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.

Research on multiple effects of fixed-asset investment on energy consumption--by three strata of industry in China.

Fixed-asset investment directly affects energy consumption through purchasing and upgrading energy-saving equipment on the one hand, and indirectly affects energy consumption by expanding output scale on the other hand. This paper analyzes the multiple effects of fixed-asset investment on energy consumption by three strata of industry in China during 1991-2017. The econometric methods based on VAR model such as Johansen co-integration test and Granger causality test (linear Granger causality test and non-linear Granger causality test) are utilized to explore the long-run stable equilibrium relationships and causal interactions between fixed-asset investment and energy consumption. And the mediation test is performed by employing the bias-corrected non-parametric percentile bootstrap method combined with causal steps approach to obtain the direct and indirect effects of fixed-asset investment on energy consumption. Our study indicates that there are long-run stable equilibrium relationships between fixed-asset investment and energy consumption by three strata of industry. Bidirectional causalities exist in secondary and tertiary industries between fixed-asset investment and their respective energy consumption, and a unidirectional causality exists in primary industry from fixed-asset investment to energy consumption. The fixed-asset investment in primary industry directly suppresses its energy consumption, while indirectly promotes its energy consumption through its value added. And the fixed-asset investment in secondary industry not only directly promotes its energy consumption but also indirectly promotes its energy consumption through its value added.

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 QTNs Controlling Seed Protein Content in Soybean Using Multi-Locus Genome-Wide Association Studies.

Protein content (PC), an important trait in soybean (Glycine max) breeding, is controlled by multiple genes with relatively small effects. To identify the quantitative trait nucleotides (QTNs) controlling PC, we conducted a multi-locus genome-wide association study (GWAS) for PC in 144 four-way recombinant inbred lines (FW-RILs). All the FW-RILs were phenotyped for PC in 20 environments, including four locations over 4 years with different experimental treatments. Meanwhile, all the FW-RILs were genotyped using SoySNP660k BeadChip, producing genotype data for 109,676 non-redundant single-nucleotide polymorphisms. A total of 129 significant QTNs were identified by five multi-locus GWAS methods. Based on the 22 common QTNs detected by multiple GWAS methods or in multiple environments, pathway analysis identified 8 potential candidate genes that are likely to be involved in protein synthesis and metabolism in soybean seeds. Using superior allele information for 22 common QTNs in 22 elite and 7 inferior lines, we found higher superior allele percentages in the elite lines and lower percentages in the inferior lines. These findings will contribute to the discovery of the polygenic networks controlling PC in soybean, increase our understanding of the genetic foundation and regulation of PC, and be useful for molecular breeding of high-protein soybean varieties.

Towards low carbon based economic development: Shanghai as a C40 city.

As a result of its rapid industrialization process, China has become the greatest emitter of carbon dioxide world-wide. Consequently, Shanghai - the most industrialized city in China - is facing serious challenges arising from carbon emissions and climate change in general. The main question of this paper is: How can Shanghai continue its economic growth, while controlling the negative consequences of its energy use and production in a responsible way? For the approach, it explores the use of the C40 framework, as an application and specification of new synergy seeking approaches, such as Value Sensitive Design. The C40 Cities Climate Leadership Group is a global city-level network to address climate change and promote world-class projects to reduce greenhouse gas emissions. In this paper, a quantitative analysis of Shanghai's energy trends is made as well as a SWOT analysis to map and evaluate its current environmental, social, economic and political characteristics. Three main challenges are presented, related to institutional inclusiveness, global relations, and long-term innovation. In view of the initiatives, targets, and the whole network of the C40 movement, this paper concludes that Shanghai is strongly recommended to fully use the C40 framework in creating a sustainable and responsible future.