Detecting RNA Viruses in Cattle: Effects of Sequencing Depth and Sequence References in Metatranscriptomics

In this study, the impact of sequencing depth and reference genome selection is shown to influence the detection of five bovine respiratory RNA viruses in metatranscriptomes from clinical cattle samples. Metatranscriptomes were generated from pooled samples and subsampled to 20 million, 10 million, and 1 million reads. We assessed the correlation between qRT-PCR cycle threshold (Ct) values and the number of reads mapped to reference genomes for four viruses: Bovine coronavirus (BCoV), Bovine nidovirus (BNV), Influenza D Virus (IDV), and Bovine Viral Diarrhea Virus-1 (BVDV-1).Strong linear correlations were observed between mapped reads and Ct values. For BCoV and BNV, RefSeq genomes yielded detection thresholds at ~ Ct 38 with 1 million reads; IDV showed a threshold at Ct 34.4. Reference genome choice had minimal impact on BCoV, BNV, and IDV detection. However, BVDV-1 detection was poor using the divergent RefSeq genome and improved significantly with a sample-derived reference.Complete coverage of the BCoV genome and IDV segment 6 was achieved in samples with Ct values below 30, regardless of the reference used. For BNV, genome 80% coverage was reached when using the NCBI RefSeq, even in samples with low-Ct samples. BVDV-1 could not be detected when using the RefSeq genome, highlighting the limitations of distant references.These findings demonstrate that both sequencing depth and reference genome choice substantially influence viral detection sensitivity in metatranscriptomic analyses.