How to correlate phenotype values with gene expression levels

Question

[afli]

Hello,

In my transgenic rice (over-expression gene A), there are several lines with different expression levels, I've measured phenotype XX for N individuals in each line. So how can I make the conclusion whether A has effect on phenotype XX ?

For example, I have 10 lines with diverse expression levels of gene A, each line has 10 individuals, I measured each individuals in each line. I can make a boxplot to see this, but how can I get the significance extent. Or just get the mean value of phenotype in each line, then do pearson correlation between phenotype mean in each line and the expression levels?

Thank you very much!

[WouterDeCoster]

That's called a QTL study, so you could start googling based on that.

Answer 1

[Asaf]

What you can do is linear regression (lm) using the expression of gene A to explain the phenotype, you can add any covariate (like batch or plot or whatever) to the regression to correct for it.

Using R it's simply lm(), in the summary you can get the significance and the effect.

There are other statistical methods, Tukey's test, for instance is widely used in agriculture when you compare different lines of crop.

[afli]

Thank you asaf, I'll try the lm() function in R.