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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.
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Mapeo Cromosómico , Glycine max , Sitios de Carácter Cuantitativo , Semillas , Glycine max/genética , Glycine max/metabolismo , Semillas/genética , Semillas/metabolismo , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Agua/metabolismo , Solubilidad , FenotipoRESUMEN
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 < 0.001], and no healing (HR, 5.45; 95% CI, 2.28-13.00; p < 0.001) were associated with an increased risk of major outcomes. Conclusion: Patients with CD who achieved TH showed improved prognosis compared to those who achieved MH only. Baseline LCR and BWT might predict TH.
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KEY MESSAGE: Three QTLs associated with low-temperature tolerance were identified by genome-wide association analysis, and 15 candidate genes were identified by haplotype analysis and gene expression analyses. Low temperature is a critical factor affecting the geographical distribution, growth, development, and yield of soybeans, with cold stress during seed germination leading to substantial productivity loss. In this study, an association panel comprising 260 soybean accessions was evaluated for four germination traits and four cold tolerance index traits, revealing extensive variation in cold tolerance. Genome-wide association study (GWAS) identified 10 quantitative trait nucleotides (QTNs) associated with cold tolerance, utilizing 30,799 single nucleotide polymorphisms (SNPs) and four GWAS models. Linkage disequilibrium (LD) analysis positioned these QTNs within three cold-tolerance quantitative trait loci (QTL) and, with QTL19-1, was positioned by three multi-locus models, underscoring its importance as a key QTL. Integrative haplotype analysis, supplemented by transcriptome analysis, uncovered 15 candidate genes. The haplotypes within the genes Glyma.18G044200, Glyma.18G044300, Glyma.18G044900, Glyma.18G045100, Glyma.19G222500, and Glyma.19G222600 exhibited significant phenotypic variations, with differential expression in materials with varying cold tolerance. The QTNs and candidate genes identified in this study offer substantial potential for marker-assisted selection and gene editing in breeding cold-tolerant soybeans, providing valuable insights into the genetic mechanisms underlying cold tolerance during soybean germination.
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Frío , Germinación , Glycine max , Haplotipos , Desequilibrio de Ligamiento , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Glycine max/genética , Glycine max/crecimiento & desarrollo , Germinación/genética , Estudio de Asociación del Genoma Completo , Fenotipo , Estudios de Asociación Genética , Mapeo Cromosómico/métodos , Genes de PlantasRESUMEN
In this study, leveraging the tunable surface groups of MXene, the two-dimensional (2D) Nb2CTx with OH terminal (NC) was synthesized. 2D ZnIn2S4 (ZIS) nanosheets were prepared with the aid of sodium citrate, enhancing the exposure ratio of active (110) facet. On this basis, 2D/2D ZnIn2S4/Nb2CTx heterojunctions were fabricated to improve photocatalytic hydrogen evolution reaction (HER) performance. The optimized 6 wt%Nb2CTx/ZnIn2S4-450 (6NC/ZIS-450) photocatalyt exhibits a remarkable HER rate of 3603 µmol g-1h-1, which is 10 times superior to that of the original ZnIn2S4. Its apparent quantum efficiency (AQE) at 380 nm reaches 14.9 %. Meanwhile, even after 5 rounds of HER, the activity of 2D/2D ZnIn2S4/Nb2CTx heterojunction remained at 90 %, far superior to that of pure ZnIn2S4 (34 % and 31 %). Energy band structure analysis and density functional theory (DFT) calculation indicate that Nb2CTx adsorbed with OH exhibit a low work function. By serving as a hole cocatalyst, it effectively boosts the photocatalytic HER rate of ZnIn2S4/Nb2CTx heterojunction and inhibits the photocorrosion of ZnIn2S4. This unique insight, via hole transport highways and increased exposure of active facets, effectively enhances the activity and stability of sulfides photocatalysts.
