LIFETIME PRODUCTION OF SLOVENIAN LOCAL GOAT BREEDS

The objective of the study was to analyze lifetime production data for two Slovenian locally adapted dairy breeds: Slovenian Saanen goat (334) and Slovenian Alpine goat (1105) and for the dairy type of Dreznica goat (141) which is the only Slovenian autochthonous goat breed. Dataset included records from 54 farms. Data for does born after 2002 have been obtained from the database of the National selection program for small ruminants, collected by the ICAR standards. The contribution of farm to phenotypic variance was estimated. Data was analyzed by MIXED procedure in SAS/STAT. The results showed significant effect of breed, farm and year of culling on all traits studied, except the effect of breed on completed lactations in lifetime and number of liveborn kids. The lifetime milk yield was higher in Slovenian Alpine goat compared to Slovenian Saanen goat by 413.26±172.52 kg. The difference in lifetime protein yield between Slovenian Alpine goat and Slovenian Saanen goat amounted to 11.76±5.21 kg. Dreznica goat did not differ in lifetime milk production and protein yield compared to both intensive goat breeds. Dreznica goat yielded about 25.50±5.21 kg more fat in lifetime compared to Slovenian Saanen goat. However, compared to Slovenian Alpine goat the difference was not significant. Comparison of Slovenian Saanen goat and Slovenian Alpine goat revealed higher lifetime fat yield of Slovenian Alpine goat by 13.28±5.21 kg. The results suggested reasonably good performance and adaptation of the autochthonous breed Dreznica goat in local agro climatic conditions

Steadfast Toll Like Receptor 4 (<i>TLR4</i>) 5-Hydroxymethylcytosine Levels in Cell-Free DNA: A Promising Consistency Marker for Colorectal Cancer Patients

Cell-free DNA (cfDNA) from patient blood is emerging as a noninvasive diagnostic avenue for various cancers. We aimed to identify reliable biomarkers in cfDNA by investigating genes exhibiting significant differences between colorectal cancer and control samples. Our objective was to identify genes that showed a positive difference between cancer and control samples. To achieve this, we conducted an in silico analysis to identify genes that exhibit no significant variation in methylation between genomic DNA (gDNA) and cfDNA. We collected experimental data from publicly available repositories, which included 5-hydroxymethylcytosine (5hmC) profiles of gDNA and cfDNA samples from both cancer patients and healthy individuals. By comparing and overlapping these two groups, we identified 187 genes of interest, of which 53 genes had a positive difference among colon cancer patients and healthy individuals. Next, we performed an ANOVA test on these genes, resulting in the identification of 12 genes that showed statistically significant higher levels of 5hmC in cfDNA and gDNA from cancer patients compared to healthy individuals. Additionally, we compared the 5hmC status of these genes between cfDNA and gDNA from cancer patients. Interestingly, we found that the 5hmC of the toll like receptor 4 (TLR4) gene was not statistically different between cfDNA and gDNA from cancer patients, indicating consistency between cfDNA and gDNA. These findings have important implications, not only for experimental validation but also for the development of more sensitive and robust noninvasive methods to improve diagnostic, prognostic, and treatment options for colon cancer

In Silico Gene Prioritization Highlights the Significance of Bone Morphogenetic Protein 4 (<i>BMP4</i>) Promoter Methylation across All Methylation Clusters in Colorectal Cancer

The cytosine–phosphate–guanine (CpG) island methylator phenotype (CIMP) represents one of the pathways involved in the development of colorectal cancer, characterized by genome-wide hypermethylation. To identify samples exhibiting hypermethylation, we used unsupervised hierarchical clustering on genome-wide methylation data. This clustering analysis revealed the presence of four distinct subtypes within the tumor samples, namely, CIMP-H, CIMP-L, cluster 3, and cluster 4. These subtypes demonstrated varying levels of methylation, categorized as high, intermediate, and very low. To gain further insights, we mapped significant probes from all clusters to Ensembl Regulatory build 89, with a specific focus on those located within promoter regions or bound regions. By intersecting the methylated promoter and bound regions across all methylation subtypes, we identified a total of 253 genes exhibiting aberrant methylation patterns in the promoter regions across all four subtypes of colorectal cancer. Among these genes, our comprehensive genome-wide analysis highlights bone morphogenic protein 4 (BMP4) as the most prominent candidate. This significant finding was derived through the utilization of various bioinformatics tools, emphasizing the potential role of BMP4 in colorectal cancer development and progression

