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Abstract Background Finding meaningful gene-gene interaction and the main Transcription Factors (TFs) in co-expression networks is one of the most important challenges in gene expression data mining. Results Here, we developed the R package “CeTF” that integrates the Partial Correlation with Information Theory (PCIT) and Regulatory Impact Factors (RIF) algorithms applied to gene expression data from microarray, RNA-seq, or single-cell RNA-seq platforms. This approach allows identifying the transcription factors most likely to regulate a given network in different biological systems — for example, regulation of gene pathways in tumor stromal cells and tumor cells of the same tumor. This pipeline can be easily integrated into the high-throughput analysis. To demonstrate the CeTF package application, we analyzed gastric cancer RNA-seq data obtained from TCGA (The Cancer Genome Atlas) and found the HOXB3 gene as the second most relevant TFs with a high regulatory impact (TFs-HRi) regulating gene pathways in the cell cycle. Conclusion This preliminary finding shows the potential of CeTF to list master regulators of gene networks. CeTF was designed as a user-friendly tool that provides many highly automated functions without requiring the user to perform many complicated processes. It is available on Bioconductor ( http://bioconductor.org/packages/CeTF ) and GitHub ( http://github.com/cbiagii/CeTF ).

Aberrant expression of long non-coding RNAs (lncRNAs) has been detected in several types of cancer, including acute lymphoblastic leukemia (ALL), but lncRNA mapped on transcribed ultraconserved regions (T-UCRs) are little explored. The T-UCRs uc.112, uc.122, uc.160 and uc.262 were evaluated by quantitative real-time PCR in bone marrow samples from children with T-ALL (n = 32) and common-ALL/pre-B ALL (n = 30). In pediatric ALL, higher expression levels of uc.112 were found in patients with T-ALL, compared to patients with B-ALL. T-cells did not differ significantly from B-cells regarding uc.112 expression in non-tumor precursors from public data. Additionally, among B-ALL patients, uc.112 was also found to be increased in patients with hyperdiploidy, compared to other karyotype results. The uc.122, uc.160, and uc.262 were not associated with biological or clinical features. These findings suggest a potential role of uc.112 in pediatric ALL and emphasize the need for further investigation of T-UCR in pediatric ALL.

Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making.

Macrophages are classified upon activation as classical activated M1 and M2 anti-inflammatory regulatory populations. This macrophage polarization is well characterized in humans and mice, but M1/M2 profile in cattle has been far less explored. Bos primigenius taurus (taurine) and Bos primigenius indicus (indicine) cattle display contrasting levels of resistance to infection and parasitic diseases such as C57BL/6J and Balb/c murine experimental models of parasite infection outcomes based on genetic background. Thus, we investigated the differential gene expression profile of unstimulated and LPS stimulated monocyte-derived macrophages (MDMs) from Holstein (taurine) and Gir (indicine) breeds using RNA sequencing methodology. For unstimulated MDMs, the contrast between Holstein and Gir breeds identified 163 Differentially Expressed Genes (DEGs) highlighting the higher expression of C-C chemokine receptor type five (CCR5) and BOLA-DQ genes in Gir animals. LPS-stimulated MDMs from Gir and Holstein animals displayed 1,257 DEGs enriched for cell adhesion and inflammatory responses. Gir MDMs cells displayed a higher expression of M1 related genes like Nitric Oxide Synthase 2 (NOS2), Toll like receptor 4 (TLR4), Nuclear factor NF-kappa-B 2 (NFKB2) in addition to higher levels of transcripts for proinflammatory cytokines, chemokines, complement factors and the acute phase protein Serum Amyloid A (SAA). We also showed that gene expression of inflammatory M1 population markers, complement and SAA genes was higher in Gir in buffy coat peripheral cells in addition to nitric oxide concentration in MDMs supernatant and animal serum. Co-expression analyses revealed that Holstein and Gir animals showed different transcriptional signatures in the MDMs response to LPS that impact on cell cycle regulation, leukocyte migration and extracellular matrix organization biological processes. Overall, the results suggest that Gir animals show a natural propensity to generate a more pronounced M1 inflammatory response than Holstein, which might account for a faster immune response favouring resistance to many infection diseases.