panicle, and grain weight, providing a new insight into synergistical modification on the grain appearance quality, grain number per panicle, and grain weight in rice.

This paper investigates a two-dimensional Riemann–Liouville distributed-order space fractional diffusion equation (RLDO-SFDE). However, many challenges exist in deriving analytical solutions for fractional dynamic systems. Efficient and reliable methods need to be explored for solving the RLDO-SFDE numerically. We develop an alternating direction implicit scheme and prove that the numerical method is unconditionally stable and convergent with an accuracy of O(σ2+ρ2+τ+hx+hy). After employing an extrapolated technique, the convergence order is improved to second order in time and space. Furthermore, a fast algorithm is constructed to reduce computational costs. Two numerical examples are presented to verify the effectiveness of the numerical methods. This study may provide more possibilities for simulating diffusion complexities by fractional calculus.

AbstractCultivated soybean (Glycine max

Grain size and flag leaf angle are two important traits that determining grain yield in rice. However, the mechanisms regulating these two traits remain largely unknown. In this study, a rice long grain 5 (lg5) mutant with a large flag leaf angle was identified, and map-based cloning revealed that a single base substitution followed by a 2 bp insertion in the LOC_Os05g40384 gene resulted in larger grains, a larger flag leaf angle, and higher plant height than the wild type. Sequence analysis revealed that lg5 is a novel allele of elongated uppermost internode-1 (EUI1), which encodes a cytochrome P450 protein. Functional complementation and overexpression tests showed that LG5 can rescue the bigger grain size and larger flag leaf angle in the Xiushui11 (XS) background. Knockdown of the LG5 transcription level by RNA interference resulted in elevated grain size and flag leaf angle in the Nipponbare (NIP) background. Morphological and cellular analyses suggested that LG5 regulated grain size and flag leaf angle by promoting cell expansion and cell proliferation. Our results provided new insight into the functions of EUI1 in rice, especially in regulating grain size and flag leaf angle, indicating a potential target for the improvement of rice breeding.

Wilms tumor gene (WT1) is used as a marker for the diagnosis and prognosis of ovarian cancer. However, the molecular mechanisms involving WT1 in ovarian cancer require further study. Herein, we used bioinformatics and other methods to identify important pathways and hub genes in ovarian cancer affected by WT1. The results showed that WT1 is highly expressed in ovarian cancer and is closely related to the overall survival and progression-free survival (PFS) of ovarian cancer. In ovarian cancer cell line SKOV3, WT1 downregulation increased the mRNA expression of 638 genes and decreased the mRNA expression of 512 genes, which were enriched in the FoxO, AMPK, and the Hippo signaling pathways. The STRING online tool and Cytoscape software were used to construct a Protein-protein interaction (PPI) network and for Module analysis, and 18 differentially expressed genes (DEGs) were selected. Kaplan-Meier plotter analysis revealed that 16 of 18 genes were related to prognosis. Analysis of GEPIA datasets indicated that 7 of 16 genes were differentially expressed in ovarian cancer tissues and in normal tissues. The expression of IGFBP1 and FBN1 genes increased significantly after WT1 interference, while the expression of the SERPINA1 gene decreased significantly. The correlation between WT1 expression and that of these three genes was consistent with that of ovarian cancer tissues and normal tissues. According to the GeneMANIA online website analysis, there were complex interactions between WT1, IGFBP1, FBN1, SERPINA1, and 20 other genes. In conclusion, we have identified important signaling pathways involving WT1 that affect ovarian cancer, and distinguished three differentially expressed genes regulated by WT1 associated with the prognosis of ovarian cancer. Our findings provide evidence outlining mechanisms involving WT1 gene expression in ovarian cancer and provides a rational for novel treatment of ovarian cancer.