The integrative knowledge base for miRNA-mRNA expression in colorectal cancer

"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application for studying microRNA and mRNA expression and their correlation in colorectal cancer. To the best of our knowledge, "miRNA colorectal cancer" has the largest knowledge base of miRNA-target gene expressions and correlations in colorectal cancer, based on the largest available sample size from the same source of data. Data from high-throughput molecular profiling of 295 colon and rectum adenocarcinoma samples from The Cancer Genome Atlas was analyzed and integrated into our knowledge base. The objective of developing this web application was to help researchers to discover the behavior and role of miRNA-target gene interactions in colorectal cancer. For this purpose, results of differential expression and correlation analyses of miRNA and mRNA data collected in our knowledge base are available through web forms. To validate our knowledge base experimentally, we selected genes FN1, TGFB2, RND3, ZEB1 and ZEB2 and miRNAs hsa-miR-200a/b/c-3p, hsa-miR-141-3p and hsa-miR-429. Both approaches revealed a negative correlation between miRNA hsa-miR-200b/c-3p and its target gene FN1 and between hsa-miR-200a-3p and its target TGFB2, thus supporting the usefulness of the developed knowledge base

Expression of cytokine-coding genes BMP8B, LEFTY1 and INSL5 could distinguish between ulcerative colitis and Crohn\u27s disease

Ulcerative colitis (UC) and Crohn’s disease (CD) are characterized by an imbalance between pro-inflammatory and anti-inflammatory cytokines, interfering with the resolution of inflammation. Due to the crucial role of cytokines, new insights into their profiles in UC and CD would help to improve our understanding of pathogenesis and enable the development of new treatment modalities. We provide an expression profile of cytokines in UC and CD, using bioinformatics approach, and experimental validation of expression of the selected genes. We retrieved data and analyzed the cytokine gene expression profiles of UC and CD. From ten genes with inverse expression, common to CD and UC, BMP8B, LEFTY1 and INSL5 were selected for gene expression experimental validation. Experimentally, BMP8B and INSL5 were down-regulated in both CD and UC but followed the bioinformatics trend. The expression of genes LEFTY1 and BMP8B was statistically significant when comparing UC and CD in colon and the expression of gene LEFTY1 showed statistical significance when CD in ileum and colon were compared. Using the bioinformatics approach and experimental validation, we found differences in expression profiles between UC and CD for INSL5, LEFTY1 and BMP8B. These three promising candidate genes need to be further explored at different levels, such as DNA methylation and protein expression, to provide more evidence on their potential diagnostic role in CD and UC

The glypican 3-hosted murine Mir717 gene

Mir717 (mmu-mir-717) was first reported in mouse and resides in the intron 3 of glypican 3 )Gpc3) gene. Our present study revealed that this microRNA (miRNA) gene is conserved among 26 mammalian species and harbors polymorphic sites within the mature seed region in mice. Our findiong represents a rare four layer genomic overlap consisting of growth associated quantitative trait locus (QTL), body mass associated Gpc3 gene, highly conserved miRNA gene and mature RNA seed sibgle nucleotide polymorphism (SNP) identified in the lean mouse strain 129/Sv. Additionally, genes potentialy targeted by Mir717 include 91 genes associated with obesity and realted phenbotypes in mammals. Our analaysis provides a basis for further experiments to casually connect the identified SNP and Mir717 gene itself to obesity regulation. Furthermore, our bioinformatics analysis now enables functional annotation of Mir717 orthologs in other species, thus determining the effect of its target genes on fat-related traits