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Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression

We evaluated differences in gene expression in pigs from the Porcine Reproductive and Respiratory Syndrome (PRRS) Host Genetics Consortium initiative showing a range of responses to PRRS virus infection. Pigs were allocated into four phenotypic groups according to their serum viral level and weight...

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Autores principales: Arceo, Maria E., Ernst, Catherine W., Lunney, Joan K., Choi, Igseo, Raney, Nancy E., Huang, Tinghua, Tuggle, Christopher K., Rowland, R. R. R., Steibel, Juan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546301/
https://www.ncbi.nlm.nih.gov/pubmed/23335940
http://dx.doi.org/10.3389/fgene.2012.00321
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author Arceo, Maria E.
Ernst, Catherine W.
Lunney, Joan K.
Choi, Igseo
Raney, Nancy E.
Huang, Tinghua
Tuggle, Christopher K.
Rowland, R. R. R.
Steibel, Juan P.
author_facet Arceo, Maria E.
Ernst, Catherine W.
Lunney, Joan K.
Choi, Igseo
Raney, Nancy E.
Huang, Tinghua
Tuggle, Christopher K.
Rowland, R. R. R.
Steibel, Juan P.
author_sort Arceo, Maria E.
collection PubMed
description We evaluated differences in gene expression in pigs from the Porcine Reproductive and Respiratory Syndrome (PRRS) Host Genetics Consortium initiative showing a range of responses to PRRS virus infection. Pigs were allocated into four phenotypic groups according to their serum viral level and weight gain. RNA obtained from blood at 0, 4, 7, 11, 14, 28, and 42 days post-infection (DPI) was hybridized to the 70-mer 20K Pigoligoarray. We used a blocked reference design for the microarray experiment. This allowed us to account for individual biological variation in gene expression, and to assess baseline effects before infection (0 DPI). Additionally, this design has the flexibility of incorporating future data for differential expression analysis. We focused on evaluating transcripts showing significant interaction of weight gain and serum viral level. We identified 491 significant comparisons [false discovery rate (FDR) = 10%] across all DPI and phenotypic groups. We corroborated the overall trend in direction and level of expression (measured as fold change) at 4 DPI using qPCR (r = 0.91, p ≤ 0.0007). At 4 and 7 DPI, network and functional analyses were performed to assess if immune related gene sets were enriched for genes differentially expressed (DE) across four phenotypic groups. We identified cell death function as being significantly associated (FDR ≤ 5%) with several networks enriched for DE transcripts. We found the genes interferon-alpha 1(IFNA1), major histocompatibility complex, class II, DQ alpha 1 (SLA-DQA1), and major histocompatibility complex, class II, DR alpha (SLA-DRA) to be DE (p ≤ 0.05) between phenotypic groups. Finally, we performed a power analysis to estimate sample size and sampling time-points for future experiments. We concluded the best scenario for investigation of early response to PRRSV infection consists of sampling at 0, 4, and 7 DPI using about 30 pigs per phenotypic group.
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spelling pubmed-35463012013-01-18 Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression Arceo, Maria E. Ernst, Catherine W. Lunney, Joan K. Choi, Igseo Raney, Nancy E. Huang, Tinghua Tuggle, Christopher K. Rowland, R. R. R. Steibel, Juan P. Front Genet Genetics We evaluated differences in gene expression in pigs from the Porcine Reproductive and Respiratory Syndrome (PRRS) Host Genetics Consortium initiative showing a range of responses to PRRS virus infection. Pigs were allocated into four phenotypic groups according to their serum viral level and weight gain. RNA obtained from blood at 0, 4, 7, 11, 14, 28, and 42 days post-infection (DPI) was hybridized to the 70-mer 20K Pigoligoarray. We used a blocked reference design for the microarray experiment. This allowed us to account for individual biological variation in gene expression, and to assess baseline effects before infection (0 DPI). Additionally, this design has the flexibility of incorporating future data for differential expression analysis. We focused on evaluating transcripts showing significant interaction of weight gain and serum viral level. We identified 491 significant comparisons [false discovery rate (FDR) = 10%] across all DPI and phenotypic groups. We corroborated the overall trend in direction and level of expression (measured as fold change) at 4 DPI using qPCR (r = 0.91, p ≤ 0.0007). At 4 and 7 DPI, network and functional analyses were performed to assess if immune related gene sets were enriched for genes differentially expressed (DE) across four phenotypic groups. We identified cell death function as being significantly associated (FDR ≤ 5%) with several networks enriched for DE transcripts. We found the genes interferon-alpha 1(IFNA1), major histocompatibility complex, class II, DQ alpha 1 (SLA-DQA1), and major histocompatibility complex, class II, DR alpha (SLA-DRA) to be DE (p ≤ 0.05) between phenotypic groups. Finally, we performed a power analysis to estimate sample size and sampling time-points for future experiments. We concluded the best scenario for investigation of early response to PRRSV infection consists of sampling at 0, 4, and 7 DPI using about 30 pigs per phenotypic group. Frontiers Media S.A. 2013-01-16 /pmc/articles/PMC3546301/ /pubmed/23335940 http://dx.doi.org/10.3389/fgene.2012.00321 Text en Copyright © 2013 Arceo, Ernst, Lunney, Choi, Raney, Huang, Tuggle, Rowland and Steibel. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Genetics
Arceo, Maria E.
Ernst, Catherine W.
Lunney, Joan K.
Choi, Igseo
Raney, Nancy E.
Huang, Tinghua
Tuggle, Christopher K.
Rowland, R. R. R.
Steibel, Juan P.
Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title_full Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title_fullStr Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title_full_unstemmed Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title_short Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
title_sort characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546301/
https://www.ncbi.nlm.nih.gov/pubmed/23335940
http://dx.doi.org/10.3389/fgene.2012.00321
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