Essential genes are required for an organism’s viability and their functions can vary greatly, spreading across many pathways. Due to the importance of essential genes, large scale efforts have been undertaken to identify the complete set of essential genes and to understand their function. Studies of genome architecture and organization have found that genes are not randomly disturbed in the genome. Using combined genetic mapping, Illumina sequencing, and bioinformatics analyses, we successfully identified 44 essential genes with 130 lethal mutations in genomic regions of C. elegans of around 7.3 Mb from Chromosome I (left). Of the 44 essential genes, six of which were genes not characterized previously by mutant alleles, let-633/let-638 (B0261.1), let-128 (C53H9.2), let-511 (W09C3.4), let-162 (Y47G6A.18), let-510 (Y47G6A.19), and let-131 (Y71G12B.6). Examine essential genes with Hi-C data shows that essential genes tend to cluster within TAD units rather near TAD boundaries. We have also shown that essential genes in the left half of chromosome I in C. elegans function in enzyme and nucleic acid binding activities during fundamental processes, such as DNA replication, transcription, and translation. From protein-protein interaction networks, essential genes exhibit more protein connectivity than non-essential genes in the genome. Also, many of the essential genes show strong expression in embryos or early larvae stages, indicating that they are important to early development. Our results confirmed that this work provided a more comprehensive picture of the essential gene and their functional characterization. These genetic resources will offer important tools for further heath and disease research.

Background: Small nucleolar RNA host gene 1 (SNHG1), a long noncoding RNA (lncRNA), is a transcript that negatively regulates tumour suppressor genes, such as p53. Abnormal SNHG1 expression is associated with cell proliferation and cancer. We used sequencing data downloaded from Genomic Data Commons to analyse the expression and interaction networks of SNHG1 in hepatocellular carcinoma (HCC). Methods: Expression was examined using the limma package of R and verified by Gene Expression Profiling Interactive Analysis. We also obtained miRNA expression data from StarBase to determine the lncRNA-miRNA-mRNA–related RNA regulatory network in HCC. Kaplan–Meier (KM) analysis was performed using the survival package of R. Gene Ontology annotation of genes was carried out using Metascape. Results: We found that SNHG1 was overexpressed and often amplified in HCC patients. In addition, SNHG1 upregulation was associated with the promotion of several primary biological functions, including cell proliferation, transcription and protein binding. Moreover, we found similar trends of small nucleolar RNA host gene 1 (SNHG1), E2F8 (E2F transcription factor 8), FANCE (FA complementation group E) and LMNB2 (encodes lamin B2) expression. In the SNHG1-associated network, high expression levels of SNHG1 (log-rank P value = 0.0643), E2F8 (log-rank P value = 0.000048), FANCE (log-rank P value = 0.00125) and LMNB2 (log-rank P value = 0.0392) were significantly associated with poor survival. Single-cell analysis showed that E2F8 may play an important role in tumorigenesis or cancer development. Conclusions: Our results highlight the benefit of utilizing multiple datasets to understand the functional potential regulatory networks of SNHG1 and the role of SNHG1 in tumours.

Background: Small nucleolar RNA host gene 1 (SNHG1), a long noncoding RNA (lncRNA), is a transcript that negatively regulates tumour-suppressor genes, such as the p53 gene. Abnormal SNHG1 expression is associated with cell proliferation and tumours. We used sequencing data downloaded from the Genomic Data Commons (GDC) to analyse the expression and interaction networks of SNHG1 in hepatocellular carcinoma (HCC). Methods: Expression was analysed using the limma package of R and verified by GEPIA. We also obtained miRNA expression data from StarBase to determine the lncRNA-miRNA-mRNA–related RNA regulatory network in HCC. Kaplan Meier (KM) analysis was performed using the survival package of R. Gene Ontology (GO) annotation of the genes was carried out using the Metascape. RESULTS: We found that SNHG1 was overexpressed and often amplified in HCC patients. In addition, SNHG1 upregulation was associated with the promotion of several primary biological functions, including cell proliferation, transcription and protein binding. Moreover, we found a competitive relationship among SNHG1, E2F8, FANCE and LMNB2. Additionally, in the SNHG1-associated network, higher expression levels of SNHG1 (log-rank P value = 0.0643), E2F8 (log-rank P value=0.000048), FANCE (log-rank P value=0.00125) and LMNB2 (log-rank P value=0.0392) were significantly associated with poor survival. We found that E2F8 may play an important role in tumorigenesis or cancer development by Single cell analysis. CONCLUSIONS: Our results highlight the utility of multiple data for understanding the functional potential regulatory networks of SNHG1 and the role of SNHG1 in tumours.