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Rous sarcoma virus (RSV), which is an oncovirus, can cause sarcoma and consequently induce malignant tumours in chicken (Gallus gallus). Research into molecular factors that regulate the tumour-inducing ability are essential to develop prevention and curation methods against RSV. In this study, we aimed to determine candidate genes contributing to the formation of tumours through a transcriptomic analysis in R programming with GSE42516 and GSE15141, which are microarray expression dataset in GEO-NCBI database. We conducted differential expression analysis among a total of 8 metastatic samples and 5 non-metastatic samples, starting from data normalization, then creating model matrixes for pairwise comparisons and using eBayes function to calculate the log fold chance values and significance level of all genes (p-value). As a result, in GSE42516, we identified 295 significant (p-value ≤ 0.05) differentially expressed genes (DEGs), with 195 downregulated genes (logFC ≤ -1) and 190 upregulated genes (logFC ≥ 1). While in GSE15141, a greater list of DEGs was extracted, with 1444 downregulated genes and 1314 upregulated genes. Top 5 DEGs retrieved in GSE42516 were TTC32, DHRS7, RARB, RSPO3, C1QB and RBM24, TOM1L1, LIPI, HINTW, C20orf59 were found in GSE15141. Enrichment GO (in this case, biological process - BP) analysis revealed that the DEGs are mainly enriched in heterochromatin assembly, negative regulation of megakaryocyte differentiation and endocytosis. The identified genes may have a vital role in elucidating the molecular metastasis mechanisms and developing effective strategies against sarcoma virus. [ABSTRACT FROM AUTHOR]

Rous sarcoma virus (RSV), which is an oncovirus, can cause sarcoma and consequently induce malignant tumours in chicken (Gallus gallus). Research into molecular factors that regulate the tumour-inducing ability are essential to develop prevention and curation methods against RSV. In this study, we aimed to determine candidate genes contributing to the formation of tumours through a transcriptomic analysis in R programming with GSE42516 and GSE15141, which are microarray expression dataset in GEO-NCBI database. We conducted differential expression analysis among a total of 8 metastatic samples and 5 non-metastatic samples, starting from data normalization, then creating model matrixes for pairwise comparisons and using eBayes function to calculate the log fold chance values and significance level of all genes (p-value). As a result, in GSE42516, we identified 295 significant (p-value ≤ 0.05) differentially expressed genes (DEGs), with 195 downregulated genes (logFC ≤ -1) and 190 upregulated genes (logFC ≥ 1). While in GSE15141, a greater list of DEGs was extracted, with 1444 downregulated genes and 1314 upregulated genes. Top 5 DEGs retrieved in GSE42516 were TTC32, DHRS7, RARB, RSPO3, C1QB and RBM24, TOM1L1, LIPI, HINTW, C20orf59 were found in GSE15141. Enrichment GO (in this case, biological process - BP) analysis revealed that the DEGs are mainly enriched in heterochromatin assembly, negative regulation of megakaryocyte differentiation and endocytosis. The identified genes may have a vital role in elucidating the molecular metastasis mechanisms and developing effective strategies against sarcoma virus. [ABSTRACT FROM AUTHOR]