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Nucleotide-binding site and leucine-rich repeat (NLR) proteins are activated by detecting pathogen effectors, which in turn trigger host defenses and cell death. Although many NLRs have been identified, the mechanisms responsible for NLR-triggered defense responses are still poorly understood. In this study, through a genome-wide association study approach, we identified a novel NLR gene, Blast Resistance Gene 8 (BRG8), which confers resistance to rice blast and bacterial blight diseases. BRG8 overexpression and complementation lines exhibit enhanced resistance to both pathogens. Subcellular localization assays showed that BRG8 is localized in both the cytoplasm and the nucleus. Additional evidence revealed that nuclear-localized BRG8 can enhance rice immunity without a hypersensitive response (HR)-like phenotype. We also demonstrated that the coiled-coil domain of BRG8 not only physically interacts with itself but also interacts with the KNOX â ¡ protein HOMEOBOX ORYZA SATIVA59 (HOS59). Knockout mutants of HOS59 in the BRG8 background show enhanced resistance to Magnaporthe oryzae strain CH171 and Xoo strain CR4, similar to that of the BRG8 background. By contrast, overexpression of HOS59 in the BRG8 background will compromise the HR-like phenotype and resistance response. Further analysis revealed that HOS59 promotes the degradation of BRG8 via the 26S proteasome pathway. Collectively, our study highlights HOS59 as an NLR immune regulator that fine-tunes BRG8-mediated immune responses against pathogens, providing new insights into NLR associations and functions in plant immunity.
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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.
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Tiller angle is a key agricultural trait that establishes plant architecture, which in turn strongly affects grain yield by influencing planting density in rice. The shoot gravity response plays a crucial role in the regulation of tiller angle in rice, but the underlying molecular mechanism is largely unknown. Here, we report the identification of the BIG TILLER ANGLE2 (BTA2), which regulates tiller angle by controlling the shoot gravity response in rice. Loss-of-function mutation of BTA2 dramatically reduced auxin content and affected auxin distribution in rice shoot base, leading to impaired gravitropism and therefore a big tiller angle. BTA2 interacted with AUXIN RESPONSE FACTOR7 (ARF7) to modulate rice tiller angle through the gravity signaling pathway. The BTA2 protein was highly conserved during evolution. Sequence variation in the BTA2 promoter of indica cultivars harboring a less expressed BTA2 allele caused lower BTA2 expression in shoot base and thus wide tiller angle during rice domestication. Overexpression of BTA2 significantly increased grain yield in the elite rice cultivar Huanghuazhan under appropriate dense planting conditions. Our findings thus uncovered the BTA2-ARF7 module that regulates tiller angle by mediating the shoot gravity response. Our work offers a target for genetic manipulation of plant architecture and valuable information for crop improvement by producing the ideal plant type.
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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.
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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.
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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.
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Glycine max , Fitomejoramiento , Glycine max/genética , Proteínas de Soja/genética , Benchmarking , ChinaRESUMEN
Atomic thick 2D materials hold great potential as building blocks to construct highly permeable membranes, yet the permeability of laminar 2D material membranes is still limited by their irregularity sheep track-like interlayer channels. Herein, a supramolecular-mediated strategy to induce the regular assembly of high-throughput 2D nanofluidic channels based on host-guest interactions is proposed. Inspired by the characteristics of motorways, supramolecular-mediated ultrathin 2D membranes with broad and continuous regular water transport channels are successfully constructed using graphene oxide (GO) as an example. The prepared membrane achieves an ultrahigh water permeability (369.94 LMH bar-1) more than six times higher than that of the original membranes while maintaining dye rejection above 98.5%, which outperforms the reported 2D membranes. Characterization and simulation results show that the introduction of hyaluronate-grafted ß-cyclodextrin not only expands the interlayer channels of GO membranes but also enables the membranes to operate stably under harsh conditions with the help of host-guest interactions. This universal supramolecular assembly strategy provides new opportunities for the preparation of 2D membranes with high separation performance and reliable and stable nanofluidic channels.
