Effect of 1-methylcyclopropene on postharvest physiological changes of ‘Zaohong’ plum

Plum is a highly perishable fruit and postharvest fruit softening limits its shelf life. The aim of this work was to study the specific effects of 1-methylcyclopropene (1-MCP) treatment on physiological changes in ‘Zaohong’ plums. Plums were treated with 500 nL L⁻¹ 1-MCP at 20°C for 18 h followed by 20°C storage. The results showed that 1-MCP treatment significantly reduced endogenous ethylene production and the activities of ethylene biosynthetic enzymes’ (1-aminocyclopropane-1-carboxylic acid synthase, ACS and 1-aminocyclopropane-1-carboxylic acid oxidase, ACO) in plum fruit during storage when compared with untreated fruit. Although 1-MCP treatment inhibited ethylene production and 1-aminocyclopropane-1-carboxylic acid (ACC) accumulation, it did not inhibit the accumulation of N-malonyl-ACC (MACC). Higher firmness was also found in 1-MCP-treated plums than in controls. During storage, superoxide anion (O₂^−·) and hydrogen peroxide (H₂O₂) levels decreased in 1-MCP-treated fruit. 1-MCP treatment also regulated superoxide dismutase (SOD) and catalase (CAT) activities during storage. Xylanase activity was upregulated while activities of polygalacturonase (PG), pectin methyl esterase (PME) and cellulase enzymes in the fruit were downregulated by 1-MCP treatment. In conclusion, 1-MCP might be a potent compound for extending both storage period and shelf life of ‘Zaohong’ plums by suppressing ethylene biosynthesis, regulating cell wall degradation enzymes and reducing fruit softening.     

Identification and characterization of adipose triglyceride lipase (ATGL) gene in birds

Adipose triglyceride lipase (ATGL) is a triglyceride hydrolysis lipase and is generally related to lipid metabolism in animals. The ATGL gene was well studied in mammals, however very less was known in birds that differed significantly with mammals for lipid metabolism. In this study, cloning, mRNA real time and association analysis was performed to characterize the ATGL gene in birds. Results showed that the obtained ATGL gene cDNA of parrot, quail, duck were 1,651 bp (NCBI accession number: GQ221784), 1,557 bp (NCBI accession number: GQ221783) and 1,440 bp each, encoded 481-, 482- and 279-amino acid (AA) peptide, respectively. The parrot ATGL (pATGL) gene was found to predominantly express in breast muscle and leg muscle, and very higher ATGL mRNA level was also found in heart, abdominal fat and subcutaneous fat. The quail ATGL (qATGL) gene was also predominantly expressed in breast muscle and leg muscle, and then to a much lesser degree in heart. The duck ATGL (dATGL) gene was found to predominantly express in subcutaneous fat and abdominal fat, quite higher ATGL mRNA was also found in heart, spleen, breast muscle and leg muscle. Blast analyses indicated the high homology of ATGL and its patatin region, and moreover, and the active serine hydrolase motif (“GASAG” for “GXSXG”) and the glycine rich motif (“GCGFLG” for “GXGXXG”) were completely conservative among 14 species. Association analyses showed that c.950+24C>A, c.950+45C>G, c.950+73G>A, c.950+83C>T and c.950+128delA of chicken ATGL gene (cATGL) were all significantly or highly significantly with cingulated fat width (CFW) (P < 0.05 or P < 0.01), and c.777−26C>A, c.950+45C>G, c.950+73G>A and c.950+118C>T were all significantly or highly significantly with pH value of breast muscle (BMPH) (P < 0.05).     

Systems Mapping for Hematopoietic Progenitor Cell Heterogeneity

Cells with the same genotype growing under the same conditions can show different phenotypes, which is known as “population heterogeneity”. The heterogeneity of hematopoietic progenitor cells has an effect on their differentiation potential and lineage choices. However, the genetic mechanisms governing population heterogeneity remain unclear. Here, we present a statistical model for mapping the quantitative trait locus (QTL) that affects hematopoietic cell heterogeneity. This strategy, termed systems mapping, integrates a system of differential equations into the framework for systems mapping, allowing hypotheses regarding the interplay between genetic actions and cell heterogeneity to be tested. A simulation approach based on cell heterogeneity dynamics has been designed to test the statistical properties of the model. This model not only considers the traditional QTLs, but also indicates the methylated QTLs that can illustrate non-genetic individual differences. It has significant implications for probing the molecular, genetic and epigenetic mechanisms of hematopoietic progenitor cell heterogeneity.