Dataset Information

Small RNA sequencing reveals dynamic microRNA expression of important nutrient metabolism during development of Camellia oleifera fruit.

ABSTRACT: To obtain insight into the function of miRNAs in the synthesis and storage of important nutrients during the development of Camellia oleifera fruit, Illumina sequencing of flower and fruit small-RNA was conducted. The results revealed that 797 miRNAs were significantly differentially expressed between flower and fruit samples of Camellia oleifera. Through integrated GO and KEGG function annotations, it was determined that the miRNA target genes were mainly involved in metabolic pathways, plant hormone signal transduction, fruit development, mitosis and regulation of biosynthetic processes. Carbohydrate accumulation genes were differentially regulated by miR156, miR390 and miR395 in the fruit growth and development process. MiR477 is the key miRNA functioning in regulation of genes and involved in fatty acid synthesis. Additionally, miR156 also has the function of regulating glycolysis and nutrient transformation genes.

SUBMITTER: Liu XX

PROVIDER: S-EPMC6367553 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Small RNA sequencing reveals dynamic microRNA expression of important nutrient metabolism during development of Camellia oleifera fruit.

Liu Xiao-Xia XX Luo Xiao-Fang XF Luo Ke-Xin KX Liu Ya-Lin YL Pan Ting T Li Zhi-Zhang ZZ Duns Gregory J GJ He Fu-Lin FL Qin Zuo-Dong ZD

International journal of biological sciences 20190101 2

To obtain insight into the function of miRNAs in the synthesis and storage of important nutrients during the development of Camellia oleifera fruit, Illumina sequencing of flower and fruit small-RNA was conducted. The results revealed that 797 miRNAs were significantly differentially expressed between flower and fruit samples of Camellia oleifera. Through integrated GO and KEGG function annotations, it was determined that the miRNA target genes were mainly involved in metabolic pat ...[more]

PMID: 30745831

Similar Datasets

Project description:BackgroundCamellia oleifera, an essential woody oil tree in China, propagates through grafting. However, in production, it has been found that the interaction between rootstocks and scions may affect fruit characteristics. Therefore, it is necessary to predict fruit characteristics after grafting to identify suitable rootstock types.MethodsThis study used Deep Neural Network (DNN) methods to analyze the impact of 106 6-year-old grafting combinations on the characteristics of C.oleifera, including fruit and seed characteristics, and fatty acids. The prediction of characteristics changes after grafting was explored to provide technical support for the cultivation and screening of specialized rootstocks. After determining the unsaturated fat acids, palmitoleic acid C16:1, cis-11 eicosenoic acid C20:1, oleic acid C18:1, linoleic acid C18:2, linolenic acid C18:3, kernel oil content, fruit height, fruit diameter, fresh fruit weight, pericarp thickness, fresh seed weight, and the number of fresh seeds, the DNN method was used to calculate and analyze the model. The model was screened using the comprehensive evaluation index of Mean Absolute Error (MAPE), determinate correlation R2 and and time consumption.ResultsWhen using 36 neurons in 3 hidden layers, the deep neural network model had a MAPE of less than or equal to 16.39% on the verification set and less than or equal to 13.40% on the test set. Compared with traditional machine learning methods such as support vector machines and random forests, the DNN method demonstrated more accurate predictions for fruit phenotypic characteristics, with MAPE improvement rates of 7.27 and 3.28 for the 12 characteristics on the test set and maximum R2 improvement values of 0.19 and 0.33. In conclusion, the DNN method developed in this study can effectively predict the oil content and fruit phenotypic characteristics of C. oleifera, providing a valuable tool for predicting the impact of grafting combinations on the fruit of C. oleifera.

Dataset Information

Small RNA sequencing reveals dynamic microRNA expression of important nutrient metabolism during development of Camellia oleifera fruit.

Publications

Small RNA sequencing reveals dynamic microRNA expression of important nutrient metabolism during development of <i>Camellia oleifera</i> fruit.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets