Global dissection of the recombination landscape in soybean using a high-density 600K SoySNP array.

Recombination is crucial for crop breeding because it can break linkage drag and generate novel allele combinations. However, the high-resolution recombination landscape and its driving forces in soybean are largely unknown. Here, we constructed eight recombinant inbred line (RIL) populations and genotyped individual lines using the high-density 600K SoySNP array, which yielded a high-resolution recombination map with 5636 recombination sites at a resolution of 1.37 kb. The recombination rate was negatively correlated with transposable element density and GC content but positively correlated with gene density. Interestingly, we found that meiotic recombination was enriched at the promoters of active genes. Further investigations revealed that chromatin accessibility and active epigenetic modifications promoted recombination. Our findings provide important insights into the control of homologous recombination and thus will increase our ability to accelerate soybean breeding by manipulating meiotic recombination rate.

Rational Design of Porous Ionic Liquids for Coupling Natural Gas Purification with Waste Gas Conversion.

Removal of trace impurities for natural gas purification coupled with waste gas conversion is highly desired in industry. We here report a type of porous ionic liquids (PILs) that can realize the continuous flow separation of CH4 /CO2 /H2 S and the conversion of the captured H2 S to useful products. The PILs are synthesized through a step-by-step surface modification of ionic liquids (ILs) onto UiO-66-OH nanocrystals. The introduction of free tertiary amine groups on the nanocrystal surface endows these PILs with an exceptional ability to enrich H2 S from CO2 and CH4 with impressive selectivity, while the permanent pores of UiO-66-OH act as containers to store an exceptionally higher amount of the selectively captured H2 S than the corresponding nonporous ILs. Simultaneously, the tertiary amines as dual functional moieties offer effective catalytic sites for the conversion of the H2 S stored in PILs into 3-mercaptoisobutyric acid, a key intermediate required for the synthesis of Captopril (an antihypertensive drug). Molecular dynamics, density functional theory calculations and Grand Canonical Monte Carlo simulations help understand both the mechanisms of separation and catalysis performance, confirming that the tertiary amines as well as the permanent pores in UiO-66-OH play vital roles in the whole procedure.

Fine mapping QTL and mining genes for protein content in soybean by the combination of linkage and association analysis.

Soybean is one main source of dietary protein; therefore, improving protein content is an important objective in breeding programs. There is a significant negative correlation between protein and oil content, which influenced mapping quantitative trait locus (QTL) and quantitative trait nucleotides for these two traits. In this study, a linkage map was created with 2232 single-nucleotide polymorphism markers for the four-way recombinant inbred line (FW-RIL) population derived from the cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19), and then conditional and unconditional QTL analyses were carried out by inclusive complete interval mapping based on the phenotypic data of protein and oil content collected in 10 different environments. As shown in the results of linkage analysis, a total of 85 QTL have been detected. We have performed association analysis using 109,676 markers after quality filtering for FW-RIL, and the results have shown that a total of 60 QTNs were detected. We have performed association analysis using 63,306 markers after quality filtering for resource population, and the results have shown that a total of 123 QTNs were detected. We have combined linkage and association analysis, and there are six QTNs verified by FW-RIL and resource population. We have performed pathway analysis on the genes in these six QTN attenuation regions, and the result shows that a total of four candidate genes are related to the synthesis or metabolism of soybean protein. These findings will facilitate marker-assisted selection and molecular breeding of soybean.

Mapping QTL/QTN and mining candidate genes for plant height and its response to planting densities in soybean [Glycine max (L.) Merr.] through a FW-RIL population.

Plant height (PH) determines the morphology and seed yield of soybean, so it is an important breeding target, which is controlled by multiple genes and affected by plant density. In this research, it was used about a four-way recombinant inbred lines (FW-RIL) with 144 families constructed by double cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19) as experimental materials, with the purpose to map QTL/QTN associated with PH under densities of 2.2×105 plant/ha (D1) and 3×105 plant/ha (D2) in five environments. The results showed that response of PH to densities varied in accordance to genotypes among environments. A total of 26 QTLs and 13 QTNs were identified specifically in D1; 20 QTLs and 21 QTNs were identified specifically in D2. Nine QTLs and one QTN were discovered commonly in two densities. Fifteen QTLs and 9 QTNs were repeatedly detected by multiple statistical methods, densities, or environments, which could be considered stable. Eighteen QTLs were detected, as well as 7 QTNs underlying responses of PH to density increment. Six QTNs, co-located in the interval of QTL, were detected in more than two environments or methods with a longer genome length over 3000 kb. Based on gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, five genes were predicted as candidates, which were likely to be involved in growth and development of PH. The results will help elucidate the genetic basis and improve molecular assistant selection of PH. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01209-0.

