Signatures of selection in Nelore cattle revealed by whole-genome sequencing data

Nelore cattle breed was farmed worldwide due to its economic importance in the beef market and adaptation to the tropics. In Brazil, purebred Nelore animals (PO) receive a certificate from the breeders' association based on the animal's genealogy and morphological characterization. The top 20 to 30% of the superior animals are eligible to receive the Special Certificate of Identification and Production (CEIP), meaning animals from this category were selected and evaluated in a breeding program to improve economically important traits. We used whole-genome sequencing and approaches based on haplotype differentiation and allelic differentiation to detect regions of selection signatures in Nelore cattle by comparing animals from PO and CEIP categories. From a total of 150 animals, a hierarchical clustering analysis was performed to choose the more unrelated animals from each category (16 PO and 40 CEIP). The hapFLK statistic was performed, and extensions of hapFLK values were investigated considering continuous regions with significant q-values. The Weir and Cockerham's Fst estimator (wcFst) was computed using the GPAT++ software library. The total of 82,326 SNPs with hapFLK values passed the FDR control (q-value<0.05), and 718 segments were target as signatures of selection. A total of 1713 highly differentiated genomic regions were identified based on the segmentFst approach. The signatures of selection were spread across the genome. Annotation of overlapping selection signature regions between the two methods revealed 118 genes in common. A variant located within the 3′ region of the BOLA-DRB3 gene was found as a promising candidate polymorphism. Within genomic regions that deserves attention, we found genes previously associated with adaptation to tropical environments (HELB), growth and navel size (HMGA2), fat deposition and domestication (IRAK3), and feed efficiency and postmortem carcass traits (GABRG3). The genes BOLA-DQA2, BOLA-DQB, BOLA-DQA5, BOLA-DQA1, BOLA-DRB3, ENSBTAG00000038397 on chromosome 23 are part of the Bovine Major Histocompatibility Complex (MHC) Class II gene family, representing good candidates for immune response and adaptation to tropical conditions. The BoLA family genes and the interaction of ROBO1 with SLIT genes appeared in the enrichment results. Genomic regions located in intronic regions were also identified and might play a regulatory role in traits under selection in PO and CEIP subpopulations. The regions here identified contribute to our knowledge regarding genes and variants that have an important role in complex traits selected in this breed     

Comprehensive gene expression analysis reveals multiple signal pathways associated with prostate cancer

Prostate cancer (PC) depends on androgenic signaling for growth and survival. To data, the exact molecular mechanism of hormone controlling proliferation and tumorigenesis in the PC remains unclear. Therefore, in this study, we explored the differentially expressed genes (DEGs) and identified featured genes related to hormone stimulus from PC. Two sets of gene expression data, including PC and normal control sample, were downloaded from Gene Expression Omnibus (GEO) database. The t-test was used to identify DEGs between PC and controls. Gene ontology (GO) functional annotation was applied to analyze the function of DEGs and screen hormone-related DEGs. Then these hormone-related DEGs were further analyzed in constructed cancer network and Human Protein Reference Database to screen important signaling pathways they participated in. A total of 912 DEGs were obtained which included 326 up-regulated genes and 586 down-regulated genes. GO functional enrichment analysis identified 50 hormone-related DEGs associated with PC. After pathway and PPI network analysis, we found these hormone-related DEGs participated in several important signaling pathways including TGF-β (TGFB2, TGFB3 and TGFBR2), MAPK (TGFB2, TGFB3 and TGFBR2), insulin (PIK3R3, SHC1 and EIF4EBP1), and p53 signaling pathways (CCND2 and CDKN1A). In addition, a total of five hormone-related DEGs (SHC1, CAV1, RXRA, CDKN1A and SRF) were located in the center of PPI network and 12 hormone-related DEGs formed six protein modules. These important signal pathways and hormone-related DEGs may provide potential therapeutic targets for PC.     

Insight into molecular profile changes after skeletal muscle contusion using microarray and bioinformatics analyses

Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. The present study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process. A total of 33 rats were divided randomly into control (n=3), mild contusion (n=15), and severe contusion (n=15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n=3 per subgroup). A total of 2844 and 2298 differentially expressed genes (DEGs) were identified using microarray analyses in the mild and severe contusions, respectively. From the analysis of the 1620 coexpressed genes in mildly and severely contused muscle, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. The functional analyses of genes in the functional modules and temporal clusters were performed, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes down-regulated at 24-48 h were largely associated with metabolic processes, especially of the oxidative phosphorylation (OXPHOS), which has been rarely reported. These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.     

Bioinformatics Analyses of the Role of Vascular Endothelial Growth Factor in Patients with Non-Small Cell Lung Cancer

Purpose

This study was aimed to identify the expression pattern of vascular endothelial growth factor (VEGF) in non-small cell lung cancer (NSCLC) and to explore its potential correlation with the progression of NSCLC.

Methods

Gene expression profile GSE39345 was downloaded from the Gene Expression Omnibus database. Twenty healthy controls and 32 NSCLC samples before chemotherapy were analyzed to identify the differentially expressed genes (DEGs). Then pathway enrichment analysis of the DEGs was performed and protein-protein interaction networks were constructed. Particularly, VEGF genes and the VEGF signaling pathway were analyzed. The sub-network was constructed followed by functional enrichment analysis.

Results

Total 1666 up-regulated and 1542 down-regulated DEGs were identified. The down-regulated DEGs were mainly enriched in the pathways associated with cancer. VEGFA and VEGFB were found to be the initiating factor of VEGF signaling pathway. In addition, in the epidermal growth factor receptor (EGFR), VEGFA and VEGFB associated sub-network, kinase insert domain receptor (KDR), fibronectin 1 (FN1), transforming growth factor beta induced (TGFBI) and proliferating cell nuclear antigen (PCNA) were found to interact with at least two of the three hub genes. The DEGs in this sub-network were mainly enriched in Gene Ontology terms related to cell proliferation.

Conclusion

EGFR, KDR, FN1, TGFBI and PCNA may interact with VEGFA to play important roles in NSCLC tumorigenesis. These genes and corresponding proteins may have the potential to be used as the targets for either diagnosis or treatment of patients with NSCLC.