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pmid:27872814

Transcriptional profiles of WNV neurovirulence in a genetically diverse Collaborative Cross population.

Richard Green · Courtney Wilkins · Sunil Thomas · Aimee Sekine · Renee C Ireton · Martin T Ferris · Duncan M Hendrick · Kathleen Voss · Fernando Pardo-Manuel de Villena · Ralph S Baric · Mark T Heise · Michael Gale

Genomics data · 2016 doi:10.1016/j.gdata.2016.10.005

Paper

complete

Experiment

partial

Data

partial

Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:27872814
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science-record
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2026-11-01T15:40:21Z
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title
Transcriptional profiles of WNV neurovirulence in a genetically diverse Collaborative Cross population.
doi
10.1016/j.gdata.2016.10.005
pmid
27872814
authors array · 12 items
[0]
Richard Green
[1]
Courtney Wilkins
[2]
Sunil Thomas
[3]
Aimee Sekine
[4]
Renee C Ireton
[5]
Martin T Ferris
[6]
Duncan M Hendrick
[7]
Kathleen Voss
[8]
Fernando Pardo-Manuel de Villena
[9]
Ralph S Baric
[10]
Mark T Heise
[11]
Michael Gale
journal
Genomics data
year
2016
abstract
West Nile Virus (WNV) is a mosquito-transmitted virus from the Flaviviridae family that causes fever in 1 in 5 infected people. WNV can also become neuro-invasive and cross the blood-brain barrier leading to severe neurological symptoms in a subset of WNV infected individuals [1]. WNV neuro-invasion is believed to be influenced by a number of factors including host genetics. In order to explore these effects and recapitulate the complex immune genetic differences among individuals, we studied gene expression following WNV infection in the Collaborative Cross (CC) model. The CC is a mouse genetics resource composed of > 70 independently bred, octo-parental recombinant inbred mouse lines [2]. To identify the individual host gene expression signatures influencing protection or susceptibility to WNV disease and WNV neuroinvasion, we used the nanostring nsolver platform to quantify gene expression in brain tissue isolated from WNV-infected CC mice at days 4, 7 and 12 post-infection [3]. This nanostring technology provided a high throughput, non-amplification based mRNA quantitation method to detect immune genes involved in neuro-invasion. Data was deposited into the Gene Expression Omnibus (GEO) under accession GSE85999.
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In an alternate approach, we performed differential expression analysis across all genes from filtered gene counts (mean ≥ 20) and then normalized the raw counts using the voom Bioconductor package in limma. Linear modeling was then performed in limma using R [1], [6], [7].
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sections[10] "Statistical modeling" paragraph 2
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In an alternate approach, we performed differential expression analysis across all genes from filtered gene counts (mean ≥ 20) and then normalized the raw counts using the voom Bioconductor package in limma. Linear modeling was then performed in limma using R [1], [6], [7].
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sections[9] "Nanostring analysis" paragraph 2
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Identifiers and phenotypes for CC dRIXs (collaborative cross discovery recombinant intercrosses).
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WNV in CNS
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CC11/Unc_x_CC042/GeniUNc
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8036 × 18018
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Asymptomatic (no WNV)
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8002 × 3032
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15155 × 8054
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8024 × 8049
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8021 × 16072
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In an alternate approach, we performed differential expression analysis across all genes from filtered gene counts (mean ≥ 20) and then normalized the raw counts using the voom Bioconductor package in limma. Linear modeling was then performed in limma using R [1], [6], [7].
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