Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Apr 22:8:639053.
doi: 10.3389/fvets.2021.639053. eCollection 2021.

Identification of Long Non-coding RNA Isolated From Naturally Infected Macrophages and Associated With Bovine Johne's Disease in Canadian Holstein Using a Combination of Neural Networks and Logistic Regression

Andrew Marete  1 , Olivier Ariel  1   2 , Eveline Ibeagha-Awemu  1 , Nathalie Bissonnette  1
Affiliations

Identification of Long Non-coding RNA Isolated From Naturally Infected Macrophages and Associated With Bovine Johne's Disease in Canadian Holstein Using a Combination of Neural Networks and Logistic Regression

Andrew Marete et al. Front Vet Sci. .

Abstract

Mycobacterium avium ssp. paratuberculosis (MAP) causes chronic enteritis in most ruminants. The pathogen MAP causes Johne's disease (JD), a chronic, incurable, wasting disease. Weight loss, diarrhea, and a gradual drop in milk production characterize the disease's clinical phase, culminating in death. Several studies have characterized long non-coding RNA (lncRNA) in bovine tissues, and a previous study characterizes (lncRNA) in macrophages infected with MAP in vitro. In this study, we aim to characterize the lncRNA in macrophages from cows naturally infected with MAP. From 15 herds, feces and blood samples were collected for each cow older than 24 months, twice yearly over 3-5 years. Paired samples were analyzed by fecal PCR and blood ELISA. We used RNA-seq data to study lncRNA in macrophages from 33 JD(+) and 33 JD(-) dairy cows. We performed RNA-seq analysis using the "new Tuxedo" suite. We characterized lncRNA using logistic regression and multilayered neural networks and used DESeq2 for differential expression analysis and Panther and Reactome classification systems for gene ontology (GO) analysis. The study identified 13,301 lncRNA, 605 of which were novel lncRNA. We found seven genes close to differentially expressed lncRNA, including CCDC174, ERI1, FZD1, TWSG1, ZBTB38, ZNF814, and ZSCAN4. None of the genes associated with susceptibility to JD have been cited in the literature. LncRNA target genes were significantly enriched for biological process GO terms involved in immunity and nucleic acid regulation. These include the MyD88 pathway (TLR5), GO:0043312 (neutrophil degranulation), GO:0002446 (neutrophil-mediated immunity), and GO:0042119 (neutrophil activation). These results identified lncRNA with potential roles in host immunity and potential candidate genes and pathways through which lncRNA might function in response to MAP infection.

Keywords: Johne's disease; MAP disease; bovine; genomics; long non-coding RNA; macrophages; paratuberculosis (Mycobacterium avium ssp. paratuberculosis).

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
(A) The study workflow from raw fastq to lncRNA identification and DE of the nearest genes. (B) Two-graph receiver operating characteristic curve (ROC) to determine the optimal coding-probability cutoff value. (C) Combinatorial effects of Fickett score, hexamer score, and ORF size on coding transcripts (brown dots) and non-coding genes (blue dots). (D) Mapping statistics (vertical axis) showing unique (red), multi-mapped (yellow-green), and overall (blue) alignment rate for all cows (horizontal axis). (E) Snapshot of lncRNA statistics identified by two tools with known lncRNAs in parentheses.
Figure 2
Figure 2
Distribution of putative, known, and novel lncRNAs in chromosomes 1–29 and X.
Figure 3
Figure 3
Normalized count distributions in JD(+) macrophages (purple) and JD(–) macrophages (blue) for 10 highly expressed genes close to lncRNA transcripts.
See this image and copyright information in PMC

References

    1. Whittington R, Donat K, Weber MF, Kelton D, Nielsen SS, Eisenberg S, et al. Control of paratuberculosis: who, why and how. A review of 48 countries. BMC Vet Res. (2019) 15:198. 10.1186/s12917-019-1943-4 - DOI - PMC - PubMed
    1. Whitlock RH, Buergelt C. Preclinical and clinical manifestations of paratuberculosis (including pathology). Vet Clin North Am Food Anim Pract. (1996) 12:345–56. 10.1016/S0749-0720(15)30410-2 - DOI - PubMed
    1. Smith RL, Strawderman RL, Schukken YH, Wells SJ, Pradhan AK, Espejo LA, et al. Effect of Johne's disease status on reproduction and culling in dairy cattle. J Dairy Sci. (2010) 93:3513–24. 10.3168/jds.2009-2742 - DOI - PubMed
    1. Garcia AB, Shalloo L. Invited review: the economic impact and control of paratuberculosis in cattle. J Dairy Sci. (2015) 98:5019–39. 10.3168/jds.2014-9241 - DOI - PubMed
    1. Corbett CS, Naqvi SA, Bauman CA, De Buck J, Orsel K, Uehlinger F, et al. Prevalence of Mycobacterium avium ssp. paratuberculosis infections in Canadian dairy herds. J Dairy Sci. (2018) 101:11218–28. 10.3168/jds.2018-14854 - DOI - PubMed