Machine-learning guided discovery of emergent antimicrobial activity from dynamic covalent assemblies（Holstein cattle， RNA seq）

This dataset contains host bulk RNA-seq data and uterine microbiome 2bRAD-M data from a Holstein dairy cow study of naturally occurring endometritis. The RNA-seq component includes 12 uterine wall tissue samples: Healthy, PBS-treated endometritis controls, A5B5-treated samples and antibiotic-treated samples, with three biological replicates per group. counts_anno.csv and FPKM_anno.csv each contain all 12 samples in one annotated expression matrix comprising 22,314 gene identifiers shared by the source datasets. sample_metadata.csv defines the RNA-seq sample groups. The microbiome component includes 21 biological samples: Healthy, PBS and A5B5 groups with six samples each, and an oxytetracycline group with three samples. All 21 samples are included in Abundance.filtered.anno.csv as a single annotated species-level relative-abundance matrix. 2bRADM_sample_metadata.csv defines the groups and identifies the 12 samples used in the current four-group analysis (three per group). Vendor reference/control columns are excluded from biological sample matrices. Methods documented for the original samples: Total RNA was extracted using TRIzol according to the manufacturer’s protocol; RNA quantity and purity were assessed using NanoDrop 2000, and RNA integrity was assessed using the Agilent 2100 Bioanalyzer. Libraries were prepared with the VAHTS Universal V10 RNA-seq Library Prep Kit (Premixed Version) and sequenced on an Illumina NovaSeq 6000 platform to generate 150 bp paired-end reads. Raw FASTQ data were processed with fastp for quality control and adapter/low-quality read removal, and clean reads were aligned to the reference genome using HISAT2. Gene-level read counts were obtained with HTSeq-count, and expression abundance was calculated (FPKM).