scholarly journals Regulator Network Analysis of Rice and Maize Yield-Related Genes

2020 ◽  
Vol 8 ◽  
Author(s):  
Zheng Chen ◽  
Zijie Shen ◽  
Lei Xu ◽  
Da Zhao ◽  
Quan Zou
Keyword(s):  
Network Analysis ◽  
Crop Yield ◽  
Regulatory Network ◽  
Gene Families ◽  
Genetic Regulatory Network ◽  
High Yield ◽  
Ethylene Response Factor ◽  
Yield Traits ◽  
Crop Species ◽  
Maize Varieties

Rice and maize are the principal food crop species worldwide. The mechanism of gene regulation for the yield of rice and maize is still the research focus at present. Seed size, weight and shape are important traits of crop yield in rice and maize. Most members of three gene families, APETALA2/ethylene response factor, auxin response factors and MADS, were identified to be involved in yield traits in rice and maize. Analysis of molecular regulation mechanisms related to yield traits provides theoretical support for the improvement of crop yield. Genetic regulatory network analysis can provide new insights into gene families with the improvement of sequencing technology. Here, we analyzed the evolutionary relationships and the genetic regulatory network for the gene family members to predicted genes that may be involved in yield-related traits in rice and maize. The results may provide some theoretical and application guidelines for future investigations of molecular biology, which may be helpful for developing new rice and maize varieties with high yield traits.

scholarly journals Genetic Regulatory Network Analysis forAppBased on Genetical Genomics Approach

2009 ◽  
Vol 36 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Xusheng Wang ◽  
Ying Chen ◽  
Xiaodong Wang ◽  
Lu Lu
Keyword(s):  
Network Analysis ◽  
Regulatory Network ◽  
Genetic Regulatory Network ◽  
Genetical Genomics

Genetic Regulatory Network Analysis for Rpe65 in the Eye of BXD Mice

2011 ◽  
Vol 282-283 ◽  
pp. 248-252
Author(s):  
Hong Lu ◽  
Huai Jin Guan ◽  
Hui Chen ◽  
Lu Lu
Keyword(s):  
Network Analysis ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Likelihood Ratio Statistic ◽  
Critical Role ◽  
Genetic Regulatory Networks ◽  
Genetic Regulatory Network ◽  
Microarray Probe ◽  
Inherited Retinal Dystrophies ◽  
Retinal Dystrophies

Previous studies have revealed that the mutation of Rpe65plays a critical role in inherited retinal dystrophies. However, little is known about the genetic regulatory network for Rpe65 and inherited retinal dystrophies. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Rpe65 expression in the eye of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Rpe65exhibited much variation in the eye across the BXD RI strains and between the parental strains, C57BL/6J and DBA/2J. Expression QTL (eQTL) mapping showed that one microarray probe set of Rpe65 has highly significant linkage (Likelihood Ratio Statistic) scores. Moreover, the QTL was mapped to within 3 Mb of the location of the gene itself (Rpe65) as a cis-acting QTL. Through mapping the joint modulation of Rpe65, we identified Ches1/Foxn3 as downstream gene of Rpe65. Then the gene co-regulatory network analysis was constructed. The genetic genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to inherited retinal dystrophies.

scholarly journals Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qinghong Shi ◽  
Hanxin Yao
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Network Analysis ◽  
Type 1 Diabetes Mellitus ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Competing Endogenous Rna ◽  
Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

scholarly journals Agro-Nanotechnology as an Emerging Field: A Novel Sustainable Approach for Improving Plant Growth by Reducing Biotic Stress

2021 ◽  
Vol 11 (5) ◽  
pp. 2282
Author(s):  
Masudulla Khan ◽  
Azhar U. Khan ◽  
Mohd Abul Hasan ◽  
Krishna Kumar Yadav ◽  
Marina M. C. Pinto ◽  
...  
Keyword(s):  
Plant Growth ◽  
Crop Yield ◽  
Biotic Stress ◽  
Crop Production ◽  
Plant Disease ◽  
Yield Loss ◽  
Growth Parameters ◽  
Plant Diseases ◽  
High Yield ◽  
Plant Disease Management

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.

Sign in / Sign up

Export Citation Format

Share Document