Holographic patterning of high-performance on-chip 3D lithium-ion microbatteries.

As sensors, wireless communication devices, personal health monitoring systems, and autonomous microelectromechanical systems (MEMS) become distributed and smaller, there is an increasing demand for miniaturized integrated power sources. Although thin-film batteries are well-suited for on-chip integration, their energy and power per unit area are limited. Three-dimensional electrode designs have potential to offer much greater power and energy per unit area; however, efforts to date to realize 3D microbatteries have led to prototypes with solid electrodes (and therefore low power) or mesostructured electrodes not compatible with manufacturing or on-chip integration. Here, we demonstrate an on-chip compatible method to fabricate high energy density (6.5 µWh cm(-2)⋅µm(-1)) 3D mesostructured Li-ion microbatteries based on LiMnO2 cathodes, and NiSn anodes that possess supercapacitor-like power (3,600 µW cm(-2)⋅µm(-1) peak). The mesostructured electrodes are fabricated by combining 3D holographic lithography with conventional photolithography, enabling deterministic control of both the internal electrode mesostructure and the spatial distribution of the electrodes on the substrate. The resultant full cells exhibit impressive performances, for example a conventional light-emitting diode (LED) is driven with a 500-µA peak current (600-C discharge) from a 10-µm-thick microbattery with an area of 4 mm(2) for 200 cycles with only 12% capacity fade. A combined experimental and modeling study where the structural parameters of the battery are modulated illustrates the unique design flexibility enabled by 3D holographic lithography and provides guidance for optimization for a given application.

High Volumetric Capacity Three-Dimensionally Sphere-Caged Secondary Battery Anodes.

High volumetric energy density secondary batteries are important for many applications, which has led to considerable efforts to replace the low volumetric capacity graphite-based anode common to most Li-ion batteries with a higher energy density anode. Because most high capacity anode materials expand significantly during charging, such anodes must contain sufficient porosity in the discharged state to enable the expansion, yet not excess porosity, which lowers the overall energy density. Here, we present a high volumetric capacity anode consisting of a three-dimensional (3D) nanocomposite formed in only a few steps which includes both a 3D structured Sn scaffold and a hollow Sn sphere within each cavity where all the free Sn surfaces are coated with carbon. The anode exhibits a high volumetric capacity of ∼1700 mA h cm(-3) over 200 cycles at 0.5C, and a capacity greater than 1200 mA h cm(-3) at 10C. Importantly, the anode can even be formed into a commercially relevant ∼100 µm thick form. When assembled into a full cell the anode shows a good compatibility with a commercial LiMn2O4 cathode. In situ TEM observations confirm the electrode design accommodates the necessary volume expansion during lithiation.

High Full-Electrode Basis Capacity Template-Free 3D Nanocomposite Secondary Battery Anodes.

A high full-electrode basis capacity secondary battery anode consisting of a template-free 3D nanostructured Fe3O4/C composite is presented. On a full electrode basis, the nanocomposite exhibits attractive electrochemical performance including a volumetric capacity of 1064 mAh cm(-3), which significantly exceeds both the practical (≈300 mAh cm(-3)) and theoretical (837 mAh cm(-3)) capacity of a commercial graphite-based anode.

Completely Inorganic Deep Eutectic Solvents for Efficient and Recyclable Liquid-Liquid Interface Catalysis.

Organic acid-based deep eutectic solvents (DESs) as catalysts always suffer from weak stability and low recyclability due to the accumulation of organic oxidative products in the DES phase. Herein, a completely inorganic deep eutectic solvent (IDES) ZnCl2/PA with zinc chloride (ZnCl2) and phosphoric acid (PA) as precursors is constructed to realize liquid-liquid interface catalysis for desulfurization of fuel and product self-separation for the first time. Owing to the inorganic nature, the organic oxidative products are accumulated at the interface between the IDES and fuel rather than the IDES phase. With this unique feature, the IDES can be reused for at least 15 times without any further treatment in oxidative desulfurization process, showing a state-of-the-art cycle-regeneration stability. Moreover, compared with the reported organic DESs, the IDES also reveals more attractive catalytic oxidative desulfurization performance. Experimental and theoretical studies indicate that the strong coordination Zn···O═P and the strong adsorption energy between IDES and sulfides enhance the activation of H2O2 to reactive oxygen species, leading to the superior catalytic performance in oxidative desulfurization of fuel.

Bio-Inspired Representation Learning for Visual Attention Prediction.

Visual attention prediction (VAP) is a significant and imperative issue in the field of computer vision. Most of the existing VAP methods are based on deep learning. However, they do not fully take advantage of the low-level contrast features while generating the visual attention map. In this article, a novel VAP method is proposed to generate the visual attention map via bio-inspired representation learning. The bio-inspired representation learning combines both low-level contrast and high-level semantic features simultaneously, which are developed by the fact that the human eye is sensitive to the patches with high contrast and objects with high semantics. The proposed method is composed of three main steps: 1) feature extraction; 2) bio-inspired representation learning; and 3) visual attention map generation. First, the high-level semantic feature is extracted from the refined VGG16, while the low-level contrast feature is extracted by the proposed contrast feature extraction block in a deep network. Second, during bio-inspired representation learning, both the extracted low-level contrast and high-level semantic features are combined by the designed densely connected block, which is proposed to concatenate various features scale by scale. Finally, the weighted-fusion layer is exploited to generate the ultimate visual attention map based on the obtained representations after bio-inspired representation learning. Extensive experiments are performed to demonstrate the effectiveness of the proposed method.

Detecting QTL and Candidate Genes for Plant Height in Soybean via Linkage Analysis and GWAS.

Soybean is an important global crop for edible protein and oil, and plant height is a main breeding goal which is closely related to its plant shape and yield. In this research, a high-density genetic linkage map was constructed by 1996 SNP-bin markers on the basis of a recombinant inbred line population derived from Dongnong L13 × Henong 60. A total of 33 QTL related to plant height were identified, of which five were repeatedly detected in multiple environments. In addition, a 455-germplasm population with 63,306 SNP markers was used for multi-locus association analysis. A total of 62 plant height QTN were detected, of which 26 were detected repeatedly under multiple methods. Two candidate genes, Glyma.02G133000 and Glyma.05G240600, involving in plant height were predicted by pathway analysis in the regions identified by multiple environments and backgrounds, and validated by qRT-PCR. These results enriched the soybean plant height regulatory network and contributed to molecular selection-assisted breeding.

Preparation of Activated Carbon Doped with Graphene Oxide Porous Materials and Their High Gas Adsorption Performance.

It is still a great challenge to develop a new porous carbon adsorbent with excellent separation performance and to recover low-concentration CH4 in coal mine gas. This work provides a new idea for the study of CH4 adsorption on activated carbon (AC) composites. Composite materials with microporous structures were prepared from coconut-shell activated carbon (CAC) doped with graphene oxide (GO) by a chemical activation process in this paper. The expansion and dissociation of GO at high temperatures indirectly improve the specific surface area (SSA) of the composite. The interlayer aggregation is reduced, the activation effect is improved, and a new low-cost adsorption material is prepared. The SSA of CAC-50 is more than 3000 m2·g-1. A high SSA and a narrow pore size distribution lead to a higher total adsorption capacity of CH4. The breakthrough test also confirmed that AC/GOs had a better adsorption capacity for CH4. The separation performance of the CH4/N2 mixture is not good at room temperature, which is due to the influence of a high SSA and average pore size. As a low-cost and rich material, CAC has a wide range of application prospects. The composite is a potential material for recovering low-concentration CH4 from the coal mine, which is worthy of attention. In the future, the selectivity of AC/GOs to CH4 can be increased by loading functional groups or modification.

A Novel Strategy to Enhance the Performance of CO2 Adsorption Separation: Grafting Hyper-cross-linked Polyimide onto Composites of UiO-66-NH2 and GO.

Graphene oxide (GO) is widely used to improve the pore structure, dispersion capacity, adsorption selectivity, resistance to acids and bases, and thermal stability of metal-organic frameworks (MOFs). However, it remains a daunting challenge to enhance selectivity simply by modifying the pore surface polarity and producing a suitable pore structure for CO2 molecules through a combination of GO with MOFs. Herein, we demonstrate a novel porous hyper-cross-linked polyimide-UiO-graphene composite adsorbent for CO2 capture via in situ chemical knitting and condensation reactions. Specifically, a network of polyimides rich in carbonyl and nitrogen atoms with amino terminations was synthesized via the reaction of 4,4'-oxydiphthalic anhydride (ODPA) and 2,4,6-trimethyl-1,3-phenylenediamine (DAM). The product plays a crucial role in the separation of CO2 from N2. As expected, the resulting composite (PI-UiO/GO-1) exhibited a 3-fold higher CO2 capacity (8.24 vs 2.8 mmol·g-1 at 298 K and 30 bar), 4.2 times higher CO2/N2 selectivity (64.71 vs 15.43), and significantly improved acid-base resistance stability compared with those values of pristine UiO-66-NH2. Furthermore, breakthrough experiments verified that the porous composites can effectively separate CO2 from simulated fuel gas (CO2/N2 = 15/85 vol %) with great potential in industrial applications. More importantly, this strategy can be extended to prepare other MOF-based composites. This clearly advances the development of MOF-polymer materials for gas capture.