Escin, a natural triterpene saponin mixture obtained from the horse chestnut tree (Aesculus hippocastanum), has been used for the treatment of chronic venous insufficiency (CVI), hemorrhoids, and edema. However, it is unclear how escin protects against endothelial barrier dysfunction induced by pro‐inflammatory high mobility group protein 1 (HMGB1). Here, we report that escin can suppress (a) HMGB1‐induced overexpression of the aquaporin‐1 (AQP1) water channel in endothelial cells and (b) HMGB1‐induced increases in endothelial cell permeability. This is the first report that escin inhibits AQP1 and alleviates barrier dysfunction in HMGB1‐induced inflammatory response.

Soybean (Glycine max (L.) Merr.) is an important nutritional crop, not only as a rich source of protein and oil, but also for the production of isoflavones. There is a demand to breed soybean cultivars bearing consistently high protein, oil and isoflavone yields, yet this requires a clear heritable genetic relationship among isoflavone, protein and oil production. Here, two soybean genotypes contrasting in terms of protein, oil and isoflavone contents and their 185 F8:10 recombinant inbred lines (RILs) were employed to characterize seed protein, oil and isoflavone contents over two years of field trials. In this population, protein, but not oil, was significantly correlated with isoflavone content. A high-density genetic linkage map containing 3943 SNP markers identified through genotyping-by-sequencing (GBS) technology was constructed for further genetic analysis, whereby a total of 25 integrated isoflavone loci were identified, including qISO1, qISO 6.1, qISO 6.3 and qISO 6.4, which are newly identified QTLs. Two major QTLs identified in this study, qISO5 and qISO6.2, were fine-mapped for production of daidzein and genistein derivatives, as well as for glycitein derivatives, in the sequences between nucleotide positions 41042159 and 42098680 on chromosome 5 and between 18449510 and 19395795 on chromosome 6, which, respectively, explain 9.3–20.4% and 7.8–24.8% of the phenotypic variation in these traits. Further combination of qISO5 and qISO6.2 resulted in additive impacts on isoflavone production. Among the 13 QTLs linked with seed protein content in this study, three also colocated with QTLs for isoflavone content, indicating that seed isoflavone and protein content may be coordinately inherited. These results contribute to understanding the relationships between isoflavone and protein or oil content in soybean seeds. This knowledge could be valuable for soybean breeding programs aiming to combine consistently high isoflavone production with high protein or oil content.

Developing high yielding cultivars with outstanding quality traits are perpetual objectives throughout crop breeding operations. Confoundingly, both of these breeding objectives typically involve working with complex quantitative traits that can be affected by genetic and environmental factors. Establishing correlations of these complex traits with more easily identifiable and highly heritable traits can simplify breeding processes. In this study, two parental soybean genotypes contrasting in seed hilum size, yield, and seed quality, as well as 175 F9 recombinant inbred lines (RILs) derived from these parents, were grown in 3 years. The h2b of four hilum size, two quality and two yield traits, ranged from 0.72 to 0.87. The four observed hilum size traits exhibited significant correlation (P < 0.05) with most of seed yield and quality traits, as indicated by correlation coefficients varying from -0.35 to 0.42, which suggests that hilum size could be considered as a proxy trait for soybean yield and quality. Interestingly, among 53 significant quantitative trait loci (QTLs) with logarithm of odds (LOD) values ranging from 2.51 to 6.69 and accounting for 6.40–16.10% of genetic variation, three loci encoding hilum size, qSH6.2, qSH8, and qSH10, colocated with QTLs for seed yield and quality traits, demonstrating that genes impacting seed hilum size colocalize in part with genes acting on soybean yield and quality. As a result of the breeding efforts and field observations described in this work, it is reasonable to conclude that optimizing hilum size through selection focused on a few QTLs may be useful for breeding new high yielding soybean varieties with favorable quality characteristics.

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

Graphene oxide membranes have great potential in separation processes, but small ions rejection needs improvement for large scale applications. Here the authors manipulate the membrane’s surface charge to control selective ion transport, achieving high rejection for A2B and AB2 type salts and maintaining high water permeance.