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In this work, potassium acetate (KAc) was added during the synthesis of a Zn-Fe based metal-organic framework (Fe-ZIF-8) to increase the fixed amount of Fe while simultaneously enhancing the number of pores. Electrospinning was utilized to embed KAc-modified Fe-ZIF-8 (Fe-ZIF-8-Ac) into the polyacrylonitrile nanofiber mesh, to obtain a network composite (Fe@NC-Ac) with hierarchical porous structure. Fe@NC-Ac was co-pyrolyzed with thiourea, resulting in Fe, N, S co-doped carbon electrocatalyst. The electrochemical tests indicated that the prepared catalyst displayed relatively remarkable oxygen reduction reaction (ORR) catalytic activity, with an onset potential (Eonset) of 1.08 V (vs. reversible hydrogen electrode, RHE) and a half-wave potential (E1/2) of 0.94 V, both higher than those of the commercial Pt/C (Eonset = 0.95 V and E1/2 = 0.84 V), respectively. Assembled into Zn-air batteries, the optimized catalyst exhibited higher open circuit voltage (1.698 V) and peak power density (90 mW cm-2) than those of the commercial 20 wt% Pt/C (1.402 V and 80 mW cm-2), respectively. This work provided a straightforward manufacturing strategy for the design of hierarchical porous carbon-based ORR catalysts with desirable performance.
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Genomic prediction (GP) uses single nucleotide polymorphisms (SNPs) to establish associations between markers and phenotypes. Selection of early individuals by genomic estimated breeding value shortens the generation interval and speeds up the breeding process. Recently, methods based on deep learning (DL) have gained great attention in the field of GP. In this study, we explore the application of Transformer-based structures to GP and develop a novel deep-learning model named GPformer. GPformer obtains a global view by gleaning beneficial information from all relevant SNPs regardless of the physical distance between SNPs. Comprehensive experimental results on five different crop datasets show that GPformer outperforms ridge regression-based linear unbiased prediction (RR-BLUP), support vector regression (SVR), light gradient boosting machine (LightGBM) and deep neural network genomic prediction (DNNGP) in terms of mean absolute error, Pearson's correlation coefficient and the proposed metric consistent index. Furthermore, we introduce a knowledge-guided module (KGM) to extract genome-wide association studies-based information, which is fused into GPformer as prior knowledge. KGM is very flexible and can be plugged into any DL network. Ablation studies of KGM on three datasets illustrate the efficiency of KGM adequately. Moreover, GPformer is robust and stable to hyperparameters and can generalize to each phenotype of every dataset, which is suitable for practical application scenarios.
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Estudio de Asociación del Genoma Completo , Modelos Genéticos , Humanos , Genotipo , Teorema de Bayes , Genómica/métodos , Fenotipo , Polimorfismo de Nucleótido SimpleRESUMEN
Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01423-y.
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Necrosis caused by soybean mosaic virus (SMV) has not been specifically distinguished from susceptible symptoms. The molecular mechanism for the occurrence of necrosis is largely overlooked in soybean genetic research. Field evaluation reveals that SMV disease seriously influences soybean production as indicated by decreasing 22.4% ~ 77.0% and 8.8% ~ 17.0% of yield and quality production, respectively. To expand molecular mechanism behind necrotic reactions, transcriptomic data obtained from the asymptomatic, mosaic, and necrotic pools were assessed. Compared between asymptomatic and mosaic plants, 1689 and 1752 up- and down-regulated differentially expressed genes (DEGs) were specifically found in necrotic plants. Interestingly, the top five enriched pathways with up-regulated DEGs were highly related to the process of the stress response, whereas the top three enriched pathways with down-regulated DEGs were highly related to the process of photosynthesis, demonstrating that defense systems are extensively activated, while the photosynthesis systems were severely destroyed. Further, results of the phylogenetic tree based on gene expression pattern and an amino acid sequence and validation experiments discovered three PR1 genes, Glyma.15G062400, Glyma.15G062500, and Glyma.15G062700, which were especially expressed in necrotic leaves. Meanwhile, exogenous salicylic acid (SA) but not methyl jasmonate (MeJA) could induce the three PR1 gene expressions on healthy leaves. Contrastingly, exogenous SA obviously decreased the expression level of Glyma.15G062400, Glyma.15G062500, and concentration of SMV, but increased Glyma.15G062700 expression in necrotic leaves. These results showed that GmPR1 is associated with the development of SMV-induced necrotic symptoms in soybean. Glyma.15G062400, Glyma.15G062500, and Glyma.15G062700 is up-regulated in necrotic leaves at the transcriptional levels, which will greatly facilitate a better understanding of the mechanism behind necrosis caused by SMV disease. Supplementary information: The online version contains supplementary material available at 10.1007/s11032-022-01351-3.