Transforming Metal-Organic Frameworks into Porous Liquids via a Covalent Linkage Strategy for CO2 Capture.

Porous liquids (PLs), an emerging kind of liquid materials with permanent porosity, have attracted increasing attention in gas capture. However, directly turning metal-organic frameworks (MOFs) into PLs via a covalent linkage surface engineering strategy has not been reported. Additionally, challenges including reducing the cost and simplifying the preparation process are daunting. Herein, we proposed a general method to transform Universitetet i Oslo (UiO)-66-OH MOFs into PLs by surface engineering with organosilane (OS) and oligomer species via covalent bonding linkage. The oligomer species endow UiO-66-OH with superior fluidity at room temperature. Meanwhile, the resulting PLs showed great potential in both CO2 adsorption and CO2/N2 selective separation. The residual porosity of PLs was verified by diverse characterizations and molecular simulations. Besides, CO2 selective capture sites were determined by grand canonical Monte Carlo (GCMC) simulation. Furthermore, the universality of the covalent linkage surface engineering strategy was confirmed using different classes of oligomer species and another MOF (ZIF-8-bearing amino groups). Notably, this strategy can be extended to construct other PLs by taking advantages of the rich library of oligomer species, thus making PLs promising candidates for further applications in energy and environment-related fields, such as gas capture, separation, and catalysis.

QTL for Main Stem Node Number and Its Response to Plant Densities in 144 Soybean FW-RILs.

Although the main stem node number of soybean [Glycine max (L.) Merr. ] is an important yield-related trait, there have been limited studies on the effect of plant density on the identification of quantitative trait loci (QTL) for main stem node number (MSNN). To address this issue, here, 144 four-way recombinant inbred lines (FW-RILs) derived from Kenfeng 14, Kenfeng 15, Heinong 48, and Kenfeng 19 were used to identify QTL for MSNN with densities of 2.2 × 105 (D1) and 3 × 105 (D2) plants/ha in five environments by linkage and association studies. As a result, the linkage and association studies identified 40 and 28 QTL in D1 and D2, respectively, indicating the difference in QTL in various densities. Among these QTL, five were common in the two densities; 36 were singly identified for response to density; 12 were repeatedly identified by both response to density and phenotype of two densities. Thirty-one were repeatedly detected across various methods, densities, and environments in the linkage and association studies. Among the 24 common QTL in the linkage and association studies, 15 explained a phenotypic variation of more than 10%. Finally, Glyma.06G094400, Glyma.06G147600, Glyma.19G160800.1, and Glyma.19G161100 were predicted to be associated with MSNN. These findings will help to elucidate the genetic basis of MSNN and improve molecular assistant selection in high-yield soybean breeding.

Evaluation and management of fungal-infected carrot seeds.

Carrot (Daucus carota L.), which is one of the 10 most important vegetable crops worldwide, is an edible root vegetable desired for its taste as well as its medicinal uses. However, a fungus isolated from carrot seeds was observed to substantially decrease the germination rate. The isolate was identified as Alternaria alternata based on morphological and molecular characteristics as well as a phylogenetic tree. The maximum seed infection rate of selected carrot cultivars was approximately 60%, with the main infection site just underneath the seed shell. Additionally, the germination rate of infected seeds decreased by 28.7%. However, the seed infection rate varied among the examined carrot cultivars. Regarding the effects of chemical fungicides, the optimal treatment involved immersing seeds in amistar top suspension concentrate (SC) (effective concentration of 0.65 g/L) for 6 h, which effectively killed the fungi inside the carrot seeds. The results of this study provide a theoretical basis for the development of efficient methods for preventing the infection of carrot seeds by specific fungi and increasing the germination rate and vigour index.

Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies.

Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties.

Linkage Analysis and Multi-Locus Genome-Wide Association Studies Identify QTNs Controlling Soybean Plant Height.