In English teaching, developing students' reading habits has been emphasized for its critical role in promoting overall core competencies. However, in practice, many teachers and parents are not informed of the effective approaches to developing good English reading habits, hindering the overall development of students' core competencies. In light of this, an empirical study was carried out to explore the developmental features of students' English reading habits and individual, family and school factors that affect its development. A questionnaire was adopted to collect quantitative data. A total of 2,130 primary and secondary school students from China participated in the study. The results indicated that their English reading habits varied with age and gender. In terms of age, secondary school students, especially middle school students, performed better than primary school students. In terms of gender, females performed better in reading frequency, reading time and ways of reading, while males had a larger reading volume. Reading habits were found to be impacted by individual, school and family factors. Among them, age had the strongest influence on the development of English reading habits. These findings shed light on effective ways to develop English reading habits, especially in foreign-language-learning contexts.

Abstract Background Identification of the quantitative trait locus (QTL) underlying salt tolerance is a prerequisite for marker-assisted selection in the salt-tolerant breeding process. Methods In this study, the recombinant inbred lines derived from the salt-tolerant elite soybean cultivar ‘Jidou 12’ and the salt-sensitive elite cultivar ‘Ji NF 58’ were used to identify the QTL associated with salt tolerance, using both salt tolerance rating (STR) and leaf chlorophyll content (SPAD) as indicators. Results A major salt-tolerant QTL, which was flanked by SSR markers GMABAB and Barcsoyssr_03_1421 on chromosome 3, was identified based on single-marker regression, single trait composite interval mapping, and multiple interval mapping analysis. For STR, the LOD ranged from 19.8 to 20.1; R2 ranged from 44.3 to 44.7%; and the additive effect ranged from 0.876 to 0.885 among the three mapping methods. For SPAD, the LOD ranged from 10.6 to 11.0; R2 ranged from 27.0 to 27.6%; and the additive effect ranged from 1.634 to 1.679 among the three mapping methods. Conclusions In this study, a major QTL conditioning salt tolerance on chromosome 3 was identified. The DNA markers closely associated with the QTLs might be useful in marker-assisted selection for soybean salt tolerance improvement in Huanghuaihai, China.

Abstract Identifying the mechanisms underlying cognitive development in early life is a critical objective. The expression of insulin‐like growth factor binding protein 2 (IGFBP2) in the hippocampus increases during neonatal development and is associated with learning and memory, but a causal connection has not been established. Here, it is reported that neurons and astrocytes expressing IGFBP2 are distributed throughout the hippocampus. IGFBP2 enhances excitatory inputs onto CA1 pyramidal neurons, facilitating intrinsic excitability and spike transmission, and regulates plasticity at excitatory synapses in a cell‐type specific manner. It facilitates long‐term potentiation (LTP) by enhancing N‐methyl‐d‐aspartate (NMDA) receptor‐dependent excitatory postsynaptic current (EPSC), and enhances neurite proliferation and elongation. Knockout of igfbp2 reduces the numbers of pyramidal cells and interneurons, impairs LTP and cognitive performance, and reduces tonic excitation of pyramidal neurons that are all rescued by IGFBP2. The results provide insight into the requirement for IGFBP2 in cognition in early life.

Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.

This paper uses the median-of-means (MOM) method to estimate the parameters of the nonlinear regression models and proves the consistency and asymptotic normality of the MOM estimator. Especially when there are outliers, the MOM estimator is more robust than nonlinear least squares (NLS) estimator and empirical likelihood (EL) estimator. On this basis, we propose hypothesis testing Statistics for the parameters of the nonlinear regression models using empirical likelihood method, and the simulation performance shows the superiority of MOM estimator. We apply the MOM method to analyze the top 50 data of GDP of China in 2019. The result shows that MOM method is more feasible than NLS estimator and EL estimator.

