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Multipopulational transcriptome analysis of beef cattle at arrival to identify and further validate candidate biomarkers for predicting clinical bovine respiratory disease

ABSTRACT: Multipopulational transcriptome analysis of beef cattle at arrival to identify and further validate candidate biomarkers for predicting clinical bovine respiratory disease

PROVIDER: PRJNA678022 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13051345_1.fastq.gz	Fastqsanger.gz
	SRR13051345_2.fastq.gz	Fastqsanger.gz
	SRR13051346_1.fastq.gz	Fastqsanger.gz
	SRR13051346_2.fastq.gz	Fastqsanger.gz
	SRR13051347_1.fastq.gz	Fastqsanger.gz

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Multipopulational transcriptome analysis of beef cattle at arrival to identify and further validate candidate biomarkers for predicting clinical bovine respiratory disease

Project description:Objective: Classify and further validate BRD-associated genes and mechanisms found to be differentially expressed at facility arrival in post-weaned beef cattle from multiple independent populations. Our approach was to profile and compare at-arrival whole blood transcriptomes of post-weaned beef cattle that failed to develop symptoms associated with clinical BRD and cattle that ultimately were diagnosed and treated for clinical BRD within the first 28 days of facility arrival, further stratifying diseased animals into severity cohorts. Methods: Whole blood RNA profiles were generated via NGS approach, using an Illumina Novaseq 6000. Individual samples were processed using an adaptation of the Revised Tuxedo Suite protocol (Tuxedo 2), then analyzed in R using edgeR with likelihood-ratio testing. Genes were considered differentially expressed with an FDR cutoff of 0.05. Downstream analysis involved PCA, gene ontology term enrichment, pathway analysis, protein-protein interaction networking, and IPA. Results: 132 differentially expressed genes were identified between all three cohorts. Biological processes and pathways primarily involved neutrophilic activity, antimicrobial killing, cell cornification, and inflammatory signaling/regulation. Conlusions: This study corroborated genes and pathways identified in our previous work, while providing novel genes and pathways for future analysis.

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Multipopulational transcriptome analysis of post-weaned beef cattle at arrival further validates candidate biomarkers for predicting clinical bovine respiratory disease.

Project description:Bovine respiratory disease (BRD) remains the leading infectious disease in post-weaned beef cattle. The objective of this investigation was to contrast the at-arrival blood transcriptomes from cattle derived from two distinct populations that developed BRD in the 28 days following arrival versus cattle that did not. Forty-eight blood samples from two populations were selected for mRNA sequencing based on even distribution of development (n = 24) or lack of (n = 24) clinical BRD within 28 days following arrival; cattle which developed BRD were further stratified into BRD severity cohorts based on frequency of antimicrobial treatment: treated once (treated_1) or treated twice or more and/or died (treated_2+). Sequenced reads (~ 50 M/sample, 150 bp paired-end) were aligned to the ARS-UCD1.2 bovine genome assembly. One hundred and thirty-two unique differentially expressed genes (DEGs) were identified between groups stratified by disease severity (healthy, n = 24; treated_1, n = 13; treated_2+, n = 11) with edgeR (FDR ≤ 0.05). Differentially expressed genes in treated_1 relative to both healthy and treated_2+ were predicted to increase neutrophil activation, cellular cornification/keratinization, and antimicrobial peptide production. Differentially expressed genes in treated_2+ relative to both healthy and treated_1 were predicted to increase alternative complement activation, decrease leukocyte activity, and increase nitric oxide production. Receiver operating characteristic (ROC) curves generated from expression data for six DEGs identified in our current and previous studies (MARCO, CFB, MCF2L, ALOX15, LOC100335828 (aka CD200R1), and SLC18A2) demonstrated good-to-excellent (AUC: 0.800-0.899; ≥ 0.900) predictability for classifying disease occurrence and severity. This investigation identifies candidate biomarkers and functional mechanisms in at arrival blood that predicted development and severity of BRD.

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