Sustainability Assessment of Water Resources Use in 31 Provinces in China: A Combination Method of Entropy Weight and Cloud Model.

As a fundamental and strategic resource, water is a crucial controlling element of ecosystem and natural environment and it plays an irreplaceable role in maintaining and promoting the sustainable development of the economy and society. To achieve the sustainable development of society, the economy and ecology, it is necessary to assess and improve the sustainability of water resources use. Based on the Human-Resource-Nature approach, this paper constructed an indicator system for the sustainability assessment of water resources use (ISSAWRU) in China from three perspectives: water resources condition, socio-economy and ecological environment. A five-level hierarchy of assessment indicators was established. Based on the entropy weight method and the cloud model which took both fuzziness and randomness into account, this paper established an entropy-cloud-based assessment model for the sustainability assessment of water resources use in 31 provinces in China in 2019. The assessment results were compared with results obtained by the TOPSIS method to test their reliability. Finally, a comprehensive and in-depth analysis of the sustainability of water resources use in China was conducted. According to the results, water resources per capita had a weighting of 0.306 and the greatest impact on the sustainable use of water resources. In addition, water structure, agricultural water use efficiency, forest coverage, and so on, had a significant impact on the sustainable use of water resources in China. The overall level of sustainability of water resources use in 31 provinces in China was not high-42% of the regions have unsustainable water resources use and there was a clear spatial distribution trend. The sustainability level of water resources use was higher in the southeast and economically developed regions. Therefore, each region should develop measures to guarantee water security based on the local conditions. This research helps policy makers to figure out the contributing factors associated with sustainability of water resources use and to set relevant rules and regulations to promote the use of water resources in a sustainable way.

RNA Sequencing-Associated Study Identifies GmDRR1 as Positively Regulating the Establishment of Symbiosis in Soybean.

In soybean (Glycine max)-rhizobium interactions, the type III secretion system (T3SS) of rhizobium plays a key role in regulating host specificity. However, the lack of information on the role of T3SS in signaling networks limits our understanding of symbiosis. Here, we conducted an RNA sequencing analysis of three soybean chromosome segment substituted lines, one female parent and two derived lines with different chromosome-substituted segments of wild soybean and opposite nodulation patterns. By analyzing chromosome-linked differentially expressed genes in the substituted segments and quantitative trait loci (QTL)-assisted selection in the substituted-segment region, genes that may respond to type III effectors to mediate plant immunity-related signaling were identified. To narrow down the number of candidate genes, QTL assistant was used to identify the candidate region consistent with the substituted segments. Furthermore, one candidate gene, GmDRR1, was identified in the substituted segment. To investigate the role of GmDRR1 in symbiosis establishment, GmDRR1-overexpression and RNA interference soybean lines were constructed. The nodule number increased in the former compared with wild-type soybean. Additionally, the T3SS-regulated effectors appeared to interact with the GmDDR1 signaling pathway. This finding will allow the detection of T3SS-regulated effectors involved in legume-rhizobium interactions.

QTL analysis of nodule traits and the identification of loci interacting with the type III secretion system in soybean.

Symbiotic nitrogen fixation is the main source of nitrogen for soybean growth. Since the genotypes of rhizobia and soybean germplasms vary, the nitrogen-fixing ability of soybean after inoculation also varies. A few studies have reported that quantitative trait loci (QTLs) control biological nitrogen fixation traits, even soybean which is an important crop. The present study reported that the Sinorhizobium fredii HH103 gene rhcJ belongs to the tts (type III secretion) cluster and that the mutant HH103ΩrhcJ can clearly decrease the number of nodules in American soybeans. However, few QTLs of nodule traits have been identified. This study used a soybean (Glycine max (L.) Merr.) 'Charleston' × 'Dongnong 594' (C × D, n = 150) recombinant inbred line (RIL). Nodule traits were analysed in the RIL population after inoculation with S. fredii HH103 and the mutant HH103ΩrhcJ. Plants were grown in a greenhouse with a 16-h light cycle at 26 °C and an 8-h dark cycle at 18 °C. Then, 4 weeks after inoculation, plants were harvested for evaluation of nodule traits. Through QTL mapping, 16 QTLs were detected on 8 chromosomes. Quantitative PCR (qRT-PCR) and RNA-seq analysis determined that the genes Glyma.04g060600, Glyma.18g159800 and Glyma.13g252600 might interact with rhcJ.

Identification of Soybean Genes Whose Expression is Affected by the Ensifer fredii HH103 Effector Protein NopP.

In some legume⁻rhizobium symbioses, host specificity is influenced by rhizobial nodulation outer proteins (Nops). However, the genes encoding host proteins that interact with Nops remain unknown. We generated an Ensifer fredii HH103 NopP mutant (HH103ΩNopP), and analyzed the nodule number (NN) and nodule dry weight (NDW) of 10 soybean germplasms inoculated with the wild-type E. fredii HH103 or the mutant strain. An analysis of recombinant inbred lines (RILs) revealed the quantitative trait loci (QTLs) associated with NopP interactions. A soybean genomic region containing two overlapping QTLs was analyzed in greater detail. A transcriptome analysis and qRT-PCR assay were used to identify candidate genes encoding proteins that interact with NopP. In some germplasms, NopP positively and negatively affected the NN and NDW, while NopP had different effects on NN and NDW in other germplasms. The QTL region in chromosome 12 was further analyzed. The expression patterns of candidate genes Glyma.12g031200 and Glyma.12g073000 were determined by qRT-PCR, and were confirmed to be influenced by NopP.