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

Use of SNP Markers Within the Fat Mass and Obesity-associated (FTO) Gene to Verify Pedigrees and Determine Haplotypes in Paternal Half-sib Families of Slovenian Simmental Cattle

The objective of this preliminary study was to identify SNP markers within the FTO gene for evaluation of pedigree data accuracy and determination of haplotypes in paternal half-sib families of Slovenian Simmental cattle. Out of 23 polymorphic SNPs identified ten most informative SNPs for genotyping 31 sires and 56 half-sib progeny were used. The ATLAS program was used for paternity testing. Haplotype analysis revealed three haplotype blocks. The effect of SNPs “ex2 T>C” and “int2 indel*>T” was significant on three correlated carcass traits: live weight at slaughter (P= 0.03), carcass weight (P= 0.038), and lean weight (P= 0.048). The FTO gene can thus be regarded as a candidate for the marker assisted selection programs in our and possibly other populations of cattle. Future studies in cattle might also reveal novel roles of the FTO gene in carcass traits on livestock species as well as fatness control in other mammals

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

Preservation of 5-Hydroxymethylcytosine Levels in <i>LRIG1</i> across Genomic DNA and Cell-Free DNA in Glioma Patients

Cell-free DNA (cfDNA) has recently emerged as a promising minimally invasive diagnostic biomarker for various cancers. In this study, our aim was to identify cfDNA biomarkers by investigating genes that displayed significant differences between glioma patients and their corresponding controls. To accomplish this, we utilized publicly available data from the Gene Expression Omnibus, focusing on 5-hydroxymethylcytosine (5hmC) profiles in both cfDNA and genomic DNA (gDNA) from glioma patients and healthy individuals. The intersection of gene lists derived from these comparative analyses unveiled LRIG1 and ZNF703 as the two genes with elevated 5hmC levels in both the cfDNA of glioma patients and gDNA of glioma tissue compared to their respective controls. The gene expression data revealed both genes were upregulated in glioma tissue compared to normal brain tissue. Integration of 5hmC data revealed a strong positive correlation in the glioma tissue group between 5hmC and the gene expression of the LRIG1 gene. Furthermore, exploration using the AmiCa web tool indicated that LRIG1 gene expression was elevated compared to 17 other cancers included in the database, emphasizing its potential as a distinctive biomarker across multiple cancer types

AmiCa: Atlas of miRNA-gene correlations in cancer

The increasing availability of RNA sequencing data has opened up numerous opportunities to analyze various RNA interactions, including microRNA-target interactions (MTIs). In response to the necessity for a specialized tool to study MTIs in cancer and normal tissues, we developed AmiCa (https://amica.omics.si/), a web server designed for comprehensive analysis of mature microRNA (miRNA) and gene expression in 32 cancer types. Data from 9498 tumor samples and 626 normal samples from The Cancer Genome Atlas were obtained through the Genomic Data Commons and used to calculate differential expression and miRNA-target gene (MTI) correlations. AmiCa provides data on differential expression of miRNAs/genes for cancers for which normal tissue samples were available. In addition, the server calculates and presents correlations separately for tumor and normal samples for cancers for which normal samples are available. Furthermore, it enables the exploration of miRNA/gene expression in all cancer types with different miRNA/gene expression. In addition, AmiCa includes a ranking system for genes and miRNAs that can be used to identify those that are particularly highly expressed in certain cancers compared to other cancers, facilitating targeted and cancer-specific research. Finally, the functionality of AmiCa is illustrated by two case studies