DOI: 10.57760/sciencedb.17422
title: A dataset of Screening of immunity-Related miRNAs in Bovine Milk
title: A dataset of Screening of immunity-Related miRNAs in Bovine Milk

description: Sample Collection and RNA ExtractionThe experimental animals were five healthy Holstein cows aged 3-4 years, weighing 450-500 kg, and provided by Ke Feng Agricultural and Animal Husbandry Co., Ltd., Hangjin Houqi, Bayannur City, Inner Mongolia. Colostrum was collected within 48 hours postpartum, and regular milk was collected at the peak lactation period when the calves were 3 months old. The collected colostrum and regular milk samples were transported in liquid nitrogen and stored at -80°C. Total RNA was extracted from colostrum and mature milk and subjected to quality control.Library Construction and miRNA SequencingSmall RNA sequencing libraries were prepared using the TruSeq Small RNA Sample Prep Kits (Illumina, San Diego, USA). The libraries were sequenced using the Illumina Hiseq2500 platform with a single-end read length of 1×50 bp.Bioinformatics AnalysisMiRNA analysis involved removing 3' adapter sequences and low-quality sequences to obtain clean data, retaining sequences with a length of 18-26 nt. Non-miRNA sequences such as rRNA, snoRNA, snRNA, and tRNA were removed using the Rfam database. Potential repeat-associated sRNAs were removed using the Repbase database. Remaining sequences were used for known miRNA analysis, aligned to the reference genome using bowtie, and identified by comparison with the miRBase database. miRNA expression profiles were normalized.10-12 Differential expression analysis was performed using T-test, with P-value ≤0.05 as the screening criterion.miRNA Target Gene Prediction and Functional AnalysisTarget genes of significantly different miRNAs were predicted using TargetScan (V5.0)13-15 and miRanda (V3.3a)16-18. Removing target genes with context score percentile less than 50 in TargetScan algorithm, and in the miRanda algorithm, target genes with a Max Energy less than -10 are removed (i.e., the threshold is TargetScan_score≥ 50), miranda_Energy &lt; -10）.Genes predicted by both software were retained as final target genes, which were then subjected to GO and KEGG enrichment analysis to annotate their biological functions and identify immune-related miRNAs and their target genes.miRNA-gene-KEGG Network ConstructionCytoscape software was used to construct miRNA-gene and gene-KEGG networks, illustrating the regulatory pathways involving key miRNAs and their target genes.
description: Sample Collection and RNA ExtractionThe experimental animals were five healthy Holstein cows aged 3-4 years, weighing 450-500 kg, and provided by Ke Feng Agricultural and Animal Husbandry Co., Ltd., Hangjin Houqi, Bayannur City, Inner Mongolia. Colostrum was collected within 48 hours postpartum, and regular milk was collected at the peak lactation period when the calves were 3 months old. The collected colostrum and regular milk samples were transported in liquid nitrogen and stored at -80°C. Total RNA was extracted from colostrum and mature milk and subjected to quality control.Library Construction and miRNA SequencingSmall RNA sequencing libraries were prepared using the TruSeq Small RNA Sample Prep Kits (Illumina, San Diego, USA). The libraries were sequenced using the Illumina Hiseq2500 platform with a single-end read length of 1×50 bp.Bioinformatics AnalysisMiRNA analysis involved removing 3' adapter sequences and low-quality sequences to obtain clean data, retaining sequences with a length of 18-26 nt. Non-miRNA sequences such as rRNA, snoRNA, snRNA, and tRNA were removed using the Rfam database. Potential repeat-associated sRNAs were removed using the Repbase database. Remaining sequences were used for known miRNA analysis, aligned to the reference genome using bowtie, and identified by comparison with the miRBase database. miRNA expression profiles were normalized.10-12 Differential expression analysis was performed using T-test, with P-value ≤0.05 as the screening criterion.miRNA Target Gene Prediction and Functional AnalysisTarget genes of significantly different miRNAs were predicted using TargetScan (V5.0)13-15 and miRanda (V3.3a)16-18. Removing target genes with context score percentile less than 50 in TargetScan algorithm, and in the miRanda algorithm, target genes with a Max Energy less than -10 are removed (i.e., the threshold is TargetScan_score≥ 50), miranda_Energy &lt; -10）.Genes predicted by both software were retained as final target genes, which were then subjected to GO and KEGG enrichment analysis to annotate their biological functions and identify immune-related miRNAs and their target genes.miRNA-gene-KEGG Network ConstructionCytoscape software was used to construct miRNA-gene and gene-KEGG networks, illustrating the regulatory pathways involving key miRNAs and their target genes.