The aim of this study was to identify key genes related to the progression of colon adenocarcinoma (COAD), and to investigate the regulatory network of hub genes and transcription factors (TFs). ...Dataset GSE20916 including 44 normal colon, 55 adenoma, and 36 adenocarcinoma tissue samples was used to construct co‐expression networks via weighted gene co‐expression network. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis for the objective module were performed using the online Database for Annotation, Visualization and Integrated Discovery. Hub genes were identified by taking the intersection of differentially expressed genes between dataset GSE20916 and GSE39582 and validated using The Cancer Genome Atlas (TCGA) database. The correlations between microRNA (miRNA) and hub genes were analyzed using the online website StarBase. Cytoscape was used to establish a regulatory network of TF‐miRNA‐target gene. We found that the orange module was a key module related to the tumor progression in COAD. In datasets GSE20916 and GSE39582, a total of eight genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) were selected, which were closely related with patients’ survivals in TCGA database and dataset GSE20916. COAD patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. A regulatory network of TF‐miRNA‐target gene with 144 TFs, 26 miRNAs, and 7 hub genes was established, including model KLF11‐miR149‐BGN, TCEAL6‐miR29B2‐COL1A1, and TCEAL6‐miR29B2‐COL1A2. In conclusion, during the progression of COAD, eight core genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) play vital roles. Regulatory networks of TF‐miRNA‐target gene can help to understand the disease progression and optimize treatment strategy.
Hub genes and transcription factor regulatory network of colon adenocarcinoma
SUMMARY
Soybean (Glycine max L. Merr.) is a major crop in animal feed and human nutrition, mainly for its rich protein and oil contents. The remarkable rise in soybean transcriptome studies over the ...past 5 years generated an enormous amount of RNA‐seq data, encompassing various tissues, developmental conditions and genotypes. In this study, we have collected data from 1298 publicly available soybean transcriptome samples, processed the raw sequencing reads and mapped them to the soybean reference genome in a systematic fashion. We found that 94% of the annotated genes (52 737/56 044) had detectable expression in at least one sample. Unsupervised clustering revealed three major groups, comprising samples from aerial, underground and seed/seed‐related parts. We found 452 genes with uniform and constant expression levels, supporting their roles as housekeeping genes. On the other hand, 1349 genes showed heavily biased expression patterns towards particular tissues. A transcript‐level analysis revealed that 95% (70 963 of 74 490) of the assembled transcripts have intron chains exactly matching those from known transcripts, whereas 3256 assembled transcripts represent potentially novel splicing isoforms. The dataset compiled here constitute a new resource for the community, which can be downloaded or accessed through a user‐friendly web interface at http://venanciogroup.uenf.br/resources/. This comprehensive transcriptome atlas will likely accelerate research on soybean genetics and genomics.
Significance Statement
Here we report an integrative and systematic analysis of 1298 RNA‐Seq samples to build a soybean gene expression atlas. This resource is accessible via a user‐friendly web interface as well as available for download.
Intermediate CAG expansions in the gene ataxin-2 (ATXN2) are a known risk factor for ALS, but little is known about their role in FTD risk. Moreover, their contribution to the risk and phenotype of ...patients might vary in populations with different genetic backgrounds. The aim of this study was to assess the relationship of intermediate CAG expansions in ATXN2 with the risk and phenotype of ALS and FTD in the Spanish population. Repeat-primed PCR was performed in 620 ALS and 137 FTD patients in three referral centers in Spain to determine the exact number of CAG repeats. In our cohort, ≥27 CAG repeats in ATXN2 were associated with a higher risk of developing ALS (odds ratio OR = 2.666 1.471–4.882; p = 0.0013) but not FTD (odds ratio OR = 1.446 0.558–3.574; p = 0.44). Moreover, ALS patients with ≥27 CAG repeats in ATXN2 showed a shorter survival rate compared to those with <27 repeats (hazard ratio HR 1.74 1.18, 2.56, p = 0.005), more frequent limb onset (odds ratio OR = 2.34 1.093–4.936; p = 0.028) and a family history of ALS (odds ratio OR = 2.538 1.375–4.634; p = 0.002). Intermediate CAG expansions of ≥27 repeats in ATXN2 are associated with ALS risk but not with FTD in the Spanish population. ALS patients carrying an intermediate expansion in ATXN2 show more frequent limb onset but a worse prognosis than those without expansions. In patients carrying C9orf72 expansions, the intermediate ATXN2 expansion might increase the penetrance and modify the phenotype.
Essential genes represent critical cellular components whose disruption results in lethality. Characteristics shared among essential genes have been uncovered in fungal and metazoan model systems. ...However, features associated with plant essential genes are largely unknown and the full set of essential genes remains to be discovered in any plant species. Here, we show that essential genes in Arabidopsis thaliana have distinct features useful for constructing within- and cross-species predictionmodels. Essential genes in A. thaliana are often single copy or derived from older duplications, highly and broadly expressed, slow evolving, and highly connected within molecular networks compared with genes with nonlethal mutant phenotypes. These gene features allowed the application of machine learning methods that predicted known lethal genes as well as an additional 1970 likely essential genes without documented phenotypes. Prediction models from A. thaliana could also be applied to predict Oryza sativa and Saccharomyces cerevisiae essential genes. Importantly, successful predictions drew upon many features, while any single feature was not sufficient. Our findings show that essential genes can be distinguished from genes with nonlethal phenotypes using features that are similar across kingdoms and indicate the possibility for translational application of our approach to species without extensive functional genomic and phenomic resources.
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