Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

Arimantas Lionikas, Caroline Meharg, Jonathan M J Derry, Aivaras Ratkevicius, Andrew M Carroll, David J Vandenbergh, David A Blizard

Research output: Contribution to journalArticle

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Abstract

ABSTRACT:

BACKGROUND: We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.
RESULTS:

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).
CONCLUSION:

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.
Original languageEnglish
Article number592
Number of pages14
JournalBMC Genomics
Volume13
Early online date5 Nov 2012
DOIs
Publication statusPublished - 5 Nov 2012

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Quantitative Trait Loci
Skeletal Muscle
RNA
Muscles
Genes
Transcriptome
NADH Tetrazolium Reductase
Bayes Theorem
Gene Expression Profiling
Confidence Intervals
Staining and Labeling
Weights and Measures

Cite this

Lionikas, A., Meharg, C., Derry, J. M. J., Ratkevicius, A., Carroll, A. M., Vandenbergh, D. J., & Blizard, D. A. (2012). Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses. BMC Genomics, 13, [592]. https://doi.org/10.1186/1471-2164-13-592

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses. / Lionikas, Arimantas; Meharg, Caroline; Derry, Jonathan M J; Ratkevicius, Aivaras; Carroll, Andrew M; Vandenbergh, David J; Blizard, David A.

In: BMC Genomics, Vol. 13, 592, 05.11.2012.

Research output: Contribution to journalArticle

Lionikas, A, Meharg, C, Derry, JMJ, Ratkevicius, A, Carroll, AM, Vandenbergh, DJ & Blizard, DA 2012, 'Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses', BMC Genomics, vol. 13, 592. https://doi.org/10.1186/1471-2164-13-592
Lionikas, Arimantas ; Meharg, Caroline ; Derry, Jonathan M J ; Ratkevicius, Aivaras ; Carroll, Andrew M ; Vandenbergh, David J ; Blizard, David A. / Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses. In: BMC Genomics. 2012 ; Vol. 13.
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