Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis.

The objective of this paper was to identify hub genes and pathways associated with retinoblastoma using centrality analysis of the co-expression network and pathway-enrichment analysis. The co-expression network of retinoblastoma was constructed by weighted gene co-expression network analysis (WGCNA) based on differentially expressed (DE) genes, and clusters were obtained through the molecular complex detection (MCODE) algorithm. Degree centrality analysis of the co-expression network was performed to explore hub genes present in retinoblastoma. Pathway-enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Validation of hub gene expression in retinoblastoma was performed by reverse transcription-polymerase chain reaction (RT-PCR) analysis. The co-expression network based on 221 DE genes between retinoblastoma and normal controls consisted of 210 nodes and 3965 edges, and 5 clusters of the network were evaluated. By assessing the centrality analysis of the co-expression network, 21 hub genes were identified, such as SNORD115-41, RASSF2, and SNORD115-44. According to RT-PCR analysis, 16 of the 21 hub genes were differently expressed, including RASSF2 and CDCA7, and 5 were not differently expressed in retinoblastoma compared to normal controls. Pathway analysis showed that genes in 2 clusters were enriched in 3 pathways: purine metabolism, p53 signaling pathway, and melanogenesis. In this study, we successfully identified 16 hub genes and 3 pathways associated with retinoblastoma, which may be potential biomarkers for early detection and therapy for retinoblastoma.

QTL verification of grain protein content and its correlation with oil content by using connected RIL populations of high-oil maize.

Maize with high grain protein and oil contents offers great advantages for human food and animal feed. In this study, grain protein contents of 282 and 263 F7:8 recombinant inbred lines (RILs) of 2 crosses were evaluated in 4 environments within and between populations. The RILs were developed from crosses between an inbred high-oil maize line and 2 normal dent inbred maize lines. A total of 16 single-population QTLs and 19 joint-population QTLs were identified for protein content, and 21 QTLs were detected for protein-oil in each of the 4 environments tested and in combination. Most of the QTLs for protein content were greatly influenced by variation among populations and environments. Seven QTLs showed generational consistency compared with QTLs detected in the 2 F2:3 populations. However, 7 and 6 QTLs were detected in only the RIL and F2:3 populations, respectively. Protein and protein-oil QTLs with the same parental effects were detected at bins 3.03-3.05, 5.04-5.06, 6.03-6.05, 8.03-8.04, and 8.04-8.06, demonstrating that tightly linked and/or pleiotropic QTLs are controlling both traits at these bins. Four single-population QTLs and 11 joint-population QTLs identified at bins 3.02-3.03, 3.05, 7.01, 8.02, 8.03, 8.04-8.05, 8.05, 9.03, and 9.05 with intervals <5 cM could be used in marker-assisted selection. Along with the previously detected QTLs qPRO1-8-1 and qPRO1-5-1 at bins 8.03-8.04 and 5.02-5.04, the QTLs detected herein could be used to develop near isogenic lines and chromosome segment substitution lines in future studies.

Bioinformatic analysis of endothelial progenitor cells exposed to folic acid in type 1 diabetes mellitus.

We investigated the effects of type 1 diabetes mellitus (T1DM) on endothelial progenitor cells (EPCs) at the molecular level and assessed the therapeutic potential of folic acid (FA) in DM. We downloaded the gene expression profile of the EPCs from T1DM patients before and after treatment with FA and from healthy controls. We identified the differentially expressed genes (DEGs) in the EPCs from T1DM patients before and after a four-week period of FA treatment and compared them with those obtained from the healthy subjects by using limma package in R language. Then, functional annotation of the DEGs was performed using the online tool Database for Annotation, Visualization and Integrated Discovery (DAVID) based on the Kyoto Encyclopedia of Genes and Genomes database. The expression of 696 genes was altered in the EPCs from T1DM patients compared to those from the healthy controls. These genes were mainly involved in the pathways associated with immune response. FA can normalize majority of the altered gene expression profiles of EPCs from T1DM patients to resemble those of healthy subjects, albeit with some side effects. FA can be a potential therapeutic agent for the treatment of T1DM. However, focused efforts are required to ensure that the dose of FA falls within the permissible pharmacological range.