The use of sterility is common in plants and multiple loci for hybrid sterility have been identified in crops such as rice. In soybean, fine-mapping and research on the molecular mechanism of male sterility is limited. Here, we identified a male-sterile soybean line, which produces larger, abnormal pollen grains that stain poorly with I2-KI. In an inheritance test, all F1 plants were fertile and the F2 and F2:3 populations conformed with the expected segregation ratio of 3:1 (fertility:sterility) (p = 0.82) and showed a 1:2:0 ratio of homozygous fertile: heterozygous fertile: homozygous sterile genotypes (p = 0.73), suggesting that the sterility was controlled by a single recessive gene (designated “mst-M”). Bulked segregant analysis showed that almost all single-nucleotide polymorphisms (SNPs; 95.92%) were distributed on chromosome 13 and 868 SNPs (95.81%) were distributed in the physical region of Chromosome 13.21877872 to Chromosome 13.22862641. Genetic mapping revealed that mst-M was flanked by W1 and dCAPS-1 with genetic distances of 0.6 and 1.8 cM, respectively. The order of the consensus markers and known sterility genes was: Satt146 – (5.0 cM) – st5 – (2.5 cM) – Satt030 – (15.3 cM) – ms6 – (5.0 cM) – Satt149 – (39.5 cM) – W1 – (0.6 cM) – mst-M – (14.1 cM) – Satt516 (7.5 cM) – ms1 – (16.3 cM) – Satt595. These results suggest that mst-M is a newly identified male-sterility gene, which represents an alternative genetic resource for developing a hybrid seed production system for soybean.

Seed dormancy is an important agronomic trait affecting grain yield and quality because of pre-harvest germination and is influenced by both environmental and genetic factors. However, our knowledge of the factors controlling seed dormancy remains limited. To better reveal the molecular mechanism underlying this trait, a genome-wide association study was conducted in an indica-only population consisting of 453 accessions genotyped using 5,291 SNPs. Nine known and new significant SNPs were identified on eight chromosomes. These lead SNPs explained 34.9% of the phenotypic variation, and four of them were designed as dCAPS markers in the hope of accelerating molecular breeding. Moreover, a total of 212 candidate genes was predicted and eight candidate genes showed plant tissue-specific expression in expression profile data from different public bioinformatics databases. In particular, LOC_Os03g10110, which had a maize homolog involved in embryo development, was identified as a candidate regulator for further biological function investigations. Additionally, a polymorphism information content ratio method was used to screen improvement footprints and 27 selective sweeps were identified, most of which harbored domestication-related genes. Further studies suggested that three significant SNPs were adjacent to the candidate selection signals, supporting the accuracy of our genome-wide association study (GWAS) results. These findings show that genome-wide screening for selective sweeps can be used to identify new improvement-related DNA regions, although the phenotypes are unknown. This study enhances our knowledge of the genetic variation in seed dormancy, and the new dormancy-associated SNPs will provide real benefits in molecular breeding.

Soybean [Glycine max (L.) Merr] is an important legume crop and its yield largely depends on root architecture (RA) and biological nitrogen fixation (BNF). However, the relationship between RA and BNF, and its genetics behind remain unclear. Here, two soybean genotypes contrasting in RA and their 175 F9:11 recombinant inbred lines (RILs) were evaluated in field. The shallow-root parent, JD12, had better nodulation and higher yield than the deep-root parent, NF58. Strong correlations between shoot dry weight (SDW) and RA or BNF traits existed in the RILs, and the shallow-root group had more and heavier nodules, as well as higher SDW. After inoculating with rhizobia, roots became shallower and bigger, showing strong synergistic interactions between RA and BNF. In total, 70 QTLs were identified for the 21 tested traits. Among them, qBNF-RA-C2, qBNF-RA-O, and qBNF-RA-B1, were newly identified QTLs for BNF and/or RA traits in soybean, which co-located with the QTLs for SDW detected presently, and with the QTLs for yield identified previously. The results together suggest that there are synergistic interactions between RA and BNF, and the QTLs identified here could be used for breeding new soybean varieties with higher yields through optimization of RA traits and BNF capacity.

Rice (Oryza sativa L.) is the only cereal crop that possesses the ability to germinate under flooded or other oxygen-deficient conditions. Rapid elongation of the coleoptile is a perfect response to flooding during germination, with coleoptile length differing among various rice varieties. Despite multiple studies have uncovered valuable information concerning this trait by focusing on the physiological metabolism of oxygen stress, the underlying genetic mechanism still remains unknown. In the present study, we screened coleoptile lengths of 432 indica varieties germinated in two environments (normal and flooded) and found more variation existing in flooded coleoptile length (FCL) rather than in normal coleoptile length (NCL). With the phenotypic data of NCL, FCL and FTI (flooding tolerance index), a genome-wide association study was performed by using 5291 single nucleotide polymorphism (SNP) markers. We detected 2, 11, and 9 significant SNPs under a mixed linear mode for NCL, FCL, and FTI, respectively. Of these SNPs, five were shared by FCL and FTI. Haplotype and phenotype effect analysis on the highest ranking locus indicated one of the two haplotypes contributed to coleoptile elongation remarkably. To better understand the controlling gene of this locus, reported expression profile data was applied. We focused on LOC_Os06g03520, a candidate gene which was highly induced by anoxia (∼507 fold). Sequence analysis in 51 varieties demonstrated Hap.2 associated perfectly with flooding tolerance. Further studies on this gene may help explore the molecular mechanism of rice flooding tolerance during germination. We believe our discoveries may conduce to isolating major genes and aid the improvement of flooding tolerance in modern breeding programs.

The japonica rice in Northeast China is famous because of its high quality. Eating and cooking qualities (ECQs) are the most important factors that determine cooked rice quality. However, the genetic basis of ECQ of japonica varieties in Northeast China needs further study. In this study, 200 japonica varieties that are widely distributed in Northeast China were collected to evaluate the physicochemical indices of grain ECQs. The distribution of each trait was concentrated without large variations. Correlation analysis indicated that gel consistency (GC) had a significantly negative correlation with gelatinization temperature (GT). By integrating various analyses including kinship calculation, principal component analysis (PCA), linkage disequilibrium (LD) analysis, and original parent investigation, we found that the japonica varieties in Northeast China exhibited a narrow genetic basis. An association study for grain ECQs was performed and eight quantitative trait loci (QTLs) were detected. ALK was the major locus that regulated GT and also significantly affecting GC. Through the linkage disequilibrium (LD) and expression pattern analysis, one possible candidate gene (LOC_Os02g29980) was predicted and required further research for validation. Additionally, a different allele of Wx was identified in the variety CH4126, and ALK was not fixed in these japonica varieties. These results further elucidate the genetic basis of ECQs of japonica varieties in Northeast China and provide local breeders some assistance for improving ECQs of rice grain in rice breeding.

Phytophthora sojae, an oomycete pathogen of soybean, causes stem and root rot, resulting in annual economic loss up to $2 billion worldwide. Varieties with P. sojae resistance are environmental friendly to effectively reduce disease damages. In order to improve the resistance of P. sojae and broaden the genetic diversity in Southern soybean cultivars and germplasm in the U.S., we established a P. sojae resistance gene pool that has high genetic diversity, and explored genomic regions underlying the host resistance to P. sojae races 1, 3, 7, 17 and 25. A soybean germplasm panel from maturity groups (MGs) IV and V including 189 accessions originated from 10 countries were used in this study. The panel had a high genetic diversity compared to the 6,749 accessions from MGs IV and V in USDA Soybean Germplasm Collection. Based on disease evaluation dataset of these accessions inoculated with P. sojae races 1, 3, 7, 17 and 25, which are publically available, five accessions in this panel were resistant to all races. Genome-wide association analysis identified a total of 32 significant SNPs, which were clustered in resistance-associated genomic regions, among those, ss715619920 was only 3kb away from the gene Glyma.14g087500, a subtilisin protease. Gene expression analysis showed that the gene was down-regulated more than 4 fold (log2 fold > 2.2) in response to P. sojae infection. The identified molecular markers and genomic regions that are associated with the disease resistance in this gene pool will greatly assist the U.S. Southern soybean breeders in developing elite varieties with broad genetic background and P. sojae resistance.