Plant height is an important target for soybean breeding. It is a typical quantitative trait controlled by multiple genes and is susceptible to environmental influences. Here, we carried out phenotypic analysis of 156 recombinant inbred lines derived from "Dongnong L13" and "Henong 60" in nine environments at four locations over 6 years using interval mapping and inclusive composite interval mapping methods. We performed quantitative trait locus (QTL) analysis by applying pre-built simple-sequence repeat maps. We detected 48 QTLs, including nine significant QTLs detected by multiple methods and in multiple environments. Meanwhile, genotyping of all lines using the SoySNP660k BeadChip produced 54,836 non-redundant single-nucleotide polymorphism (SNP) genotypes. We used five multi-locus genome-wide association analysis methods to locate 10 quantitative trait nucleotides (QTNs), four of which overlap with previously located QTLs. Five candidate genes related to plant height are predicted to lie within 200 kb of these four QTNs. We identified 19 homologous genes in Arabidopsis, two of which may be associated with plant height. These findings further our understanding of the multi-gene regulatory network and genetic determinants of soybean plant height, which will be important for breeding high-yielding soybean.

Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping.

Soybean varieties suitable for high planting density allow greater yields. However, the seed protein and oil contents, which determine the value of this crop, can be influenced by planting density. Thus, it is important to understand the genetic basis of the responses of different soybean genotypes to planting density. In this study, we quantified the protein and oil contents in a four-way recombinant inbred line (FW-RIL) soybean population under two planting densities and the response to density. We performed quantitative trait locus (QTL) mapping using a single nucleotide polymorphism (SNP) linkage map generated by inclusive composite interval mapping. We identified 14 QTLs for protein content and 17 for oil content at a planting density of 2.15 × 105 plant/ha (D1) and 14 QTLs for protein content and 20 for oil content at a planting density 3.0 × 105 plant/ha (D2). Among the QTLs detected, two oil-content QTLs was detected at both plant densities. In addition, we identified 38 QTLs for the responses of protein and oil contents to planting density. Of the QTLs detected, 70 were identified in previous studies, while 33 were newly identified. Fourty-five QTLs accounted for over 10% of the phenotypic variation of the corresponding trait, based on 23 QTLs at a marker interval distance of ~600 kb detected under different densities and with the responses to density difference. Pathway analysis revealed four candidate genes involved in protein and oil biosynthesis/metabolism. These results improve our understanding of the genetic underpinnings of protein and oil biosynthesis in soybean, laying the foundation for enhancing protein and oil contents and increasing yields in soybean.

Mapping developmental QTL for plant height in soybean [Glycine max (L.) Merr.] using a four-way recombinant inbred line population.

Plant height (PH) is an important trait in soybean, as taller plants may have higher yields but may also be at risk for lodging. Many genes act jointly to influence PH throughout development. To map the quantitative trait loci (QTL) controlling PH, we used the unconditional variable method (UVM) and conditional variable method (CVM) to analyze PH data for a four-way recombinant inbred line (FW-RIL) population derived from the cross of (Kenfeng14 × Kenfeng15) × (Heinong48 × Kenfeng19). We identified 7, 8, 16, 19, 15, 27, 17, 27, 22, and 24 QTL associated with PH at 10 developmental stages, respectively. These QTL mapped to 95 genomic regions. Among these QTL, 9 were detected using UVM and CVM, and 89 and 66 were only detected by UVM or CVM, respectively. In total, 36 QTL controlling PH were detected at multiple developmental stages and these made unequal contributions to genetic variation throughout development. Among 19 novel regions discovered in our study, 7 could explain over 10% of the phenotypic variation and contained only one single QTL. The unconditional and conditional QTL detected here could be used in molecular design breeding across the whole developmental procedure.

Identification of QTLs related to the vertical distribution and seed-set of pod number in soybean [Glycine max (L.) Merri].

Pod number is an important factor that influences yield in soybean. Here, we used two associated recombinant inbred line (RIL) soybean populations, RIL3613 (containing 134 lines derived from Dongnong L13 × Heihe 36) and RIL6013 (composed of 156 individuals from Dongnong L13 × Henong 60), to identify quantitative trait loci (QTLs) regulating the vertical distribution and quantity of seeds and seed pods. The numbers of pods were quantified in the upper, middle, and lower sections of the plant, as well as in the plants as a whole, and QTLs regulating these spatial traits were mapped using an inclusive complete interval mapping method. A total of 21 and 26 QTLs controlling pod-number-related traits were detected in RIL3613 and RIL6013, respectively, which explained 1.25-11.6698% and 0.0001-7.91% of the phenotypic variation. A total of 34 QTLs were verified by comparison with previous research, were identified in both populations, or were found to regulate multiple traits, indicating their authenticity. These results enhance our understanding of the vertical distribution of pod-number-related traits and support molecular breeding for seed yield.