Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice

被引:66
作者
Bottomly, Daniel [1 ,2 ]
Ferris, Martin T. [2 ,3 ]
Aicher, Lauri D. [2 ,4 ]
Rosenzweig, Elizabeth [2 ,4 ]
Whitmore, Alan [2 ,3 ]
Aylor, David L. [3 ,5 ]
Haagmans, Bart L. [6 ]
Gralinski, Lisa E. [2 ,7 ]
Bradel-Tretheway, Birgit G. [2 ,4 ]
Bryan, Janine T. [2 ,4 ]
Threadgill, David W. [8 ]
de Villena, Fernando Pardo-Manuel [2 ,3 ,5 ]
Baric, Ralph S. [2 ,7 ,9 ]
Katze, Michael G. [2 ,4 ,9 ]
Heise, Mark [2 ,3 ]
McWeeney, Shannon K. [1 ,2 ,10 ,11 ,12 ]
机构
[1] Oregon Hlth & Sci Univ, Oregon Clin & Translat Res Inst, Portland, OR 97239 USA
[2] Pacific NW Reg Ctr Excellence Biodef & Emerging I, Beaverton, OR 97006 USA
[3] Univ N Carolina, Dept Genet, Chapel Hill, NC 27599 USA
[4] Univ Washington, Sch Med, Dept Microbiol, Seattle, WA 98195 USA
[5] Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27514 USA
[6] Erasmus MC, NL-3000 CA Rotterdam, Netherlands
[7] Univ N Carolina, Dept Epidemiol, Chapel Hill, NC 27599 USA
[8] N Carolina State Univ, Dept Genet, Raleigh, NC 27695 USA
[9] Univ N Carolina, Dept Microbiol & Immunol, Chapel Hill, NC 27599 USA
[10] Oregon Hlth & Sci Univ, Div Bioinformat & Computat Biol, Portland, OR 97239 USA
[11] Oregon Hlth & Sci Univ, Div Biostat Publ Hlth & Preventat Med, Portland, OR 97239 USA
[12] Oregon Hlth & Sci Univ, OHSU Knight Canc Inst, Portland, OR 97239 USA
来源
G3-GENES GENOMES GENETICS | 2012年 / 2卷 / 02期
基金
美国国家卫生研究院;
关键词
VIRUS-INFECTION; IMMUNE-RESPONSES; GENETIC-ANALYSIS; AGED MICE; ARRAY; LUNG; SUSCEPTIBILITY; IDENTIFICATION; NORMALIZATION; PROTECTION;
D O I
10.1534/g3.111.001800
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe ("high") and mild ("low") response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative regulatory regions potentially controlling their expression. Twenty-one significant expression quantitative trait loci were identified, which allowed direct examination of genes associated with regulation of host response to infection. To perform initial validation of our findings, quantitative polymerase chain reaction was performed in the infected founder strains, and we were able to confirm or partially confirm more than 70% of those tested. In addition, we explored putative causal and reactive (downstream) relationships between the significantly regulated genes and others in the high or low response groups using structural equation modeling. By using systems approaches and a genetically diverse population, we were able to develop a novel framework for identifying the underlying biological subnetworks under host genetic control during influenza virus infection.
引用
收藏
页码:213 / 221
页数:9
相关论文
共 66 条
[1]   Evidence for a heritable predisposition to death due to influenza [J].
Albright, Frederick S. ;
Orlando, Patricia ;
Pavia, Andrew T. ;
Jackson, George G. ;
Albright, Lisa A. Cannon .
JOURNAL OF INFECTIOUS DISEASES, 2008, 197 (01) :18-24
[2]  
[Anonymous], 2005, Limma: linear models for microarray data
[3]   The search for host genetic factors of HIV/AIDS pathogenesis in the post-genome era: Progress to date and new avenues for discovery [J].
Aouizerat B.E. ;
Pearce C.L. ;
Miaskowski C. .
Current HIV/AIDS Reports, 2011, 8 (1) :38-44
[4]   Direct interaction between metastasis-associated protein 1 and endophilin 3 [J].
Aramaki, Y ;
Ogawa, K ;
Toh, Y ;
Ito, T ;
Akimitsu, N ;
Hamamoto, H ;
Sekimizu, K ;
Matsusue, K ;
Kono, A ;
Iguchi, H ;
Takiguchi, S .
FEBS LETTERS, 2005, 579 (17) :3731-3736
[5]   Immune responses and protection in different strains of aged mice immunized intranasally with an adjuvant-combined influenza vaccine [J].
Asanuma, H ;
Hirokawa, K ;
Uchiyama, M ;
Suzuki, Y ;
Aizawa, C ;
Kurata, T ;
Sata, T ;
Tamura, S .
VACCINE, 2001, 19 (28-29) :3981-3989
[6]   Using genetic markers to orient the edges in quantitative trait networks: The NEO software [J].
Aten, Jason E. ;
Fuller, Tova F. ;
Lusis, Aldons J. ;
Horvath, Steve .
BMC SYSTEMS BIOLOGY, 2008, 2
[7]   Genetic analysis of complex traits in the emerging Collaborative Cross [J].
Aylor, David L. ;
Valdar, William ;
Foulds-Mathes, Wendy ;
Buus, Ryan J. ;
Verdugo, Ricardo A. ;
Baric, Ralph S. ;
Ferris, Martin T. ;
Frelinger, Jeff A. ;
Heise, Mark ;
Frieman, Matt B. ;
Gralinski, Lisa E. ;
Bell, Timothy A. ;
Didion, John D. ;
Hua, Kunjie ;
Nehrenberg, Derrick L. ;
Powell, Christine L. ;
Steigerwalt, Jill ;
Xie, Yuying ;
Kelada, Samir N. P. ;
Collins, Francis S. ;
Yang, Ivana V. ;
Schwartz, David A. ;
Branstetter, Lisa A. ;
Chesler, Elissa J. ;
Miller, Darla R. ;
Spence, Jason ;
Liu, Eric Yi ;
McMillan, Leonard ;
Sarkar, Abhishek ;
Wang, Jeremy ;
Wang, Wei ;
Zhang, Qi ;
Broman, Karl W. ;
Korstanje, Ron ;
Durrant, Caroline ;
Mott, Richard ;
Iraqi, Fuad A. ;
Pomp, Daniel ;
Threadgill, David ;
de Villena, Fernando Pardo-Manuel ;
Churchill, Gary A. .
GENOME RESEARCH, 2011, 21 (08) :1213-1222
[8]  
Bates D., 2011, lme4: Linear mixed-effects models using S4 classes
[9]  
BENDER BS, 1995, J LAB CLIN MED, V126, P169
[10]  
Benjamini Y, 2001, ANN STAT, V29, P1165