Zao5241 is an elite soybean [Glycine max (L.) Merr.] line and backbone parent. In this study, we employed iTRAQ to analyze the proteomes and protein expression profiles of Zao5241 during leaf development. We identified 1,245 proteins in all experiments, of which only 45 had been previously annotated. Among overlapping proteins between three biological replicates, 598 proteins with 2 unique peptides identified were reliably quantified. The protein datasets were classified into 36 GO functional terms, and the photosynthesis term was most significantly enriched. A total of 113 proteins were defined as being differentially expressed during leaf development; 41 proteins were found to be differently expressed between two and four week old leaves, and 84 proteins were found to be differently expressed between two and six week old leaves, respectively. Cluster analysis of the data revealed dynamic proteomes. Proteins annotated as electron carrier activity were greatly enriched in the peak expression profiles, and photosynthesis proteins were negatively modulated along the whole time course. This dataset will serve as the foundation for a systems biology approach to understanding photosynthetic development.

A vapor chamber can meet the cooling requirements of high heat flux electronic equipment. In this paper, based on a proposed vapor chamber with a side window, a vapor chamber experimental system was designed to visually study its evaporation and condensation heat transfer performance. Using infrared thermal imaging technology, the temperature distribution and the vapor⁻liquid two-phase interface evolution inside the cavity were experimentally observed. Furthermore, the evaporation and condensation heat transfer coefficients were obtained according to the measured temperature of the liquid near the evaporator surface and the vapor near the condenser surface. The effects of heat load and filling rate on the thermal resistance and the evaporation and condensation heat transfer coefficients are analyzed and discussed. The results indicate that the liquid filling rate that maximized the evaporation heat transfer coefficient was different from the liquid filling rate that maximized the condensation heat transfer coefficient. The vapor chamber showed good heat transfer performance with a liquid filling rate of 33%. According to the infrared thermal images, it was observed that the evaporation/boiling heat transfer could be strengthened by the interference of easily broken bubbles and boiling liquid. When the heat input increased, the uniformity of temperature distribution was improved due to the intensified heat transfer on the evaporator surface.

The flat two-phase thermosyphon has been recognized as a promising technique to realize uniform heat dissipation for high-heat-flux electronic devices. In this paper, a visualization experiment is designed and conducted to study the startup modes and operating states in a flat two-phase thermosyphon. The dynamic wall temperatures and gas–liquid interface evolution are observed and analyzed. From the results, the sudden startup and gradual startup modes and three quasi-steady operating states are identified. As the heat load increases, the continuous large-amplitude pulsation, alternate pulsation, and continuous small-amplitude pulsation states are experienced in sequence for the evaporator wall temperature. The alternate pulsation state can be divided into two types of alternate pulsation: lengthy single-large-amplitude-pulsation alternated with short multiple-small-amplitude-pulsation, and short single-large-amplitude-pulsation alternated with lengthy multiple-small-amplitude alternate pulsation state. During the continuous large-amplitude pulsation state, the bubbles were generated intermittently and the wall temperature fluctuated cyclically with a continuous large amplitude. In the alternate pulsation state, the duration of boiling became longer compared to the continuous large-amplitude pulsation state, and the wall temperature of the evaporator section exhibited small fluctuations. In addition, there was no large-amplitude wall temperature pulsation in the continuous small-amplitude pulsation state, and the boiling occurred continuously. The thermal performance of the alternate pulsation state in a flat two-phase thermosyphon is inferior to the continuous small-amplitude pulsation state but superior to the continuous large-amplitude pulsation state.