|Yu, Ying -|
|Luo, Juan -|
|Mitra, Apratim -|
|Chang, Shuang -|
|Tian, Fei -|
|Yuan, Ping -|
|Zhou, Huaijun -|
|Song, Jiuzhou -|
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 12, 2011
Publication Date: January 31, 2012
Citation: Yu, Y., Luo, J., Mitra, A., Chang, S., Tian, F., Zhang, H., Yuan, P., Zhou, H., Song, J. 2012. Temporal transcriptome changes induced by MDV in Marek's disease-resistant and -susceptible inbred chickens. Biomed Central (BMC) Genomics. 12:501. Available: http://www.biomedcentral.com/1471-2164/12/501. Interpretive Summary: Genetic diseases in animals are caused by a variety of alterations in the genetic code known as DNA sequences. For a long time, it has been known that DNA mutation (substitutions, additions, and deletions in genetic code) is one of the driving forces leading to such alteration. It is now clear that the magnitude or level of gene expression, a piece of DNA sequence coding for another molecular component known as messenger ribonucleic acid (mRNA), also constitutes such alterations. We examined chickens from three different genetic lines of varied genetic resistance to Marek’s disease (MD), an economically important virus-induced disease of chickens, for differences in gene expression. A significant amount of difference in gene expression was found, which coincides with the chicken line phenotype (characteristics in genetic resistance to MD). These findings should advance the understanding of genetic resistance to MD and help to improve control measures through selection strategies for disease resistance in chickens.
Technical Abstract: Mareks disease (MD) is a lymphoproliferative disease in chickens caused by Marek's disease virus (MDV) and characterized by T cell lymphoma and infiltration of lymphoid cells into various organs such as liver, spleen, peripheral nerves and muscle. Resistance to MD and disease risk have long been thought to be influenced both by genetic and environmental factors, the combination of which contributes to the observed outcome in an individual. We hypothesize that after MDV infection, genes related to MD-resistance or -susceptibility may exhibit different trends in chicken lines having varying resistance to MD. RESULTS: In order to study the mechanisms of resistance and susceptibility to MD, we performed genome-wide temporal expression analysis in MD-resistant line 63, susceptible line 72 and recombinant congenic strain M (RCS-M) chickens, which have a phenotype intermediate between lines 63 and 72 after MDV infection. Three time points of the MDV life cycle in chicken were selected for study: 5 days post infection (dpi), 10dpi and 21dpi, representing the early cytolytic, latent and late cytolytic stages, respectively. We observed similar gene expression profiles at the three time points in line 63 and RCS-M chickens that are different from line 72. Pathway analysis using Ingenuity Pathway Analysis (IPA) showed that MDV can broadly influence the chickens irrespective of whether they are resistant or susceptible to MD. However, some pathways like cardiac arrhythmia and cardiovascular disease were found to be affected only in line 72; while some networks related to cell-mediated immune response and antigen presentation were enriched only in line 63 and RCS-M. We identified 49, 78 and 36 candidate genes associated with MD resistance, at the three time points respectively, by considering genes having the same trend of expression change after MDV infection in lines 63 and RCS-M. On the other hand, by considering genes with the same trend of expression change after MDV infection in lines 72 and RCS-M, we identified 54, 78 and 43 genes that may be associated with MD-susceptibility. CONCLUSIONS: By testing temporal transcriptome changes using three representative chicken lines with different resistance to MD, we identified 163 candidate genes for MD-resistance and 175 candidate genes for MD-susceptibility over the three time points. Genes included in our resistance or susceptibility genes lists that are also involved in more than 5 biofunctions, such as CD8alpha, IL8, USP18, and CTLA4, are considered to be important genes involved in MD-resistance or -susceptibility. We were also able to identify several biofunctions related with immune response that we believe play an important role in MD-resistance.