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A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01372-6.
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Biofilm-based biological nitrification is widely used for ammonia removal, while hasn't been explored for ammonia analysis. The stumbling block is the coexist of nitrifying and heterotrophic microbes in real environment resulting in non-specific sensing. Herein, an exclusive ammonia sensing nitrifying biofilm was screened from natural bioresource, and a bioreaction-detection system for the on-line analysis of environmental ammonia based on biological nitrification was reported. The nitrifying microbes were aggregated into a nitrifying biofilm through a result-oriented bioresource enrichment strategy. The predominant nitrifying population and progressive surface reaction in the plug flow bioreactor led to the exclusive and exhaustive ammonia biodegradation for the establishment of a novel analytical method. The on-line ammonia monitoring prototype achieved complete biodegradation for determining ammonium nitrogen within 5 min and showed exceptional reliability in long-term real sample measurements without frequent calibration. This work offers a low-threshold natural screening paradigm for developing sustainable bioresource-based analytical technologies.
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Amoníaco , Nitrificación , Amoníaco/metabolismo , Reproducibilidad de los Resultados , Reactores Biológicos , BiopelículasRESUMEN
Biochemical oxygen demand (BOD) is a water quality parameter of vital importance. Rapid BOD analysis methods have emerged to simplify the five-day BOD (BOD5) measurement protocol. However, their universal implementations are restricted by the tricky environmental matrix (including environmental microbes, contaminants, ionic compositions, etc.). Here, an in situ and self-adaptive BOD bioreaction sensing system consisting of a "gut-like" microfluidic coil bioreactor with self-renewed biofilm was proposed for the establishment of a rapid, resilient and reliable BOD determination method. With the spontaneous surface adhesion of environmental microbial populations, the biofilm was colonized in situ on the inner surface of the microfluidic coil bioreactor. Exploiting the environmental domestication during every real sample measurement, the biofilm was capable of self-renewal to adapt to the environmental changes and exhibited representative biodegradation behaviors. The aggregated abundant, adequate and adapted microbial populations in the BOD bioreactor rendered a total organic carbon (TOC) removal rate of 67.7% within a short hydraulic retention time of 99 s. As validated by an online BOD prototype, exceptional analytical performance was achieved in terms of reproducibility (relative standard deviation of 3.7%), survivability (inhibition by pH and metal ion interference of <20%) and accuracy (relative error of -5.9% to 9.7%). This work rediscovered the interactive effects of the environmental matrix on BOD assays and demonstrated an instructive attempt by making use of the environment to develop practical online BOD monitoring devices for water quality assessments.
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Técnicas Biosensibles , Oxígeno , Reproducibilidad de los Resultados , Biopelículas , Análisis de la Demanda Biológica de Oxígeno , Calidad del Agua , Técnicas Biosensibles/métodosRESUMEN
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.
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Asymmetric intermolecular C-H functionalization of pyridines at C3 is unprecedented. Herein, we report the first examples of such transformations: specifically, C3-allylation of pyridines via tandem borane and iridium catalysis. First, borane-catalyzed pyridine hydroboration generates nucleophilic dihydropyridines; then, the dihydropyridine undergoes enantioselective iridium-catalyzed allylation; and finally, oxidative aromatization with air as the oxidant gives the C3-allylated pyridine. This protocol provides direct access to C3-allylated pyridines with excellent enantioselectivity (up to >99% ee) and is suitable for late-stage functionalization of pyridine-containing drugs.