Zhu F.,China Agricultural University |
Yuan J.-M.,China Agricultural University |
Zhang Z.-H.,China Agricultural University |
Hao J.-P.,Beijing Jinxing Golden Star Duck Center |
And 5 more authors.
Animal Genetics | Year: 2015
Breast muscle yield and feed conversion efficiency are the major breeding aims in duck breeding. Understanding the role of specific transcripts in the muscle and small intestine might lead to the elucidation of interrelated biological processes. In this study, we obtained jejunum and breast muscle samples from two strains of Peking ducks that were sorted by feed conversion ratio (FCR) and breast muscle percentage into two-tailed populations. Ten RNA-Seq libraries were developed from the pooled samples and sequenced using the Hiseq2000 platform. We created a reference duck transcript database using de novo assembly methods, which included 16 663 irredundant contigs with an N50 length of 1530 bp. This new duck reference cDNA dataset significantly improved the mapping rate for RNA-Seq data, from 50% to 70%. Mapping and annotation were followed by Gene Ontology analysis, which showed that numerous genes were differentially expressed between the low and high FCR groups. The differentially expressed genes in the jejunum were enriched in biological processes related to immune response and immune response activation, whereas those in the breast muscle were significantly enriched in biological processes related to muscle cell differentiation and organ development. We identified new candidate genes, that is, PCK1, for improving the FCR and breast muscle yield of ducks and obtained much better reference duck transcripts. This study suggested that de novo assembly is essential when applying transcriptome analysis to a species with an incomplete genome. © 2015 Stichting International Foundation for Animal Genetics. Source
Liu X.,China Agricultural University |
Li Y.,China Agricultural University |
Liu J.,China Agricultural University |
Zhong M.,China Agricultural University |
And 2 more authors.
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | Year: 2015
Eggs have become main sources of protein choice for Chinese consumers due to the fact that they are both inexpensive and rich in vitamins, minerals and protein. However, as a perishable product, the quality of fresh eggs deteriorates continuously during the period from their leaving the farm until final consumption or use in manufacturing. With consumers' increasing awareness and concern for food safety, increasing attention is being given to the shelf life of eggs through the supply chain. To develop a prediction model of the shelf life of fresh eggs, two types of model were developed and tested, including a kinetic model and a back-propagation (BP) neural network model. A sample of 115 eggs was collected on the same day from the same farm layer-hen house subsequently for use in simulating quality deterioration under laboratory conditions. The experiments were conducted at constant temperatures of 5, 25 and 35℃ to cover the normal range of temperatures that can occur under real egg storage conditions and the experimental results were used to construct the kinetic and BP neural network models, and validation of model shelf-life prediction was compared with actual egg shelf life. Three layers of BP neural network were constructed with Haugh units, yolk index and temperature as the input layer parameters, 10 nodes in the hidden layer and remaining day's duration of storage as the output layer's parameter. It was found that the BP neural network model had a superior prediction accuracy of 95.93% compared with 90.79% of the kinetic model. Hence it can be concluded that the BP neural network model could readily be integrated as part of a quality control system setting sell or use-by-dates for consumers. ©, 2015, Chinese Society of Agricultural Machinery. All right reserved. Source
Ma T.,Chinese Academy of Agricultural Sciences |
Tu Y.,Chinese Academy of Agricultural Sciences |
Zhang N.-F.,Chinese Academy of Agricultural Sciences |
Guo J.-P.,Beijing General Station of Animal Husbandry |
And 4 more authors.
Journal of Integrative Agriculture | Year: 2015
This study aimed to investigate the effects of dietary supplementation of yeast β-glucan on the nutrient digestibility and serum profiles in pre-ruminant Holstein calves. Forty-two neonatal Holstein calves ((39.6±4.2) kg) were randomly allotted to six groups, and each was offered one of the following diets: a basal diet (control) or the basal diet supplemented with 25, 50, 75, 100 or 200 mg of yeast β-glucan kg-1 feed (dry matter basis). The basal diet consisted of a milk replacer and a starter feed. The trial lasted for 56 d. Two digestibility trials were conducted from d 14 to 20 and from d 42 to 48. Blood samples were collected on d 0, 14, 28 and 42 for serum profile analyses. On d 56, three calves from each group were slaughtered, and intestinal samples were collected to assess the villous height, crypt depth and mucosal thickness. Although feed intake was not affected by dietary treatment (P>0.05), the average daily gain (ADG) and gain-to-feed ratios were higher (P<0.05) for the calves fed 75 mg of yeast β-glucan kg-1 feed than those in the other groups. The supplementation of yeast β-glucan at 75 mg kg-1 feed increased the apparent digestibility of dry matter (DM), crude protein (CP), ether extract (EE), and phosphorus (P) (P<0.05) and the ratio of intestinal villous height to crypt depth (V/C) (P<0.05) when compared with the control group. No effects of yeast β-glucan on the serum concentrations of total protein (TP), albumin (ALB), serum urea nitrogen (SUN) and glucose (GLU) were observed (P>0.05). Compared with the control group, supplementation of yeast β-glucan decreased (P<0.05) the serum concentrations of triglycerides (TG) and total cholesterol (TC). The serum concentration of immunoglobulin G (IgG) and immunoglobulin M (IgM) increased quadratically (P<0.05), whereas the serum concentration of immunoglobulin A (IgA) was unaffected by dietary treatments (P>0.05). The supplementation of yeast β-glucan stimulated the enzymatic activity of alkaline phosphatase (ALP) (P<0.05) compared with the control group. The lysozyme (LYZ) concentration increased quadratically (P<0.05) with increasing yeast β-glucan levels. The results suggested that dietary supplementation of yeast β-glucan at 75 mg kg-1 feed improved nutrient digestibility, enhanced immunity by increasing the immunoglobulin concentration and stimulating ALP, and exerted no adverse effects on metabolism in pre-ruminant calves. © 2015 Chinese Academy of Agricultural Sciences. Source
XU F.,Chinese Academy of Agricultural Sciences |
REN K.,Beijing General Station of Animal Husbandry |
YANG Y.-Z.,Beijing General Station of Animal Husbandry |
GUO J.-P.,Beijing General Station of Animal Husbandry |
And 4 more authors.
Journal of Integrative Agriculture | Year: 2015
The detection of chemical contaminants is critical to ensure dairy safety. These contaminants include veterinary medicines, antibiotics, pesticides, heavy metals, mycotoxins, and persistent organic pollutants (POPs). Immunoassays have recently been used to detect contaminants in milk because of their simple operation, high speed, and low cost. This article describes the latest developments in the most important component of immunoassays - antibodies, and then reviews the four major substrates used for immunoassays (i.e., microplates, membranes, gels, and chips) as well as their use in the detection of milk contaminants. The paper concludes with prospects for further applications of these immunoassays. © 2015 Chinese Academy of Agricultural Sciences. Source