ArticlePloS one2026
Identification and validation of novel reference genes for bovine respiratory and lymphoid tissues using public transcriptomes and BRSV challenge model.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
RT-qPCR can be employed to quantify target gene expression normalized to reference genes that are expected to remain stable across experimental conditions. However, previously reported reference genes may not be stably expressed across all experimental conditions and individuals. This research identified novel candidate reference genes from publicly available healthy bovine tissue transcriptomes and subsequently developed and validated primers for five candidate reference genes. Forty-one transcriptomes were obtained from the NCBI Gene Expression Omnibus (GEO) from apparently healthy Bos taurus samples: bone marrow, bronchial lymph nodes (LN), mesenteric LN, kidney, liver, lung, nasal epithelium, unspecified LN, spleen, thymus, and trachea. Bioinformatic analysis of each dataset was performed using FastQC, Trimmomatic, STAR, and R, with library normalization carried out using the Relative Log Expression (RLE) method and normalized gene counts converted to log2-CPM values. The values for each gene across the transcriptomes were ranked by coefficient of variation (CV). The top 200 genes ranked by CV were analyzed using RefFinder for inter-tissue stability. Five candidates were selected: DDX23, NMT1, CRNKL1, TMEM183A, and UBE2Q1. To validate stability, RT-qPCR was used to assess the stability of these genes in tissues from seven bovine respiratory syncytial virus-infected calves and two healthy calves, including lung, bronchus, trachea, nasal epithelium, tracheobronchial LN, mediastinal LN, thymus, spleen, and bone marrow. The averaged CT values were analyzed with RefFinder. Comprehensive stability values identified CRNKL1 as the most or second most stable gene in 8/10 tissues, with variation in ranking of each reference gene across all tissues. This study identified a bioinformatic workflow and candidate reference genes, with primers validated for five genes which demonstrated stability across various bovine tissues.
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