Deep sequencing of the microRNA expression in fall dormant and non-dormant alfalfa

AbstractMicroRNAs (miRNAs) play a critical role in post-transcriptional gene regulation that down-regulates target genes by mRNA degradation or translational repression. Evidence is increasing for their crucial roles during plant development. Identification of miRNAs at the global genome-level by high-throughput sequencing is essential to functionally characterize miRNAs in plants. Alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage legumes worldwide. Fall dormancy is an adaptive character related to the biomass production and winter survival in alfalfa. However, little is known about miRNA-mediated developmental regulation of fall dormancy in alfalfa. Here, we provide detailed experimental methods and analysis pipeline in our study to identify miRNAs that were responsive to fall dormancy (Fan W et al., Genome-wide identification of different dormant Medicago sativa L. microRNAs in response to fall dormancy, submitted for publication) for reproducible research. The data generated in our work provide meaningful information for understanding the roles of miRNAs in response to seasonal change and growth regulation in alfalfa

expression in adenocarcinoma of the

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Non-negligible greenhouse gases from urban sewer system

Abstract Background The urban sewer system is an important component of urban water infrastructure for sewage collection and transportation, and in-sewer transportation of sewage can cause multitudinous contaminant degradations which lead to formation of gaseous products. Although the greenhouse gases of methane and carbon dioxide have been confirmed to consist in the gaseous products, the mechanisms of greenhouse gas generation were unclear and the significances of greenhouse gases emission from sewers were generally underestimated. Results In this study, 3 years of monitoring was conducted to evaluate the greenhouse gases emission in 37-km-long urban sewer systems covering 13 km2. The results showed that the emission of carbon dioxide and methane was extensively existing in sewers, and especially, exhibited a characteristic of regional difference. In order to reveal the formation mechanism of carbon dioxide and methane in sewers, the metagenomic approach was utilized to analyze the annotated pathways and homologous bio-enzymes, and it indicated that fourteen pivotal annotated pathways were involved in the carbon dioxide and methane generation. According to the metagenomics and 3-year monitoring results, the total amounts of carbon dioxide and methane emission in sewers were calculated by the transformation venation of contaminants (such as methyl alcohol, methylamine and acetic acid along branch sewer, sub-main sewer and main sewer, respectively). The calculation results showed that the total greenhouse gas emissions in sewer were calculated to be 199 t/day in Xi’an, and if scaling up as population proportion, the greenhouse gas emission from sewer systems in China could be 30,685 t/day. Comparing with the greenhouse gas emissions from different metropolises (New York City, London and Tokyo) and industries (dairy farms, automobile production and steel enterprises), the amount of greenhouse gases produced by the urban sewer system is much higher. Conclusions This study revealed the transformation pathways of contaminants which promoted the generation of greenhouse gases in sewers. Based on this analysis, the greenhouse gas emissions along sewer systems were calculated. The results indicate that the greenhouse gas emission from sewer systems is non-negligible, and should be attracted sufficient attention

Digital gene-expression of alfalfa saponin extract on laying hens

Cardiovascular disease is a major cause of death worldwide, so people are advised to limit their intake of dietary cholesterol [1]. Egg consumption has been seriously reduced because of the high levels of cholesterol [2]. The objective of this study was to evaluate the cholesterol metabolism effects of alfalfa saponin extract (ASE) in liver and ovary tissues using digital gene-expression (DGE) profiling analysis. The liver and ovary tissues were isolated from laying hens fed with ASE for RNA sequencing. Here, we provide detailed experimental methods and analysis pipeline in our study to identify digital gene expression of alfalfa saponin extract on laying hens and analysis pipeline published by Singh and colleagues in the PLOS ONE [3]. The data generated in our work provide meaningful information for understanding the molecular mechanisms underlying the cholesterol-lowering effects of ASE