Computational protocol: QTL Analysis of Type I and Type IIA Fibers in Soleus Muscle in a Cross between LG/J and SM/J Mouse Strains

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Protocol publication

[…] The soleus muscles were frozen in isopentane cooled in liquid nitrogen. Transverse sections from the belly of the muscle were cut at a thickness of 10 μm with a cryotome (Leica CM1850UV) at −20°C. The muscle samples were then subjected to ATPase staining (acid preincubation, pH 4.47) to distinguish between fiber types (Brooke and Kaiser, ).Microscopic images of stained sections were taken at ×5 and ×20 magnification (Figure ). Muscle fiber traits were manually analyzed using ImageJ software (NIH – version 1.43). The following phenotypes were assessed; muscle fiber number (type I and IIA) and percent of type I muscle fibers, cross-sectional area (CSA) of type I and type IIA fibers.Fiber CSA’s were measured on ×20 images. For each fiber type, 25 measurements were taken to obtain a value representing the mean CSA of type I or type IIA fibers for that muscle. This was deemed as a representative sample by empirical testing (the mean of 25 randomly selected fibers, ∼10% of the same type of fibers per muscle, deviated only 1 out of 100 times from that of all fibers of the muscle at P < 0.05). Muscle fiber numbers were assessed on ×5 images. As all fibers in mouse soleus pass through the belly of the muscle (Timson et al., ), this method provides an accurate estimate of the number of fibers constituting the muscle. Total number of type I fibers and total number of type IIA fibers were counted, permitting derivation of percentage of type I fibers. [...] The SPSS statistical package was used (SPSS Statistics 17.0). Data are presented as mean ± SD, unless otherwise stated.A two-way ANOVA was used to examine the effects of strain and sex on total number of fibers and percentage of type I fibers in the parental strains. The CSA of type I and type IIA fibers was analyzed using a two-way paired-measures ANOVA. In the F2 intercross, Pearson or Spearman correlation analyses were carried out depending on Kolmogorov–Smirnoff tests of normality. [...] The F2 mice genotyped at 160 SNP markers approximately evenly distributed across the genome were used (Cheng et al., ). Interval mapping analysis was performed using the R/qtl package (R 2.10.1; Broman et al., ). Due to the sex differences in muscle mass in these mice (Lionikas et al., ), and the discovery of sex-specific QTL in other studies (Lionikas et al., , ), we included sex as an additive and interacting covariate. Although solei from top and bottom quartiles of muscle weight were selectively phenotyped, the distribution of muscle fiber traits did not significantly deviate from the normal distribution. Significance thresholds were derived using 1000 permutations for each phenotype using R/qtl. The confidence intervals for each of the QTL were defined as the 1.5-LOD drop off on either side of the peak of the QTL (note that 1.5-LOD intervals may not be 95% confidence intervals; Manichaikul et al., ). This interval was expressed in physical map units (megabase) by using the nearest genotyped SNP that flanked the support interval. Limited sample sizes precluded a meaningful search for epistatic interactions.Terms for all significant QTL and for sex were included in a multiple regression model using the fitqtl function of the R/qtl package (Broman et al., ). Because of the limited sample size only the most robust QTL were subjected to this analysis. Terms not significantly (P ≥ 0.05) contributing to the regression model were dropped one at a time until only significant terms remained. […]

Pipeline specifications

Software tools SPSS, R/qtl
Applications Miscellaneous, WGS analysis
Organisms Mus musculus, Sus scrofa